WorldWideScience

Sample records for modeling sensitivity studies

  1. Sensitivity study of reduced models of the activated sludge process ...

    African Journals Online (AJOL)

    2009-08-07

    Aug 7, 2009 ... Sensitivity study of reduced models of the activated sludge process, for the purposes of parameter estimation and process optimisation: Benchmark process with ASM1 and UCT reduced biological models. S du Plessis and R Tzoneva*. Department of Electrical Engineering, Cape Peninsula University of ...

  2. Sensitivity study of reduced models of the activated sludge process ...

    African Journals Online (AJOL)

    The problem of derivation and calculation of sensitivity functions for all parameters of the mass balance reduced model of the COST benchmark activated sludge plant is formulated and solved. The sensitivity functions, equations and augmented sensitivity state space models are derived for the cases of ASM1 and UCT ...

  3. A piecewise modeling approach for climate sensitivity studies: Tests with a shallow-water model

    Science.gov (United States)

    Shao, Aimei; Qiu, Chongjian; Niu, Guo-Yue

    2015-10-01

    In model-based climate sensitivity studies, model errors may grow during continuous long-term integrations in both the "reference" and "perturbed" states and hence the climate sensitivity (defined as the difference between the two states). To reduce the errors, we propose a piecewise modeling approach that splits the continuous long-term simulation into subintervals of sequential short-term simulations, and updates the modeled states through re-initialization at the end of each subinterval. In the re-initialization processes, this approach updates the reference state with analysis data and updates the perturbed states with the sum of analysis data and the difference between the perturbed and the reference states, thereby improving the credibility of the modeled climate sensitivity. We conducted a series of experiments with a shallow-water model to evaluate the advantages of the piecewise approach over the conventional continuous modeling approach. We then investigated the impacts of analysis data error and subinterval length used in the piecewise approach on the simulations of the reference and perturbed states as well as the resulting climate sensitivity. The experiments show that the piecewise approach reduces the errors produced by the conventional continuous modeling approach, more effectively when the analysis data error becomes smaller and the subinterval length is shorter. In addition, we employed a nudging assimilation technique to solve possible spin-up problems caused by re-initializations by using analysis data that contain inconsistent errors between mass and velocity. The nudging technique can effectively diminish the spin-up problem, resulting in a higher modeling skill.

  4. Sensitivity analysis approaches applied to systems biology models.

    Science.gov (United States)

    Zi, Z

    2011-11-01

    With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

  5. Efficient stochastic approaches for sensitivity studies of an Eulerian large-scale air pollution model

    Science.gov (United States)

    Dimov, I.; Georgieva, R.; Todorov, V.; Ostromsky, Tz.

    2017-10-01

    Reliability of large-scale mathematical models is an important issue when such models are used to support decision makers. Sensitivity analysis of model outputs to variation or natural uncertainties of model inputs is crucial for improving the reliability of mathematical models. A comprehensive experimental study of Monte Carlo algorithms based on Sobol sequences for multidimensional numerical integration has been done. A comparison with Latin hypercube sampling and a particular quasi-Monte Carlo lattice rule based on generalized Fibonacci numbers has been presented. The algorithms have been successfully applied to compute global Sobol sensitivity measures corresponding to the influence of several input parameters (six chemical reactions rates and four different groups of pollutants) on the concentrations of important air pollutants. The concentration values have been generated by the Unified Danish Eulerian Model. The sensitivity study has been done for the areas of several European cities with different geographical locations. The numerical tests show that the stochastic algorithms under consideration are efficient for multidimensional integration and especially for computing small by value sensitivity indices. It is a crucial element since even small indices may be important to be estimated in order to achieve a more accurate distribution of inputs influence and a more reliable interpretation of the mathematical model results.

  6. Sensitivity model study of regional mercury dispersion in the atmosphere

    Science.gov (United States)

    Gencarelli, Christian N.; Bieser, Johannes; Carbone, Francesco; De Simone, Francesco; Hedgecock, Ian M.; Matthias, Volker; Travnikov, Oleg; Yang, Xin; Pirrone, Nicola

    2017-01-01

    Atmospheric deposition is the most important pathway by which Hg reaches marine ecosystems, where it can be methylated and enter the base of food chain. The deposition, transport and chemical interactions of atmospheric Hg have been simulated over Europe for the year 2013 in the framework of the Global Mercury Observation System (GMOS) project, performing 14 different model sensitivity tests using two high-resolution three-dimensional chemical transport models (CTMs), varying the anthropogenic emission datasets, atmospheric Br input fields, Hg oxidation schemes and modelling domain boundary condition input. Sensitivity simulation results were compared with observations from 28 monitoring sites in Europe to assess model performance and particularly to analyse the influence of anthropogenic emission speciation and the Hg0(g) atmospheric oxidation mechanism. The contribution of anthropogenic Hg emissions, their speciation and vertical distribution are crucial to the simulated concentration and deposition fields, as is also the choice of Hg0(g) oxidation pathway. The areas most sensitive to changes in Hg emission speciation and the emission vertical distribution are those near major sources, but also the Aegean and the Black seas, the English Channel, the Skagerrak Strait and the northern German coast. Considerable influence was found also evident over the Mediterranean, the North Sea and Baltic Sea and some influence is seen over continental Europe, while this difference is least over the north-western part of the modelling domain, which includes the Norwegian Sea and Iceland. The Br oxidation pathway produces more HgII(g) in the lower model levels, but overall wet deposition is lower in comparison to the simulations which employ an O3 / OH oxidation mechanism. The necessity to perform continuous measurements of speciated Hg and to investigate the local impacts of Hg emissions and deposition, as well as interactions dependent on land use and vegetation, forests, peat

  7. A Sensitivity Analysis Method to Study the Behavior of Complex Process-based Models

    Science.gov (United States)

    Brugnach, M.; Neilson, R.; Bolte, J.

    2001-12-01

    The use of process-based models as a tool for scientific inquiry is becoming increasingly relevant in ecosystem studies. Process-based models are artificial constructs that simulate the system by mechanistically mimicking the functioning of its component processes. Structurally, a process-based model can be characterized, in terms of its processes and the relationships established among them. Each process comprises a set of functional relationships among several model components (e.g., state variables, parameters and input data). While not encoded explicitly, the dynamics of the model emerge from this set of components and interactions organized in terms of processes. It is the task of the modeler to guarantee that the dynamics generated are appropriate and semantically equivalent to the phenomena being modeled. Despite the availability of techniques to characterize and understand model behavior, they do not suffice to completely and easily understand how a complex process-based model operates. For example, sensitivity analysis studies model behavior by determining the rate of change in model output as parameters or input data are varied. One of the problems with this approach is that it considers the model as a "black box", and it focuses on explaining model behavior by analyzing the relationship input-output. Since, these models have a high degree of non-linearity, understanding how the input affects an output can be an extremely difficult task. Operationally, the application of this technique may constitute a challenging task because complex process-based models are generally characterized by a large parameter space. In order to overcome some of these difficulties, we propose a method of sensitivity analysis to be applicable to complex process-based models. This method focuses sensitivity analysis at the process level, and it aims to determine how sensitive the model output is to variations in the processes. Once the processes that exert the major influence in

  8. Sensitivity Analysis in Sequential Decision Models.

    Science.gov (United States)

    Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet

    2017-02-01

    Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.

  9. Context Sensitive Modeling of Cancer Drug Sensitivity.

    Directory of Open Access Journals (Sweden)

    Bo-Juen Chen

    Full Text Available Recent screening of drug sensitivity in large panels of cancer cell lines provides a valuable resource towards developing algorithms that predict drug response. Since more samples provide increased statistical power, most approaches to prediction of drug sensitivity pool multiple cancer types together without distinction. However, pan-cancer results can be misleading due to the confounding effects of tissues or cancer subtypes. On the other hand, independent analysis for each cancer-type is hampered by small sample size. To balance this trade-off, we present CHER (Contextual Heterogeneity Enabled Regression, an algorithm that builds predictive models for drug sensitivity by selecting predictive genomic features and deciding which ones should-and should not-be shared across different cancers, tissues and drugs. CHER provides significantly more accurate models of drug sensitivity than comparable elastic-net-based models. Moreover, CHER provides better insight into the underlying biological processes by finding a sparse set of shared and type-specific genomic features.

  10. Measuring sensitivity in pharmacoeconomic studies. Refining point sensitivity and range sensitivity by incorporating probability distributions.

    Science.gov (United States)

    Nuijten, M J

    1999-07-01

    The aim of the present study is to describe a refinement of a previously presented method, based on the concept of point sensitivity, to deal with uncertainty in economic studies. The original method was refined by the incorporation of probability distributions which allow a more accurate assessment of the level of uncertainty in the model. In addition, a bootstrap method was used to create a probability distribution for a fixed input variable based on a limited number of data points. The original method was limited in that the sensitivity measurement was based on a uniform distribution of the variables and that the overall sensitivity measure was based on a subjectively chosen range which excludes the impact of values outside the range on the overall sensitivity. The concepts of the refined method were illustrated using a Markov model of depression. The application of the refined method substantially changed the ranking of the most sensitive variables compared with the original method. The response rate became the most sensitive variable instead of the 'per diem' for hospitalisation. The refinement of the original method yields sensitivity outcomes, which greater reflect the real uncertainty in economic studies.

  11. Climate stability and sensitivity in some simple conceptual models

    Energy Technology Data Exchange (ETDEWEB)

    Bates, J. Ray [University College Dublin, Meteorology and Climate Centre, School of Mathematical Sciences, Dublin (Ireland)

    2012-02-15

    A theoretical investigation of climate stability and sensitivity is carried out using three simple linearized models based on the top-of-the-atmosphere energy budget. The simplest is the zero-dimensional model (ZDM) commonly used as a conceptual basis for climate sensitivity and feedback studies. The others are two-zone models with tropics and extratropics of equal area; in the first of these (Model A), the dynamical heat transport (DHT) between the zones is implicit, in the second (Model B) it is explicitly parameterized. It is found that the stability and sensitivity properties of the ZDM and Model A are very similar, both depending only on the global-mean radiative response coefficient and the global-mean forcing. The corresponding properties of Model B are more complex, depending asymmetrically on the separate tropical and extratropical values of these quantities, as well as on the DHT coefficient. Adopting Model B as a benchmark, conditions are found under which the validity of the ZDM and Model A as climate sensitivity models holds. It is shown that parameter ranges of physical interest exist for which such validity may not hold. The 2 x CO{sub 2} sensitivities of the simple models are studied and compared. Possible implications of the results for sensitivities derived from GCMs and palaeoclimate data are suggested. Sensitivities for more general scenarios that include negative forcing in the tropics (due to aerosols, inadvertent or geoengineered) are also studied. Some unexpected outcomes are found in this case. These include the possibility of a negative global-mean temperature response to a positive global-mean forcing, and vice versa. (orig.)

  12. Model dependence of isospin sensitive observables at high densities

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Wen-Mei [Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); School of Science, Huzhou Teachers College, Huzhou 313000 (China); Yong, Gao-Chan, E-mail: yonggaochan@impcas.ac.cn [Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000 (China); State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190 (China); Wang, Yongjia [School of Science, Huzhou Teachers College, Huzhou 313000 (China); School of Nuclear Science and Technology, Lanzhou University, Lanzhou 730000 (China); Li, Qingfeng [School of Science, Huzhou Teachers College, Huzhou 313000 (China); Zhang, Hongfei [School of Nuclear Science and Technology, Lanzhou University, Lanzhou 730000 (China); State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190 (China); Zuo, Wei [Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000 (China); State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190 (China)

    2013-10-07

    Within two different frameworks of isospin-dependent transport model, i.e., Boltzmann–Uehling–Uhlenbeck (IBUU04) and Ultrarelativistic Quantum Molecular Dynamics (UrQMD) transport models, sensitive probes of nuclear symmetry energy are simulated and compared. It is shown that neutron to proton ratio of free nucleons, π{sup −}/π{sup +} ratio as well as isospin-sensitive transverse and elliptic flows given by the two transport models with their “best settings”, all have obvious differences. Discrepancy of numerical value of isospin-sensitive n/p ratio of free nucleon from the two models mainly originates from different symmetry potentials used and discrepancies of numerical value of charged π{sup −}/π{sup +} ratio and isospin-sensitive flows mainly originate from different isospin-dependent nucleon–nucleon cross sections. These demonstrations call for more detailed studies on the model inputs (i.e., the density- and momentum-dependent symmetry potential and the isospin-dependent nucleon–nucleon cross section in medium) of isospin-dependent transport model used. The studies of model dependence of isospin sensitive observables can help nuclear physicists to pin down the density dependence of nuclear symmetry energy through comparison between experiments and theoretical simulations scientifically.

  13. A global sensitivity analysis approach for morphogenesis models

    KAUST Repository

    Boas, Sonja E. M.

    2015-11-21

    Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

  14. A global sensitivity analysis approach for morphogenesis models.

    Science.gov (United States)

    Boas, Sonja E M; Navarro Jimenez, Maria I; Merks, Roeland M H; Blom, Joke G

    2015-11-21

    Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such 'black-box' models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all 'black-box' models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

  15. Laboratory measurements and model sensitivity studies of dust deposition ice nucleation

    Directory of Open Access Journals (Sweden)

    G. Kulkarni

    2012-08-01

    Full Text Available We investigated the ice nucleating properties of mineral dust particles to understand the sensitivity of simulated cloud properties to two different representations of contact angle in the Classical Nucleation Theory (CNT. These contact angle representations are based on two sets of laboratory deposition ice nucleation measurements: Arizona Test Dust (ATD particles of 100, 300 and 500 nm sizes were tested at three different temperatures (−25, −30 and −35 °C, and 400 nm ATD and kaolinite dust species were tested at two different temperatures (−30 and −35 °C. These measurements were used to derive the onset relative humidity with respect to ice (RHice required to activate 1% of dust particles as ice nuclei, from which the onset single contact angles were then calculated based on CNT. For the probability density function (PDF representation, parameters of the log-normal contact angle distribution were determined by fitting CNT-predicted activated fraction to the measurements at different RHice. Results show that onset single contact angles vary from ~18 to 24 degrees, while the PDF parameters are sensitive to the measurement conditions (i.e. temperature and dust size. Cloud modeling simulations were performed to understand the sensitivity of cloud properties (i.e. ice number concentration, ice water content, and cloud initiation times to the representation of contact angle and PDF distribution parameters. The model simulations show that cloud properties are sensitive to onset single contact angles and PDF distribution parameters. The comparison of our experimental results with other studies shows that under similar measurement conditions the onset single contact angles are consistent within ±2.0 degrees, while our derived PDF parameters have larger discrepancies.

  16. Sensitivity of hydrological modeling to meteorological data and implications for climate change studies

    International Nuclear Information System (INIS)

    Roy, L.G.; Roy, R.; Desrochers, G.E.; Vaillancourt, C.; Chartier, I.

    2008-01-01

    There are uncertainties associated with the use of hydrological models. This study aims to analyse one source of uncertainty associated with hydrological modeling, particularly in the context of climate change studies on water resources. Additional intent of this study is to compare the ability of some meteorological data sources, used in conjunction with an hydrological model, to reproduce the hydrologic regime of a watershed. A case study on a watershed of south-western Quebec, Canada using five different sources of meteorological data as input to an offline hydrological model are presented in this paper. Data used came from weather stations, NCEP reanalysis, ERA40 reanalysis and two Canadian Regional Climate Model (CRCM) runs driven by NCEP and ERA40 reanalysis, providing atmospheric driving boundary conditions to this limited-area climate model. To investigate the sensitivity of simulated streamflow to different sources of meteorological data, we first calibrated the hydrological model with each of the meteorological data sets over the 1961-1980 period. The five different sets of parameters of the hydrological model were then used to simulate streamflow of the 1981-2000 validation period with the five meteorological data sets as inputs. The 25 simulated streamflow series have been compared to the observed streamflow of the watershed. The five meteorological data sets do not have the same ability, when used with the hydrological model, to reproduce streamflow. Our results show also that the hydrological model parameters used may have an important influence on results such as water balance, but it is linked with the differences that may have in the characteristics of the meteorological data used. For climate change impacts assessments on water resources, we have found that there is an uncertainty associated with the meteorological data used to calibrate the model. For expected changes on mean annual flows of the Chateauguay River, our results vary from a small

  17. Parametric Sensitivity Analysis of the WAVEWATCH III Model

    Directory of Open Access Journals (Sweden)

    Beng-Chun Lee

    2009-01-01

    Full Text Available The parameters in numerical wave models need to be calibrated be fore a model can be applied to a specific region. In this study, we selected the 8 most important parameters from the source term of the WAVEWATCH III model and subjected them to sensitivity analysis to evaluate the sensitivity of the WAVEWATCH III model to the selected parameters to determine how many of these parameters should be considered for further discussion, and to justify the significance priority of each parameter. After ranking each parameter by sensitivity and assessing their cumulative impact, we adopted the ARS method to search for the optimal values of those parameters to which the WAVEWATCH III model is most sensitive by comparing modeling results with ob served data at two data buoys off the coast of north eastern Taiwan; the goal being to find optimal parameter values for improved modeling of wave development. The procedure adopting optimal parameters in wave simulations did improve the accuracy of the WAVEWATCH III model in comparison to default runs based on field observations at two buoys.

  18. High-Level Waste Glass Formulation Model Sensitivity Study 2009 Glass Formulation Model Versus 1996 Glass Formulation Model

    International Nuclear Information System (INIS)

    Belsher, J.D.; Meinert, F.L.

    2009-01-01

    This document presents the differences between two HLW glass formulation models (GFM): The 1996 GFM and 2009 GFM. A glass formulation model is a collection of glass property correlations and associated limits, as well as model validity and solubility constraints; it uses the pretreated HLW feed composition to predict the amount and composition of glass forming additives necessary to produce acceptable HLW glass. The 2009 GFM presented in this report was constructed as a nonlinear optimization calculation based on updated glass property data and solubility limits described in PNNL-18501 (2009). Key mission drivers such as the total mass of HLW glass and waste oxide loading are compared between the two glass formulation models. In addition, a sensitivity study was performed within the 2009 GFM to determine the effect of relaxing various constraints on the predicted mass of the HLW glass.

  19. Parametric uncertainty and global sensitivity analysis in a model of the carotid bifurcation: Identification and ranking of most sensitive model parameters.

    Science.gov (United States)

    Gul, R; Bernhard, S

    2015-11-01

    In computational cardiovascular models, parameters are one of major sources of uncertainty, which make the models unreliable and less predictive. In order to achieve predictive models that allow the investigation of the cardiovascular diseases, sensitivity analysis (SA) can be used to quantify and reduce the uncertainty in outputs (pressure and flow) caused by input (electrical and structural) model parameters. In the current study, three variance based global sensitivity analysis (GSA) methods; Sobol, FAST and a sparse grid stochastic collocation technique based on the Smolyak algorithm were applied on a lumped parameter model of carotid bifurcation. Sensitivity analysis was carried out to identify and rank most sensitive parameters as well as to fix less sensitive parameters at their nominal values (factor fixing). In this context, network location and temporal dependent sensitivities were also discussed to identify optimal measurement locations in carotid bifurcation and optimal temporal regions for each parameter in the pressure and flow waves, respectively. Results show that, for both pressure and flow, flow resistance (R), diameter (d) and length of the vessel (l) are sensitive within right common carotid (RCC), right internal carotid (RIC) and right external carotid (REC) arteries, while compliance of the vessels (C) and blood inertia (L) are sensitive only at RCC. Moreover, Young's modulus (E) and wall thickness (h) exhibit less sensitivities on pressure and flow at all locations of carotid bifurcation. Results of network location and temporal variabilities revealed that most of sensitivity was found in common time regions i.e. early systole, peak systole and end systole. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Sensitivity Analysis for Urban Drainage Modeling Using Mutual Information

    Directory of Open Access Journals (Sweden)

    Chuanqi Li

    2014-11-01

    Full Text Available The intention of this paper is to evaluate the sensitivity of the Storm Water Management Model (SWMM output to its input parameters. A global parameter sensitivity analysis is conducted in order to determine which parameters mostly affect the model simulation results. Two different methods of sensitivity analysis are applied in this study. The first one is the partial rank correlation coefficient (PRCC which measures nonlinear but monotonic relationships between model inputs and outputs. The second one is based on the mutual information which provides a general measure of the strength of the non-monotonic association between two variables. Both methods are based on the Latin Hypercube Sampling (LHS of the parameter space, and thus the same datasets can be used to obtain both measures of sensitivity. The utility of the PRCC and the mutual information analysis methods are illustrated by analyzing a complex SWMM model. The sensitivity analysis revealed that only a few key input variables are contributing significantly to the model outputs; PRCCs and mutual information are calculated and used to determine and rank the importance of these key parameters. This study shows that the partial rank correlation coefficient and mutual information analysis can be considered effective methods for assessing the sensitivity of the SWMM model to the uncertainty in its input parameters.

  1. Sensitivity study of CFD turbulent models for natural convection analysis

    International Nuclear Information System (INIS)

    Yu sun, Park

    2007-01-01

    The buoyancy driven convective flow fields are steady circulatory flows which were made between surfaces maintained at two fixed temperatures. They are ubiquitous in nature and play an important role in many engineering applications. Application of a natural convection can reduce the costs and efforts remarkably. This paper focuses on the sensitivity study of turbulence analysis using CFD (Computational Fluid Dynamics) for a natural convection in a closed rectangular cavity. Using commercial CFD code, FLUENT and various turbulent models were applied to the turbulent flow. Results from each CFD model will be compared each other in the viewpoints of grid resolution and flow characteristics. It has been showed that: -) obtaining general flow characteristics is possible with relatively coarse grid; -) there is no significant difference between results from finer grid resolutions than grid with y + + is defined as y + = ρ*u*y/μ, u being the wall friction velocity, y being the normal distance from the center of the cell to the wall, ρ and μ being respectively the fluid density and the fluid viscosity; -) the K-ε models show a different flow characteristic from K-ω models or from the Reynolds Stress Model (RSM); and -) the y + parameter is crucial for the selection of the appropriate turbulence model to apply within the simulation

  2. Investigation of Wave Energy Converter Effects on Wave Fields: A Modeling Sensitivity Study in Monterey Bay CA.

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, Jesse D.; Grace Chang; Jason Magalen; Craig Jones

    2014-08-01

    A n indust ry standard wave modeling tool was utilized to investigate model sensitivity to input parameters and wave energy converter ( WEC ) array deploym ent scenarios. Wave propagation was investigated d ownstream of the WECs to evaluate overall near - and far - field effects of WEC arrays. The sensitivity study illustrate d that b oth wave height and near - bottom orbital velocity we re subject to the largest pote ntial variations, each decreas ed in sensitivity as transmission coefficient increase d , as number and spacing of WEC devices decrease d , and as the deployment location move d offshore. Wave direction wa s affected consistently for all parameters and wave perio d was not affected (or negligibly affected) by varying model parameters or WEC configuration .

  3. Modelling ESCOMPTE episodes with the CTM MOCAGE. Part 2 : sensitivity studies.

    Science.gov (United States)

    Dufour, A.; Amodei, M.; Brocheton, F.; Michou, M.; Peuch, V.-H.

    2003-04-01

    The multi-scale CTM MOCAGE has been applied to study pollution episodes documented during the ESCOMPTE field campain in June July 2001 in south eastern France (http://medias.obs-mip.fr/escompte). Several sensitivity studies have been performed on the basis of the 2nd IOP, covering 6 continuous days. The main objective of the present work is to investigate the question of chemical boundary conditions, as on the vertical than on the horizontal, for regional air quality simulations of several days. This issue, that often tended to be oversimplified (use of fixed continental climatology), raises increasing interest, particurlarly with the perspective of space-born tropospheric chemisry data assimilation in global model. In addition, we have examined how resolution refinements impact on the quality of the model outputs, at the surface and in altitude, against the observational database of dynamic and chemistry : resolution of the model by the way of the four nested models (from 2° to 0.01°), but also resolution of emission inventories (from 1° to 0.01°). Lastly, the impact of the refinement in the representation of chemistry has been assessed by using either detailed chemical schemes, such as RAM or SAPRC, or schemes used in global modelling, which just account for a limited amount of volatil hydrocarbon.

  4. Model Driven Development of Data Sensitive Systems

    DEFF Research Database (Denmark)

    Olsen, Petur

    2014-01-01

    storage systems, where the actual values of the data is not relevant for the behavior of the system. For many systems the values are important. For instance the control flow of the system can be dependent on the input values. We call this type of system data sensitive, as the execution is sensitive...... to the values of variables. This theses strives to improve model-driven development of such data-sensitive systems. This is done by addressing three research questions. In the first we combine state-based modeling and abstract interpretation, in order to ease modeling of data-sensitive systems, while allowing...... efficient model-checking and model-based testing. In the second we develop automatic abstraction learning used together with model learning, in order to allow fully automatic learning of data-sensitive systems to allow learning of larger systems. In the third we develop an approach for modeling and model-based...

  5. The Sensitivity of Evapotranspiration Models to Errors in Model ...

    African Journals Online (AJOL)

    Five evapotranspiration (Et) model-the penman, Blaney - Criddel, Thornthwaite, the Blaney –Morin-Nigeria, and the Jensen and Haise models – were analyzed for parameter sensitivity under Nigerian Climatic conditions. The sensitivity of each model to errors in any of its measured parameters (variables) was based on the ...

  6. Eocene climate and Arctic paleobathymetry: A tectonic sensitivity study using GISS ModelE-R

    Science.gov (United States)

    Roberts, C. D.; Legrande, A. N.; Tripati, A. K.

    2009-12-01

    The early Paleogene (65-45 million years ago, Ma) was a ‘greenhouse’ interval with global temperatures warmer than any other time in the last 65 Ma. This period was characterized by high levels of CO2, warm high-latitudes, warm surface-and-deep oceans, and an intensified hydrological cycle. Sediments from the Arctic suggest that the Eocene surface Arctic Ocean was warm, brackish, and episodically enabled the freshwater fern Azolla to bloom. The precise mechanisms responsible for the development of these conditions remain uncertain. We present equilibrium climate conditions derived from a fully-coupled, water-isotope enabled, general circulation model (GISS ModelE-R) configured for the early Eocene. We also present model-data comparison plots for key climatic variables (SST and δ18O) and analyses of the leading modes of variability in the tropical Pacific and North Atlantic regions. Our tectonic sensitivity study indicates that Northern Hemisphere climate would have been very sensitive to the degree of oceanic exchange through the seaways connecting the Arctic to the Atlantic and Tethys. By restricting these seaways, we simulate freshening of the surface Arctic Ocean to ~6 psu and warming of sea-surface temperatures by 2°C in the North Atlantic and 5-10°C in the Labrador Sea. Our results may help explain the occurrence of low-salinity tolerant taxa in the Arctic Ocean during the Eocene and provide a mechanism for enhanced warmth in the north western Atlantic. We also suggest that the formation of a volcanic land-bridge between Greenland and Europe could have caused increased ocean convection and warming of intermediate waters in the Atlantic. If true, this result is consistent with the theory that bathymetry changes may have caused thermal destabilisation of methane clathrates in the Atlantic.

  7. Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation

    Directory of Open Access Journals (Sweden)

    Y. Tang

    2007-01-01

    Full Text Available This study seeks to identify sensitivity tools that will advance our understanding of lumped hydrologic models for the purposes of model improvement, calibration efficiency and improved measurement schemes. Four sensitivity analysis methods were tested: (1 local analysis using parameter estimation software (PEST, (2 regional sensitivity analysis (RSA, (3 analysis of variance (ANOVA, and (4 Sobol's method. The methods' relative efficiencies and effectiveness have been analyzed and compared. These four sensitivity methods were applied to the lumped Sacramento soil moisture accounting model (SAC-SMA coupled with SNOW-17. Results from this study characterize model sensitivities for two medium sized watersheds within the Juniata River Basin in Pennsylvania, USA. Comparative results for the 4 sensitivity methods are presented for a 3-year time series with 1 h, 6 h, and 24 h time intervals. The results of this study show that model parameter sensitivities are heavily impacted by the choice of analysis method as well as the model time interval. Differences between the two adjacent watersheds also suggest strong influences of local physical characteristics on the sensitivity methods' results. This study also contributes a comprehensive assessment of the repeatability, robustness, efficiency, and ease-of-implementation of the four sensitivity methods. Overall ANOVA and Sobol's method were shown to be superior to RSA and PEST. Relative to one another, ANOVA has reduced computational requirements and Sobol's method yielded more robust sensitivity rankings.

  8. An Equation-of-State Compositional In-Situ Combustion Model: A Study of Phase Behavior Sensitivity

    DEFF Research Database (Denmark)

    Kristensen, Morten Rode; Gerritsen, M. G.; Thomsen, Per Grove

    2009-01-01

    phase behavior sensitivity for in situ combustion, a thermal oil recovery process. For the one-dimensional model we first study the sensitivity to numerical discretization errors and provide grid density guidelines for proper resolution of in situ combustion behavior. A critical condition for success...... to ignition. For a particular oil we show that the simplified approach overestimates the required air injection rate for sustained front propagation by 17% compared to the equation of state-based approach....

  9. Healthy volunteers can be phenotyped using cutaneous sensitization pain models.

    Directory of Open Access Journals (Sweden)

    Mads U Werner

    Full Text Available BACKGROUND: Human experimental pain models leading to development of secondary hyperalgesia are used to estimate efficacy of analgesics and antihyperalgesics. The ability to develop an area of secondary hyperalgesia varies substantially between subjects, but little is known about the agreement following repeated measurements. The aim of this study was to determine if the areas of secondary hyperalgesia were consistently robust to be useful for phenotyping subjects, based on their pattern of sensitization by the heat pain models. METHODS: We performed post-hoc analyses of 10 completed healthy volunteer studies (n = 342 [409 repeated measurements]. Three different models were used to induce secondary hyperalgesia to monofilament stimulation: the heat/capsaicin sensitization (H/C, the brief thermal sensitization (BTS, and the burn injury (BI models. Three studies included both the H/C and BTS models. RESULTS: Within-subject compared to between-subject variability was low, and there was substantial strength of agreement between repeated induction-sessions in most studies. The intraclass correlation coefficient (ICC improved little with repeated testing beyond two sessions. There was good agreement in categorizing subjects into 'small area' (1(st quartile [75%] responders: 56-76% of subjects consistently fell into same 'small-area' or 'large-area' category on two consecutive study days. There was moderate to substantial agreement between the areas of secondary hyperalgesia induced on the same day using the H/C (forearm and BTS (thigh models. CONCLUSION: Secondary hyperalgesia induced by experimental heat pain models seem a consistent measure of sensitization in pharmacodynamic and physiological research. The analysis indicates that healthy volunteers can be phenotyped based on their pattern of sensitization by the heat [and heat plus capsaicin] pain models.

  10. Remote sensing of mineral dust aerosol using AERI during the UAE2: A modeling and sensitivity study

    Science.gov (United States)

    Hansell, R. A.; Liou, K. N.; Ou, S. C.; Tsay, S. C.; Ji, Q.; Reid, J. S.

    2008-09-01

    Numerical simulations and sensitivity studies have been performed to assess the potential for using brightness temperature spectra from a ground-based Atmospheric Emitted Radiance Interferometer (AERI) during the United Arab Emirates Unified Aerosol Experiment (UAE2) for detecting/retrieving mineral dust aerosol. A methodology for separating dust from clouds and retrieving the dust IR optical depths was developed by exploiting differences between their spectral absorptive powers in prescribed thermal IR window subbands. Dust microphysical models were constructed using in situ data from the UAE2 and prior field studies while composition was modeled using refractive index data sets for minerals commonly observed around the UAE region including quartz, kaolinite, and calcium carbonate. The T-matrix, finite difference time domain (FDTD), and Lorenz-Mie light scattering programs were employed to calculate the single scattering properties for three dust shapes: oblate spheroids, hexagonal plates, and spheres. We used the Code for High-resolution Accelerated Radiative Transfer with Scattering (CHARTS) radiative transfer program to investigate sensitivity of the modeled AERI spectra to key dust and atmospheric parameters. Sensitivity studies show that characterization of the thermodynamic boundary layer is crucial for accurate AERI dust detection/retrieval. Furthermore, AERI sensitivity to dust optical depth is manifested in the strong subband slope dependence of the window region. Two daytime UAE2 cases were examined to demonstrate the present detection/retrieval technique, and we show that the results compare reasonably well to collocated AERONET Sun photometer/MPLNET micropulse lidar measurements. Finally, sensitivity of the developed methodology to the AERI's estimated MgCdTe detector nonlinearity was evaluated.

  11. Sensitivity Studies on Revised PSA Model of KHNP Nuclear Power Plants

    International Nuclear Information System (INIS)

    Lee, Hyun-Gyo; Hwang, Seok-Won; Shin, Tae-Young

    2016-01-01

    Korea also performed safety revaluation for all nuclear power plants led by Korean regulatory and elicited 49 improvement factor for plants. One of those factors is Severe Accident Management Guidelines (SAMG) development, KHNP decided to develop Low Power and Shutdown(LPSD) Probabilistic Safety Assessment (PSA) models and upgrade full power PSA models of all operating plants for enhancement of guideline quality. In this paper we discuss about the effectiveness of post Fukushima equipment and improvements of each plant based on the results of revised full power PSA and newly developed LPSD PSA. Through sensitivity analysis based on revised PSA models we confirmed that the facilities installed or planned to installation as follow-up measures of Fukushima accident helped to enhance the safety of nuclear power plants. These results will provide various technical insights to scheduled studies which evaluate effectiveness of Fukushima post action items and develop accident management guideline. Also it will contribute to improve nuclear power plants safety

  12. Sensitivity Studies on Revised PSA Model of KHNP Nuclear Power Plants

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Hyun-Gyo; Hwang, Seok-Won; Shin, Tae-Young [KHNP, Daejeon (Korea, Republic of)

    2016-10-15

    Korea also performed safety revaluation for all nuclear power plants led by Korean regulatory and elicited 49 improvement factor for plants. One of those factors is Severe Accident Management Guidelines (SAMG) development, KHNP decided to develop Low Power and Shutdown(LPSD) Probabilistic Safety Assessment (PSA) models and upgrade full power PSA models of all operating plants for enhancement of guideline quality. In this paper we discuss about the effectiveness of post Fukushima equipment and improvements of each plant based on the results of revised full power PSA and newly developed LPSD PSA. Through sensitivity analysis based on revised PSA models we confirmed that the facilities installed or planned to installation as follow-up measures of Fukushima accident helped to enhance the safety of nuclear power plants. These results will provide various technical insights to scheduled studies which evaluate effectiveness of Fukushima post action items and develop accident management guideline. Also it will contribute to improve nuclear power plants safety.

  13. Sensitivity Analysis of Launch Vehicle Debris Risk Model

    Science.gov (United States)

    Gee, Ken; Lawrence, Scott L.

    2010-01-01

    As part of an analysis of the loss of crew risk associated with an ascent abort system for a manned launch vehicle, a model was developed to predict the impact risk of the debris resulting from an explosion of the launch vehicle on the crew module. The model consisted of a debris catalog describing the number, size and imparted velocity of each piece of debris, a method to compute the trajectories of the debris and a method to calculate the impact risk given the abort trajectory of the crew module. The model provided a point estimate of the strike probability as a function of the debris catalog, the time of abort and the delay time between the abort and destruction of the launch vehicle. A study was conducted to determine the sensitivity of the strike probability to the various model input parameters and to develop a response surface model for use in the sensitivity analysis of the overall ascent abort risk model. The results of the sensitivity analysis and the response surface model are presented in this paper.

  14. Sensitivity of a complex urban air quality model to input data

    International Nuclear Information System (INIS)

    Seigneur, C.; Tesche, T.W.; Roth, P.M.; Reid, L.E.

    1981-01-01

    In recent years, urban-scale photochemical simulation models have been developed that are of practical value for predicting air quality and analyzing the impacts of alternative emission control strategies. Although the performance of some urban-scale models appears to be acceptable, the demanding data requirements of such models have prompted concern about the costs of data acquistion, which might be high enough to preclude use of photochemical models for many urban areas. To explore this issue, sensitivity studies with the Systems Applications, Inc. (SAI) Airshed Model, a grid-based time-dependent photochemical dispersion model, have been carried out for the Los Angeles basin. Reductions in the amount and quality of meteorological, air quality and emission data, as well as modifications of the model gridded structure, have been analyzed. This paper presents and interprets the results of 22 sensitivity studies. A sensitivity-uncertainty index is defined to rank input data needs for an urban photochemical model. The index takes into account the sensitivity of model predictions to the amount of input data, the costs of data acquistion, and the uncertainties in the air quality model input variables. The results of these sensitivity studies are considered in light of the limitations of specific attributes of the Los Angeles basin and of the modeling conditions (e.g., choice of wind model, length of simulation time). The extent to which the results may be applied to other urban areas also is discussed

  15. Sensitivity Analysis of b-factor in Microwave Emission Model for Soil Moisture Retrieval: A Case Study for SMAP Mission

    Directory of Open Access Journals (Sweden)

    Dugwon Seo

    2010-05-01

    Full Text Available Sensitivity analysis is critically needed to better understand the microwave emission model for soil moisture retrieval using passive microwave remote sensing data. The vegetation b-factor along with vegetation water content and surface characteristics has significant impact in model prediction. This study evaluates the sensitivity of the b-factor, which is function of vegetation type. The analysis is carried out using Passive and Active L and S-band airborne sensor (PALS and measured field soil moisture from Southern Great Plains experiment (SGP99. The results show that the relative sensitivity of the b-factor is 86% in wet soil condition and 88% in high vegetated condition compared to the sensitivity of the soil moisture. Apparently, the b-factor is found to be more sensitive than the vegetation water content, surface roughness and surface temperature; therefore, the effect of the b-factor is fairly large to the microwave emission in certain conditions. Understanding the dependence of the b-factor on the soil and vegetation is important in studying the soil moisture retrieval algorithm, which can lead to potential improvements in model development for the Soil Moisture Active-Passive (SMAP mission.

  16. Sensitivity of fluvial sediment source apportionment to mixing model assumptions: A Bayesian model comparison.

    Science.gov (United States)

    Cooper, Richard J; Krueger, Tobias; Hiscock, Kevin M; Rawlins, Barry G

    2014-11-01

    Mixing models have become increasingly common tools for apportioning fluvial sediment load to various sediment sources across catchments using a wide variety of Bayesian and frequentist modeling approaches. In this study, we demonstrate how different model setups can impact upon resulting source apportionment estimates in a Bayesian framework via a one-factor-at-a-time (OFAT) sensitivity analysis. We formulate 13 versions of a mixing model, each with different error assumptions and model structural choices, and apply them to sediment geochemistry data from the River Blackwater, Norfolk, UK, to apportion suspended particulate matter (SPM) contributions from three sources (arable topsoils, road verges, and subsurface material) under base flow conditions between August 2012 and August 2013. Whilst all 13 models estimate subsurface sources to be the largest contributor of SPM (median ∼76%), comparison of apportionment estimates reveal varying degrees of sensitivity to changing priors, inclusion of covariance terms, incorporation of time-variant distributions, and methods of proportion characterization. We also demonstrate differences in apportionment results between a full and an empirical Bayesian setup, and between a Bayesian and a frequentist optimization approach. This OFAT sensitivity analysis reveals that mixing model structural choices and error assumptions can significantly impact upon sediment source apportionment results, with estimated median contributions in this study varying by up to 21% between model versions. Users of mixing models are therefore strongly advised to carefully consider and justify their choice of model structure prior to conducting sediment source apportionment investigations. An OFAT sensitivity analysis of sediment fingerprinting mixing models is conductedBayesian models display high sensitivity to error assumptions and structural choicesSource apportionment results differ between Bayesian and frequentist approaches.

  17. Variability of indicator values for ozone production sensitivity: a model study in Switzerland and San Joaquin Valley (California)

    International Nuclear Information System (INIS)

    Andreani-Aksoyoglu, S.; Keller, J.; Prevot, A.S.H.; Chenghsuan Lu; Chang, J.S.

    2001-01-01

    The threshold values of indicator species and ratios delineating the transition between NO x and VOC sensitivity of ozone formation are assumed to be universal by various investigators. However, our previous studies suggested that threshold values might vary according to the locations and conditions. In this study, threshold values derived from various model simulations at two different locations (the area of Switzerland by UAM Model and San Joaquin Valley of Central California by SAQM Model) are examined using a new approach for defining NO x and VOC sensitive regimes. Possible definitions for the distinction of NO x and VOC sensitive ozone production regimes are given. The dependence of the threshold values for indicators and indicator ratios such as NO y , O 3 /NO z , HCHO/NO y , and H 2 O 2 /HNO 3 on the definition of NO x and VOC sensitivity is discussed. Then the variations of threshold values under low emission conditions and in two different days are examined in both areas to check whether the models respond consistently to changes in environmental conditions. In both cases, threshold values are shifted similarly when emissions are reduced. Changes in the wind fields and aging of the photochemical oxidants seem to cause the day-to-day variation of the threshold values. O 3 /NO z and HCHO/NO y indicators are predicted to be unsatisfactory to separate the NO x and VOC sensitive regimes. Although NO y and H 2 O 2 /HNO 3 provide a good separation of the two regimes, threshold values are affected by changes in the environmental conditions studied in this work. (author)

  18. Sensitivity analysis of the boundary layer height on idealised cities (model study)

    Energy Technology Data Exchange (ETDEWEB)

    Schayes, G. [Univ. of Louvain, Louvain-la-Neuve (Belgium); Grossi, P. [Joint Research Center, Ispra (Italy)

    1997-10-01

    The behaviour of the typical diurnal variation of the atmospheric boundary layer (ABL) over cities is a complex function of very numerous environmental parameters. Two types of geographical situations have been retained: (i) inland city only surrounded by uniform fields, (ii) coastal city, thus influenced by the sea/land breeze effect. We have used the three-dimensional Thermal Vorticity-mode Mesoscale (TVM) model developed jointly by the UCL (Belgium) and JRC (Italy). In this study it has been used in 2-D mode allowing to perform many sensitivity runs. This implies that a kind of infinitely wide city has been effectively stimulated, but this does not affect the conclusions for the ABL height. The sensibility study has been performed for two turbulence closure schemes, for various assumptions for the ABL height definition in the model, and for a selected parameter, the soil water content. (LN)

  19. A sensitivity analysis of regional and small watershed hydrologic models

    Science.gov (United States)

    Ambaruch, R.; Salomonson, V. V.; Simmons, J. W.

    1975-01-01

    Continuous simulation models of the hydrologic behavior of watersheds are important tools in several practical applications such as hydroelectric power planning, navigation, and flood control. Several recent studies have addressed the feasibility of using remote earth observations as sources of input data for hydrologic models. The objective of the study reported here was to determine how accurately remotely sensed measurements must be to provide inputs to hydrologic models of watersheds, within the tolerances needed for acceptably accurate synthesis of streamflow by the models. The study objective was achieved by performing a series of sensitivity analyses using continuous simulation models of three watersheds. The sensitivity analysis showed quantitatively how variations in each of 46 model inputs and parameters affect simulation accuracy with respect to five different performance indices.

  20. A Culture-Sensitive Agent in Kirman's Ant Model

    Science.gov (United States)

    Chen, Shu-Heng; Liou, Wen-Ching; Chen, Ting-Yu

    The global financial crisis brought a serious collapse involving a "systemic" meltdown. Internet technology and globalization have increased the chances for interaction between countries and people. The global economy has become more complex than ever before. Mark Buchanan [12] indicated that agent-based computer models will prevent another financial crisis and has been particularly influential in contributing insights. There are two reasons why culture-sensitive agent on the financial market has become so important. Therefore, the aim of this article is to establish a culture-sensitive agent and forecast the process of change regarding herding behavior in the financial market. We based our study on the Kirman's Ant Model[4,5] and Hofstede's Natational Culture[11] to establish our culture-sensitive agent based model. Kirman's Ant Model is quite famous and describes financial market herding behavior from the expectations of the future of financial investors. Hofstede's cultural consequence used the staff of IBM in 72 different countries to understand the cultural difference. As a result, this paper focuses on one of the five dimensions of culture from Hofstede: individualism versus collectivism and creates a culture-sensitive agent and predicts the process of change regarding herding behavior in the financial market. To conclude, this study will be of importance in explaining the herding behavior with cultural factors, as well as in providing researchers with a clearer understanding of how herding beliefs of people about different cultures relate to their finance market strategies.

  1. Validity of Quinpirole Sensitization Rat Model of OCD: Linking Evidence from Animal and Clinical Studies.

    Science.gov (United States)

    Stuchlik, Ales; Radostová, Dominika; Hatalova, Hana; Vales, Karel; Nekovarova, Tereza; Koprivova, Jana; Svoboda, Jan; Horacek, Jiri

    2016-01-01

    Obsessive-compulsive disorder (OCD) is a neuropsychiatric disorder with 1-3% prevalence. OCD is characterized by recurrent thoughts (obsessions) and repetitive behaviors (compulsions). The pathophysiology of OCD remains unclear, stressing the importance of pre-clinical studies. The aim of this article is to critically review a proposed animal model of OCD that is characterized by the induction of compulsive checking and behavioral sensitization to the D2/D3 dopamine agonist quinpirole. Changes in this model have been reported at the level of brain structures, neurotransmitter systems and other neurophysiological aspects. In this review, we consider these alterations in relation to the clinical manifestations in OCD, with the aim to discuss and evaluate axes of validity of this model. Our analysis shows that some axes of validity of quinpirole sensitization model (QSM) are strongly supported by clinical findings, such as behavioral phenomenology or roles of brain structures. Evidence on predictive validity is contradictory and ambiguous. It is concluded that this model is useful in the context of searching for the underlying pathophysiological basis of the disorder because of the relatively strong biological similarities with OCD.

  2. Sensitivity and uncertainty studies of the CRAC2 computer code

    International Nuclear Information System (INIS)

    Kocher, D.C.; Ward, R.C.; Killough, G.G.; Dunning, D.E. Jr.; Hicks, B.B.; Hosker, R.P. Jr.; Ku, J.Y.; Rao, K.S.

    1985-05-01

    This report presents a study of the sensitivity of early fatalities, early injuries, latent cancer fatalities, and economic costs for hypothetical nuclear reactor accidents as predicted by the CRAC2 computer code (CRAC = Calculation of Reactor Accident Consequences) to uncertainties in selected models and parameters used in the code. The sources of uncertainty that were investigated in the CRAC2 sensitivity studies include (1) the model for plume rise, (2) the model for wet deposition, (3) the procedure for meteorological bin-sampling involving the selection of weather sequences that contain rain, (4) the dose conversion factors for inhalation as they are affected by uncertainties in the physical and chemical form of the released radionuclides, (5) the weathering half-time for external ground-surface exposure, and (6) the transfer coefficients for estimating exposures via terrestrial foodchain pathways. The sensitivity studies were performed for selected radionuclide releases, hourly meteorological data, land-use data, a fixed non-uniform population distribution, a single evacuation model, and various release heights and sensible heat rates. Two important general conclusions from the sensitivity and uncertainty studies are as follows: (1) The large effects on predicted early fatalities and early injuries that were observed in some of the sensitivity studies apparently are due in part to the presence of thresholds in the dose-response models. Thus, the observed sensitivities depend in part on the magnitude of the radionuclide releases. (2) Some of the effects on predicted early fatalities and early injuries that were observed in the sensitivity studies were comparable to effects that were due only to the selection of different sets of weather sequences in bin-sampling runs. 47 figs., 50 tabs

  3. Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation

    Science.gov (United States)

    Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten

    2015-04-01

    Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.

  4. Sensitivity study of the Continuous Release Dispersion Model (CRDM) for radioactive pollutants

    International Nuclear Information System (INIS)

    Camacho, F.

    1987-08-01

    The Continuous Release Dispersion Model (CRDM) is used to calculate spatial distribution of pollutants and their radiation doses in the event of accidental releases of radioactive material from Nuclear Generation Stations. A sensitivity analysis of the CRDM was carried out to develop a method for quantifying the expected output uncertainty due to inaccuracies and uncertainties in the input values. A simulation approach was used to explore the behaviour of the sensitivity functions. It was found that the most sensitive variable is wind speed, the least sensitive is the ambient temperature, and that largest values of normalized concentrations are likely to occur for small values of wind speed and highly stable atmospheric conditions. It was also shown that an error between 10% and 25% should be expected in the output values for a 1% overall error in the input values, and this factor could be much larger in certain situations

  5. Global sensitivity analysis of DRAINMOD-FOREST, an integrated forest ecosystem model

    Science.gov (United States)

    Shiying Tian; Mohamed A. Youssef; Devendra M. Amatya; Eric D. Vance

    2014-01-01

    Global sensitivity analysis is a useful tool to understand process-based ecosystem models by identifying key parameters and processes controlling model predictions. This study reported a comprehensive global sensitivity analysis for DRAINMOD-FOREST, an integrated model for simulating water, carbon (C), and nitrogen (N) cycles and plant growth in lowland forests. The...

  6. ADGEN: a system for automated sensitivity analysis of predictive models

    International Nuclear Information System (INIS)

    Pin, F.G.; Horwedel, J.E.; Oblow, E.M.; Lucius, J.L.

    1986-09-01

    A system that can automatically enhance computer codes with a sensitivity calculation capability is presented. With this new system, named ADGEN, rapid and cost-effective calculation of sensitivities can be performed in any FORTRAN code for all input data or parameters. The resulting sensitivities can be used in performance assessment studies related to licensing or interactions with the public to systematically and quantitatively prove the relative importance of each of the system parameters in calculating the final performance results. A general procedure calling for the systematic use of sensitivities in assessment studies is presented. The procedure can be used in modelling and model validation studies to avoid ''over modelling,'' in site characterization planning to avoid ''over collection of data,'' and in performance assessment to determine the uncertainties on the final calculated results. The added capability to formally perform the inverse problem, i.e., to determine the input data or parameters on which to focus additional research or analysis effort in order to improve the uncertainty of the final results, is also discussed

  7. Is Convection Sensitive to Model Vertical Resolution and Why?

    Science.gov (United States)

    Xie, S.; Lin, W.; Zhang, G. J.

    2017-12-01

    Model sensitivity to horizontal resolutions has been studied extensively, whereas model sensitivity to vertical resolution is much less explored. In this study, we use the US Department of Energy (DOE)'s Accelerated Climate Modeling for Energy (ACME) atmosphere model to examine the sensitivity of clouds and precipitation to the increase of vertical resolution of the model. We attempt to understand what results in the behavior change (if any) of convective processes represented by the unified shallow and turbulent scheme named CLUBB (Cloud Layers Unified by Binormals) and the Zhang-McFarlane deep convection scheme in ACME. A short-term hindcast approach is used to isolate parameterization issues from the large-scale circulation. The analysis emphasizes on how the change of vertical resolution could affect precipitation partitioning between convective- and grid-scale as well as the vertical profiles of convection-related quantities such as temperature, humidity, clouds, convective heating and drying, and entrainment and detrainment. The goal is to provide physical insight into potential issues with model convective processes associated with the increase of model vertical resolution. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

  8. Bayesian Sensitivity Analysis of Statistical Models with Missing Data.

    Science.gov (United States)

    Zhu, Hongtu; Ibrahim, Joseph G; Tang, Niansheng

    2014-04-01

    Methods for handling missing data depend strongly on the mechanism that generated the missing values, such as missing completely at random (MCAR) or missing at random (MAR), as well as other distributional and modeling assumptions at various stages. It is well known that the resulting estimates and tests may be sensitive to these assumptions as well as to outlying observations. In this paper, we introduce various perturbations to modeling assumptions and individual observations, and then develop a formal sensitivity analysis to assess these perturbations in the Bayesian analysis of statistical models with missing data. We develop a geometric framework, called the Bayesian perturbation manifold, to characterize the intrinsic structure of these perturbations. We propose several intrinsic influence measures to perform sensitivity analysis and quantify the effect of various perturbations to statistical models. We use the proposed sensitivity analysis procedure to systematically investigate the tenability of the non-ignorable missing at random (NMAR) assumption. Simulation studies are conducted to evaluate our methods, and a dataset is analyzed to illustrate the use of our diagnostic measures.

  9. Sensitivity and uncertainty analyses for performance assessment modeling

    International Nuclear Information System (INIS)

    Doctor, P.G.

    1988-08-01

    Sensitivity and uncertainty analyses methods for computer models are being applied in performance assessment modeling in the geologic high level radioactive waste repository program. The models used in performance assessment tend to be complex physical/chemical models with large numbers of input variables. There are two basic approaches to sensitivity and uncertainty analyses: deterministic and statistical. The deterministic approach to sensitivity analysis involves numerical calculation or employs the adjoint form of a partial differential equation to compute partial derivatives; the uncertainty analysis is based on Taylor series expansions of the input variables propagated through the model to compute means and variances of the output variable. The statistical approach to sensitivity analysis involves a response surface approximation to the model with the sensitivity coefficients calculated from the response surface parameters; the uncertainty analysis is based on simulation. The methods each have strengths and weaknesses. 44 refs

  10. Parameter sensitivity study of a Field II multilayer transducer model on a convex transducer

    DEFF Research Database (Denmark)

    Bæk, David; Jensen, Jørgen Arendt; Willatzen, Morten

    2009-01-01

    A multilayer transducer model for predicting a transducer impulse response has in earlier works been developed and combined with the Field II software. This development was tested on current, voltage, and intensity measurements on piezoceramics discs (Bæk et al. IUS 2008) and a convex 128 element...... ultrasound imaging transducer (Bæk et al. ICU 2009). The model benefits from its 1D simplicity and hasshown to give an amplitude error around 1.7‐2 dB. However, any prediction of amplitude, phase, and attenuation of pulses relies on the accuracy of manufacturer supplied material characteristics, which may...... is a quantitative calibrated model for a complete ultrasound system. This includes a sensitivity study aspresented here.Statement of Contribution/MethodsThe study alters 35 different model parameters which describe a 128 element convex transducer from BK Medical Aps. The changes are within ±20 % of the values...

  11. Sensitivity analysis of machine-learning models of hydrologic time series

    Science.gov (United States)

    O'Reilly, A. M.

    2017-12-01

    Sensitivity analysis traditionally has been applied to assessing model response to perturbations in model parameters, where the parameters are those model input variables adjusted during calibration. Unlike physics-based models where parameters represent real phenomena, the equivalent of parameters for machine-learning models are simply mathematical "knobs" that are automatically adjusted during training/testing/verification procedures. Thus the challenge of extracting knowledge of hydrologic system functionality from machine-learning models lies in their very nature, leading to the label "black box." Sensitivity analysis of the forcing-response behavior of machine-learning models, however, can provide understanding of how the physical phenomena represented by model inputs affect the physical phenomena represented by model outputs.As part of a previous study, hybrid spectral-decomposition artificial neural network (ANN) models were developed to simulate the observed behavior of hydrologic response contained in multidecadal datasets of lake water level, groundwater level, and spring flow. Model inputs used moving window averages (MWA) to represent various frequencies and frequency-band components of time series of rainfall and groundwater use. Using these forcing time series, the MWA-ANN models were trained to predict time series of lake water level, groundwater level, and spring flow at 51 sites in central Florida, USA. A time series of sensitivities for each MWA-ANN model was produced by perturbing forcing time-series and computing the change in response time-series per unit change in perturbation. Variations in forcing-response sensitivities are evident between types (lake, groundwater level, or spring), spatially (among sites of the same type), and temporally. Two generally common characteristics among sites are more uniform sensitivities to rainfall over time and notable increases in sensitivities to groundwater usage during significant drought periods.

  12. Repository design sensitivity study: Engineering study report

    International Nuclear Information System (INIS)

    1987-01-01

    A preliminary sensitivity study of the salt repository design has been performed to identify critical site and design parameters to help guide future site characterization and design optimization activities. The study considered the SCP-conceptual design at the Deaf Smith County site in Texas with the horizontal waste package emplacement mode as the base case. Relative to this base case, parameter variations were compared. Limited studies were performed which considered the vertical emplacement mode geometry. The report presents the reference data base and design parameters on which the study was based (including the range of parameters that might be expected). Detailed descriptions of the numerical modeling methods and assumptions are included for the thermal, thermomechanical and hydrogeological analyses. The impacts of parameter variations on the sensitivity of the rock mass response are discussed. Recommendations are provided to help guide site characterization activities and advanced conceptual design optimization activities. 47 refs., 119 refs., 22 tabs

  13. Variance-based sensitivity indices for models with dependent inputs

    International Nuclear Information System (INIS)

    Mara, Thierry A.; Tarantola, Stefano

    2012-01-01

    Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.

  14. Sensitivity Analysis of Simulation Models

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2009-01-01

    This contribution presents an overview of sensitivity analysis of simulation models, including the estimation of gradients. It covers classic designs and their corresponding (meta)models; namely, resolution-III designs including fractional-factorial two-level designs for first-order polynomial

  15. ADGEN: a system for automated sensitivity analysis of predictive models

    International Nuclear Information System (INIS)

    Pin, F.G.; Horwedel, J.E.; Oblow, E.M.; Lucius, J.L.

    1987-01-01

    A system that can automatically enhance computer codes with a sensitivity calculation capability is presented. With this new system, named ADGEN, rapid and cost-effective calculation of sensitivities can be performed in any FORTRAN code for all input data or parameters. The resulting sensitivities can be used in performance assessment studies related to licensing or interactions with the public to systematically and quantitatively prove the relative importance of each of the system parameters in calculating the final performance results. A general procedure calling for the systematic use of sensitivities in assessment studies is presented. The procedure can be used in modeling and model validation studies to avoid over modeling, in site characterization planning to avoid over collection of data, and in performance assessments to determine the uncertainties on the final calculated results. The added capability to formally perform the inverse problem, i.e., to determine the input data or parameters on which to focus to determine the input data or parameters on which to focus additional research or analysis effort in order to improve the uncertainty of the final results, is also discussed. 7 references, 2 figures

  16. Reproducibility of the heat/capsaicin skin sensitization model in healthy volunteers

    Directory of Open Access Journals (Sweden)

    Cavallone LF

    2013-11-01

    Full Text Available Laura F Cavallone,1 Karen Frey,1 Michael C Montana,1 Jeremy Joyal,1 Karen J Regina,1 Karin L Petersen,2 Robert W Gereau IV11Department of Anesthesiology, Washington University in St Louis, School of Medicine, St Louis, MO, USA; 2California Pacific Medical Center Research Institute, San Francisco, CA, USAIntroduction: Heat/capsaicin skin sensitization is a well-characterized human experimental model to induce hyperalgesia and allodynia. Using this model, gabapentin, among other drugs, was shown to significantly reduce cutaneous hyperalgesia compared to placebo. Since the larger thermal probes used in the original studies to produce heat sensitization are now commercially unavailable, we decided to assess whether previous findings could be replicated with a currently available smaller probe (heated area 9 cm2 versus 12.5–15.7 cm2.Study design and methods: After Institutional Review Board approval, 15 adult healthy volunteers participated in two study sessions, scheduled 1 week apart (Part A. In both sessions, subjects were exposed to the heat/capsaicin cutaneous sensitization model. Areas of hypersensitivity to brush stroke and von Frey (VF filament stimulation were measured at baseline and after rekindling of skin sensitization. Another group of 15 volunteers was exposed to an identical schedule and set of sensitization procedures, but, in each session, received either gabapentin or placebo (Part B.Results: Unlike previous reports, a similar reduction of areas of hyperalgesia was observed in all groups/sessions. Fading of areas of hyperalgesia over time was observed in Part A. In Part B, there was no difference in area reduction after gabapentin compared to placebo.Conclusion: When using smaller thermal probes than originally proposed, modifications of other parameters of sensitization and/or rekindling process may be needed to allow the heat/capsaicin sensitization protocol to be used as initially intended. Standardization and validation of

  17. Global sensitivity analysis of computer models with functional inputs

    International Nuclear Information System (INIS)

    Iooss, Bertrand; Ribatet, Mathieu

    2009-01-01

    Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.

  18. Supplementary Material for: A global sensitivity analysis approach for morphogenesis models

    KAUST Repository

    Boas, Sonja

    2015-01-01

    Abstract Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

  19. Sensitivity Analysis of the Integrated Medical Model for ISS Programs

    Science.gov (United States)

    Goodenow, D. A.; Myers, J. G.; Arellano, J.; Boley, L.; Garcia, Y.; Saile, L.; Walton, M.; Kerstman, E.; Reyes, D.; Young, M.

    2016-01-01

    Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral

  20. Sensitivities and uncertainties of modeled ground temperatures in mountain environments

    Directory of Open Access Journals (Sweden)

    S. Gubler

    2013-08-01

    Full Text Available Model evaluation is often performed at few locations due to the lack of spatially distributed data. Since the quantification of model sensitivities and uncertainties can be performed independently from ground truth measurements, these analyses are suitable to test the influence of environmental variability on model evaluation. In this study, the sensitivities and uncertainties of a physically based mountain permafrost model are quantified within an artificial topography. The setting consists of different elevations and exposures combined with six ground types characterized by porosity and hydraulic properties. The analyses are performed for a combination of all factors, that allows for quantification of the variability of model sensitivities and uncertainties within a whole modeling domain. We found that model sensitivities and uncertainties vary strongly depending on different input factors such as topography or different soil types. The analysis shows that model evaluation performed at single locations may not be representative for the whole modeling domain. For example, the sensitivity of modeled mean annual ground temperature to ground albedo ranges between 0.5 and 4 °C depending on elevation, aspect and the ground type. South-exposed inclined locations are more sensitive to changes in ground albedo than north-exposed slopes since they receive more solar radiation. The sensitivity to ground albedo increases with decreasing elevation due to shorter duration of the snow cover. The sensitivity in the hydraulic properties changes considerably for different ground types: rock or clay, for instance, are not sensitive to uncertainties in the hydraulic properties, while for gravel or peat, accurate estimates of the hydraulic properties significantly improve modeled ground temperatures. The discretization of ground, snow and time have an impact on modeled mean annual ground temperature (MAGT that cannot be neglected (more than 1 °C for several

  1. Exploring Intercultural Sensitivity in Early Adolescence: A Mixed Methods Study

    Science.gov (United States)

    Mellizo, Jennifer M.

    2017-01-01

    The purpose of this mixed methods study was to explore levels of intercultural sensitivity in a sample of fourth to eighth grade students in the United States (n = 162). "Intercultural sensitivity" was conceptualised through Bennett's Developmental Model of Sensitivity, and assessed through the Adapted Intercultural Sensitivity Index.…

  2. Sensitivity studies using the TRNSM 2 computerized model for the NRC physical protection project. Final report

    International Nuclear Information System (INIS)

    Anderson, G.M.

    1979-08-01

    A computerized model of the transportation system for shipment of nuclear fuel cycle materials is required to investigate the effects on fleet size, fleet composition and efficiency of fleet utilization resulting from changes in a variety of physical and regulatory factors, including shipping requirements, security regulations, work rules, maintenance requirements, and vehicle capacities. Such a model has been developed which provides a capability for complete sizing requirements studies of a combined aircraft and truck fleet. This report presents the results of a series of sensitivity studies performed using this model. These studies include the effects of the intinerary optimization criteria, work rules, and maintenance policies. These results demonstrate the effectiveness and versatility of the model for investigating the effects of a wide variety of physical and regulatory factors on the transportation fleet

  3. Modelling sensitivity and uncertainty in a LCA model for waste management systems - EASETECH

    DEFF Research Database (Denmark)

    Damgaard, Anders; Clavreul, Julie; Baumeister, Hubert

    2013-01-01

    In the new model, EASETECH, developed for LCA modelling of waste management systems, a general approach for sensitivity and uncertainty assessment for waste management studies has been implemented. First general contribution analysis is done through a regular interpretation of inventory and impact...

  4. Personalization of models with many model parameters: an efficient sensitivity analysis approach.

    Science.gov (United States)

    Donders, W P; Huberts, W; van de Vosse, F N; Delhaas, T

    2015-10-01

    Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific applications of models that enhance diagnosis or aid decision-making. Variance-based sensitivity analysis methods, which apportion each fraction of the output uncertainty (variance) to the effects of individual input parameters or their interactions, are considered the gold standard. The variance portions are called the Sobol sensitivity indices and can be estimated by a Monte Carlo (MC) approach (e.g., Saltelli's method [1]) or by employing a metamodel (e.g., the (generalized) polynomial chaos expansion (gPCE) [2, 3]). All these methods require a large number of model evaluations when estimating the Sobol sensitivity indices for models with many parameters [4]. To reduce the computational cost, we introduce a two-step approach. In the first step, a subset of important parameters is identified for each output of interest using the screening method of Morris [5]. In the second step, a quantitative variance-based sensitivity analysis is performed using gPCE. Efficient sampling strategies are introduced to minimize the number of model runs required to obtain the sensitivity indices for models considering multiple outputs. The approach is tested using a model that was developed for predicting post-operative flows after creation of a vascular access for renal failure patients. We compare the sensitivity indices obtained with the novel two-step approach with those obtained from a reference analysis that applies Saltelli's MC method. The two-step approach was found to yield accurate estimates of the sensitivity indices at two orders of magnitude lower computational cost. Copyright © 2015 John Wiley & Sons, Ltd.

  5. Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

    Directory of Open Access Journals (Sweden)

    Xiao-meng Song

    2013-01-01

    Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

  6. Variance-based sensitivity analysis for wastewater treatment plant modelling.

    Science.gov (United States)

    Cosenza, Alida; Mannina, Giorgio; Vanrolleghem, Peter A; Neumann, Marc B

    2014-02-01

    Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. © 2013.

  7. RETRAN sensitivity studies of light water reactor transients. Final report

    International Nuclear Information System (INIS)

    Burrell, N.S.; Gose, G.C.; Harrison, J.F.; Sawtelle, G.R.

    1977-06-01

    This report presents the results of sensitivity studies performed using the RETRAN/RELAP4 transient analysis code to identify critical parameters and models which influence light water reactor transient predictions. Various plant transients for both boiling water reactors and pressurized water reactors are examined. These studies represent the first detailed evaluation of the RETRAN/RELAP4 transient code capability in predicting a variety of plant transient responses. The wide range of transients analyzed in conjunction with the parameter and modeling studies performed identify several sensitive areas as well as areas requiring future study and model development

  8. Model of urban water management towards water sensitive city: a literature review

    Science.gov (United States)

    Maftuhah, D. I.; Anityasari, M.; Sholihah, M.

    2018-04-01

    Nowadays, many cities are facing with complex issues such as climate change, social, economic, culture, and environmental problems, especially urban water. In other words, the city has to struggle with the challenge to make sure its sustainability in all aspects. This research focuses on how to ensure the city sustainability and resilience on urban water management. Many research were not only conducted in urban water management, but also in sustainability itself. Moreover, water sustainability shifts from urban water management into water sensitive city. This transition needs comprehensive aspects such as social, institutional dynamics, technical innovation, and local contents. Some literatures about model of urban water management and the transition towards water sensitivity had been reviewed in this study. This study proposed discussion about model of urban water management and the transition towards water sensitive city. Research findings suggest that there are many different models developed in urban water management, but they are not comprehensive yet and only few studies discuss about the transition towards water sensitive and resilience city. The drawbacks of previous research can identify and fulfill the gap of this study. Therefore, the paper contributes a general framework for the urban water management modelling studies.

  9. A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

    Science.gov (United States)

    Wang, Daosheng; Cao, Anzhou; Zhang, Jicai; Fan, Daidu; Liu, Yongzhi; Zhang, Yue

    2018-06-01

    Based on the theory of inverse problems, a three-dimensional sigma-coordinate cohesive sediment transport model with the adjoint data assimilation is developed. In this model, the physical processes of cohesive sediment transport, including deposition, erosion and advection-diffusion, are parameterized by corresponding model parameters. These parameters are usually poorly known and have traditionally been assigned empirically. By assimilating observations into the model, the model parameters can be estimated using the adjoint method; meanwhile, the data misfit between model results and observations can be decreased. The model developed in this work contains numerous parameters; therefore, it is necessary to investigate the parameter sensitivity of the model, which is assessed by calculating a relative sensitivity function and the gradient of the cost function with respect to each parameter. The results of parameter sensitivity analysis indicate that the model is sensitive to the initial conditions, inflow open boundary conditions, suspended sediment settling velocity and resuspension rate, while the model is insensitive to horizontal and vertical diffusivity coefficients. A detailed explanation of the pattern of sensitivity analysis is also given. In ideal twin experiments, constant parameters are estimated by assimilating 'pseudo' observations. The results show that the sensitive parameters are estimated more easily than the insensitive parameters. The conclusions of this work can provide guidance for the practical applications of this model to simulate sediment transport in the study area.

  10. Sensitivities in global scale modeling of isoprene

    Directory of Open Access Journals (Sweden)

    R. von Kuhlmann

    2004-01-01

    Full Text Available A sensitivity study of the treatment of isoprene and related parameters in 3D atmospheric models was conducted using the global model of tropospheric chemistry MATCH-MPIC. A total of twelve sensitivity scenarios which can be grouped into four thematic categories were performed. These four categories consist of simulations with different chemical mechanisms, different assumptions concerning the deposition characteristics of intermediate products, assumptions concerning the nitrates from the oxidation of isoprene and variations of the source strengths. The largest differences in ozone compared to the reference simulation occured when a different isoprene oxidation scheme was used (up to 30-60% or about 10 nmol/mol. The largest differences in the abundance of peroxyacetylnitrate (PAN were found when the isoprene emission strength was reduced by 50% and in tests with increased or decreased efficiency of the deposition of intermediates. The deposition assumptions were also found to have a significant effect on the upper tropospheric HOx production. Different implicit assumptions about the loss of intermediate products were identified as a major reason for the deviations among the tested isoprene oxidation schemes. The total tropospheric burden of O3 calculated in the sensitivity runs is increased compared to the background methane chemistry by 26±9  Tg( O3 from 273 to an average from the sensitivity runs of 299 Tg(O3. % revised Thus, there is a spread of ± 35% of the overall effect of isoprene in the model among the tested scenarios. This range of uncertainty and the much larger local deviations found in the test runs suggest that the treatment of isoprene in global models can only be seen as a first order estimate at present, and points towards specific processes in need of focused future work.

  11. Prior Sensitivity Analysis in Default Bayesian Structural Equation Modeling.

    Science.gov (United States)

    van Erp, Sara; Mulder, Joris; Oberski, Daniel L

    2017-11-27

    Bayesian structural equation modeling (BSEM) has recently gained popularity because it enables researchers to fit complex models and solve some of the issues often encountered in classical maximum likelihood estimation, such as nonconvergence and inadmissible solutions. An important component of any Bayesian analysis is the prior distribution of the unknown model parameters. Often, researchers rely on default priors, which are constructed in an automatic fashion without requiring substantive prior information. However, the prior can have a serious influence on the estimation of the model parameters, which affects the mean squared error, bias, coverage rates, and quantiles of the estimates. In this article, we investigate the performance of three different default priors: noninformative improper priors, vague proper priors, and empirical Bayes priors-with the latter being novel in the BSEM literature. Based on a simulation study, we find that these three default BSEM methods may perform very differently, especially with small samples. A careful prior sensitivity analysis is therefore needed when performing a default BSEM analysis. For this purpose, we provide a practical step-by-step guide for practitioners to conducting a prior sensitivity analysis in default BSEM. Our recommendations are illustrated using a well-known case study from the structural equation modeling literature, and all code for conducting the prior sensitivity analysis is available in the online supplemental materials. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  12. The Sensitivity of State Differential Game Vessel Traffic Model

    Directory of Open Access Journals (Sweden)

    Lisowski Józef

    2016-04-01

    Full Text Available The paper presents the application of the theory of deterministic sensitivity control systems for sensitivity analysis implemented to game control systems of moving objects, such as ships, airplanes and cars. The sensitivity of parametric model of game ship control process in collision situations have been presented. First-order and k-th order sensitivity functions of parametric model of process control are described. The structure of the game ship control system in collision situations and the mathematical model of game control process in the form of state equations, are given. Characteristics of sensitivity functions of the game ship control process model on the basis of computer simulation in Matlab/Simulink software have been presented. In the end, have been given proposals regarding the use of sensitivity analysis to practical synthesis of computer-aided system navigator in potential collision situations.

  13. Automating sensitivity analysis of computer models using computer calculus

    International Nuclear Information System (INIS)

    Oblow, E.M.; Pin, F.G.

    1985-01-01

    An automated procedure for performing sensitivity analyses has been developed. The procedure uses a new FORTRAN compiler with computer calculus capabilities to generate the derivatives needed to set up sensitivity equations. The new compiler is called GRESS - Gradient Enhanced Software System. Application of the automated procedure with ''direct'' and ''adjoint'' sensitivity theory for the analysis of non-linear, iterative systems of equations is discussed. Calculational efficiency consideration and techniques for adjoint sensitivity analysis are emphasized. The new approach is found to preserve the traditional advantages of adjoint theory while removing the tedious human effort previously needed to apply this theoretical methodology. Conclusions are drawn about the applicability of the automated procedure in numerical analysis and large-scale modelling sensitivity studies. 24 refs., 2 figs

  14. Automating sensitivity analysis of computer models using computer calculus

    International Nuclear Information System (INIS)

    Oblow, E.M.; Pin, F.G.

    1986-01-01

    An automated procedure for performing sensitivity analysis has been developed. The procedure uses a new FORTRAN compiler with computer calculus capabilities to generate the derivatives needed to set up sensitivity equations. The new compiler is called GRESS - Gradient Enhanced Software System. Application of the automated procedure with direct and adjoint sensitivity theory for the analysis of non-linear, iterative systems of equations is discussed. Calculational efficiency consideration and techniques for adjoint sensitivity analysis are emphasized. The new approach is found to preserve the traditional advantages of adjoint theory while removing the tedious human effort previously needed to apply this theoretical methodology. Conclusions are drawn about the applicability of the automated procedure in numerical analysis and large-scale modelling sensitivity studies

  15. Sensitivity analysis of Takagi-Sugeno-Kang rainfall-runoff fuzzy models

    Directory of Open Access Journals (Sweden)

    A. P. Jacquin

    2009-01-01

    Full Text Available This paper is concerned with the sensitivity analysis of the model parameters of the Takagi-Sugeno-Kang fuzzy rainfall-runoff models previously developed by the authors. These models are classified in two types of fuzzy models, where the first type is intended to account for the effect of changes in catchment wetness and the second type incorporates seasonality as a source of non-linearity. The sensitivity analysis is performed using two global sensitivity analysis methods, namely Regional Sensitivity Analysis and Sobol's variance decomposition. The data of six catchments from different geographical locations and sizes are used in the sensitivity analysis. The sensitivity of the model parameters is analysed in terms of several measures of goodness of fit, assessing the model performance from different points of view. These measures include the Nash-Sutcliffe criteria, volumetric errors and peak errors. The results show that the sensitivity of the model parameters depends on both the catchment type and the measure used to assess the model performance.

  16. WRF model sensitivity to choice of parameterization: a study of the `York Flood 1999'

    Science.gov (United States)

    Remesan, Renji; Bellerby, Tim; Holman, Ian; Frostick, Lynne

    2015-10-01

    Numerical weather modelling has gained considerable attention in the field of hydrology especially in un-gauged catchments and in conjunction with distributed models. As a consequence, the accuracy with which these models represent precipitation, sub-grid-scale processes and exceptional events has become of considerable concern to the hydrological community. This paper presents sensitivity analyses for the Weather Research Forecast (WRF) model with respect to the choice of physical parameterization schemes (both cumulus parameterisation (CPSs) and microphysics parameterization schemes (MPSs)) used to represent the `1999 York Flood' event, which occurred over North Yorkshire, UK, 1st-14th March 1999. The study assessed four CPSs (Kain-Fritsch (KF2), Betts-Miller-Janjic (BMJ), Grell-Devenyi ensemble (GD) and the old Kain-Fritsch (KF1)) and four MPSs (Kessler, Lin et al., WRF single-moment 3-class (WSM3) and WRF single-moment 5-class (WSM5)] with respect to their influence on modelled rainfall. The study suggests that the BMJ scheme may be a better cumulus parameterization choice for the study region, giving a consistently better performance than other three CPSs, though there are suggestions of underestimation. The WSM3 was identified as the best MPSs and a combined WSM3/BMJ model setup produced realistic estimates of precipitation quantities for this exceptional flood event. This study analysed spatial variability in WRF performance through categorical indices, including POD, FBI, FAR and CSI during York Flood 1999 under various model settings. Moreover, the WRF model was good at predicting high-intensity rare events over the Yorkshire region, suggesting it has potential for operational use.

  17. Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.

    Science.gov (United States)

    Dresch, Jacqueline M; Liu, Xiaozhou; Arnosti, David N; Ay, Ahmet

    2010-10-24

    Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. We apply local and global sensitivity analyses to two recent transcriptional models to determine the sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive, while values for protein cooperativities are not, and provide insights on why these differential sensitivities stem from both biological effects and the structure of the applied models. In a second case, we demonstrate that parameters that were thought to prove the system's dependence on activator-activator cooperativity are relatively insensitive. We show that there are numerous parameter sets that do not satisfy the relationships proferred as the optimal solutions, indicating that structural differences between the two types of transcriptional enhancers analyzed may not be as simple as altered activator cooperativity. Our results emphasize the need for sensitivity analysis to examine model construction and forms of biological data used for modeling transcriptional processes, in order to determine the significance of estimated parameter values for thermodynamic models. Knowledge of parameter sensitivities can provide the necessary

  18. Computer models versus reality: how well do in silico models currently predict the sensitization potential of a substance.

    Science.gov (United States)

    Teubner, Wera; Mehling, Anette; Schuster, Paul Xaver; Guth, Katharina; Worth, Andrew; Burton, Julien; van Ravenzwaay, Bennard; Landsiedel, Robert

    2013-12-01

    National legislations for the assessment of the skin sensitization potential of chemicals are increasingly based on the globally harmonized system (GHS). In this study, experimental data on 55 non-sensitizing and 45 sensitizing chemicals were evaluated according to GHS criteria and used to test the performance of computer (in silico) models for the prediction of skin sensitization. Statistic models (Vega, Case Ultra, TOPKAT), mechanistic models (Toxtree, OECD (Q)SAR toolbox, DEREK) or a hybrid model (TIMES-SS) were evaluated. Between three and nine of the substances evaluated were found in the individual training sets of various models. Mechanism based models performed better than statistical models and gave better predictivities depending on the stringency of the domain definition. Best performance was achieved by TIMES-SS, with a perfect prediction, whereby only 16% of the substances were within its reliability domain. Some models offer modules for potency; however predictions did not correlate well with the GHS sensitization subcategory derived from the experimental data. In conclusion, although mechanistic models can be used to a certain degree under well-defined conditions, at the present, the in silico models are not sufficiently accurate for broad application to predict skin sensitization potentials. Copyright © 2013 Elsevier Inc. All rights reserved.

  19. A sensitivity study of the thermomechanical far-field model of Yucca Mountain

    International Nuclear Information System (INIS)

    Brandshaug, T.

    1991-04-01

    A sensitivity study has been conducted investigating the predicted thermal and mechanical behavior of the far-field model of a proposed nuclear waste repository at Yucca Mountain. The model input parameters and phenomena that have been investigated include areal power density, thermal conductivity, specific heat capacity, material density, pore water boiling, stratigraphic and topographic simplifications Young's modulus, Poisson's ratio, coefficient of thermal expansion, in situ stress, rock matrix cohesion, rock matrix angle of internal friction, rock joint cohesion, and rock joint angle of internal friction. Using the range in values currently associated with these parameters, predictions were obtained for rock temperatures, stresses, matrix failure, and joint activity throughout the far-field model. Results show that the range considered for the areal power density has the most significant effect on the predicted rock temperatures. The range considered for the in situ stress has the most significant effect on the prediction of rock stresses and factors-of-safety for the matrix and joints. Predictions of matrix and joint factors-of-safety are also influenced significantly by the use of stratigraphic and topographic simplifications. 16 refs., 75 figs., 13 tabs

  20. Application of sensitivity analysis in nuclear power plant probabilistic risk assessment studies

    International Nuclear Information System (INIS)

    Hirschberg, S.; Knochenhauer, M.

    1986-01-01

    Nuclear power plant probabilistic risk assessment (PRA) studies utilise many models, simplifications and assumptions. Also subjective judgement is widely applied due to lack of actual data. This results in significant uncertainties. Three general types of uncertainties have been identified: (1) parameter uncertainties, (2) modelling uncertainties, and (3) completeness uncertainties. The significance of some of the modelling assumptions and simplifications cannot be investigated by assignment and propagation of parameter uncertainties. In such cases the impact of different options may (and should) be studied by performing sensitivity analyses, which concentrate on the most critical elements. This paper describes several items suitable for close examination by means of application of sensitivity analysis, when performing a level 1 PRA. Sensitivity analyses are performed with respect to: (1) boundary conditions (success criteria, credit for non-safety systems, degree of detail in modelling of support functions), (2) operator actions, (3) treatment of common cause failures (CCFs). The items of main interest are continuously identified in the course of performing a PRA study, as well as by scrutinising the final results. The practical aspects of sensitivity analysis are illustrated by several applications from a recent PRA study. The critical importance of modelling assumptions is also demonstrated by implementation of some modelling features from another level 1 PRA into the reference model. It is concluded that sensitivity analysis leads to insights important for analysts, reviewers and decision makers. (author)

  1. SR-Site Pre-modelling: Sensitivity studies of hydrogeological model variants for the Laxemar site using CONNECTFLOW

    Energy Technology Data Exchange (ETDEWEB)

    Joyce, Steven; Hoek, Jaap; Hartley, Lee (Serco (United Kingdom)); Marsic, Niko (Kemakta Konsult AB, Stockholm (Sweden))

    2010-12-15

    This study investigated a number of potential model variants of the SR-Can hydrogeological models of the temperate period and the sensitivity of the performance measures to the chosen parameters. This will help to guide the choice of potential variants for the SR-Site project and provide an input to design premises for the underground construction of the repository. It was found that variation of tunnel backfill properties in the tunnels had a significant effect on performance measures, but in the central area, ramps and shafts it had a lesser effect for those property values chosen. Variation of tunnel EDZ properties only had minor effects on performance measures. The presence of a crown space in the deposition tunnels had a significant effect on the tunnel performance measures and a lesser effect on the rock and EDZ performance measures. The presence of a deposition hole EDZ and spalling also had an effect on the performance measures.

  2. The mobilisation model and parameter sensitivity

    International Nuclear Information System (INIS)

    Blok, B.M.

    1993-12-01

    In the PRObabillistic Safety Assessment (PROSA) of radioactive waste in a salt repository one of the nuclide release scenario's is the subrosion scenario. A new subrosion model SUBRECN has been developed. In this model the combined effect of a depth-dependent subrosion, glass dissolution, and salt rise has been taken into account. The subrosion model SUBRECN and the implementation of this model in the German computer program EMOS4 is presented. A new computer program PANTER is derived from EMOS4. PANTER models releases of radionuclides via subrosion from a disposal site in a salt pillar into the biosphere. For uncertainty and sensitivity analyses the new subrosion model Latin Hypercube Sampling has been used for determine the different values for the uncertain parameters. The influence of the uncertainty in the parameters on the dose calculations has been investigated by the following sensitivity techniques: Spearman Rank Correlation Coefficients, Partial Rank Correlation Coefficients, Standardised Rank Regression Coefficients, and the Smirnov Test. (orig./HP)

  3. Therapeutic Implications from Sensitivity Analysis of Tumor Angiogenesis Models

    Science.gov (United States)

    Poleszczuk, Jan; Hahnfeldt, Philip; Enderling, Heiko

    2015-01-01

    Anti-angiogenic cancer treatments induce tumor starvation and regression by targeting the tumor vasculature that delivers oxygen and nutrients. Mathematical models prove valuable tools to study the proof-of-concept, efficacy and underlying mechanisms of such treatment approaches. The effects of parameter value uncertainties for two models of tumor development under angiogenic signaling and anti-angiogenic treatment are studied. Data fitting is performed to compare predictions of both models and to obtain nominal parameter values for sensitivity analysis. Sensitivity analysis reveals that the success of different cancer treatments depends on tumor size and tumor intrinsic parameters. In particular, we show that tumors with ample vascular support can be successfully targeted with conventional cytotoxic treatments. On the other hand, tumors with curtailed vascular support are not limited by their growth rate and therefore interruption of neovascularization emerges as the most promising treatment target. PMID:25785600

  4. Sensitivity of subject-specific models to Hill muscle-tendon model parameters in simulations of gait.

    Science.gov (United States)

    Carbone, V; van der Krogt, M M; Koopman, H F J M; Verdonschot, N

    2016-06-14

    Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle-tendon (MT) model parameters for each of the 56 MT parts contained in a state-of-the-art MS model. We used two metrics, namely a Local Sensitivity Index (LSI) and an Overall Sensitivity Index (OSI), to distinguish the effect of the perturbation on the predicted force produced by the perturbed MT parts and by all the remaining MT parts, respectively, during a simulated gait cycle. Results indicated that sensitivity of the model depended on the specific role of each MT part during gait, and not merely on its size and length. Tendon slack length was the most sensitive parameter, followed by maximal isometric muscle force and optimal muscle fiber length, while nominal pennation angle showed very low sensitivity. The highest sensitivity values were found for the MT parts that act as prime movers of gait (Soleus: average OSI=5.27%, Rectus Femoris: average OSI=4.47%, Gastrocnemius: average OSI=3.77%, Vastus Lateralis: average OSI=1.36%, Biceps Femoris Caput Longum: average OSI=1.06%) and hip stabilizers (Gluteus Medius: average OSI=3.10%, Obturator Internus: average OSI=1.96%, Gluteus Minimus: average OSI=1.40%, Piriformis: average OSI=0.98%), followed by the Peroneal muscles (average OSI=2.20%) and Tibialis Anterior (average OSI=1.78%) some of which were not included in previous sensitivity studies. Finally, the proposed priority list provides quantitative information to indicate which MT parts and which MT parameters should be estimated most accurately to create detailed and reliable subject-specific MS models. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Sensitivity studies on TIME2 Version 1.0

    International Nuclear Information System (INIS)

    1988-03-01

    The results of a sensitivity analysis of Version 1.0 of the TIME2 computer code to certain aspects of the input data set are presented. Parameters evaluated were: river dimensions, the density and grain size of sediment carried by the river, human intrusion data, sea level rise rate, erosion factors and meander modelling data. The sensitivity of the code to variation of single value parameters was evaluated by means of graphical comparisons. For parameters specified as probability density functions (pdf's), the Kolmogorov-Smirnov test was used. The study assists in the specification of data for TIME2 by identifying parameters to which the models used are particularly sensitive and also suggests that some input currently specified as pdf's could be replaced with single values without affecting the quality of the results obtained. (author)

  6. Dynamic plantwide modeling, uncertainty and sensitivity analysis of a pharmaceutical upstream synthesis: Ibuprofen case study

    DEFF Research Database (Denmark)

    Montes, Frederico C. C.; Gernaey, Krist; Sin, Gürkan

    2018-01-01

    A dynamic plantwide model was developed for the synthesis of the Active pharmaceutical Ingredient (API) ibuprofen, following the Hoescht synthesis process. The kinetic parameters, reagents, products and by-products of the different reactions were adapted from literature, and the different process...... operations integrated until the end process, crystallization and isolation of the ibuprofen crystals. The dynamic model simulations were validated against available measurements from literature and then used as enabling tool to analyze the robustness of design space. To this end, sensitivity of the design...... space towards input disturbances and process uncertainties (from physical and model parameters) is studied using Monte Carlo simulations. The results quantify the uncertainty of the quality of product attributes, with particular focus on crystal size distribution and ibuprofen crystalized. The ranking...

  7. Nordic reference study on uncertainty and sensitivity analysis

    International Nuclear Information System (INIS)

    Hirschberg, S.; Jacobsson, P.; Pulkkinen, U.; Porn, K.

    1989-01-01

    This paper provides a review of the first phase of Nordic reference study on uncertainty and sensitivity analysis. The main objective of this study is to use experiences form previous Nordic Benchmark Exercises and reference studies concerning critical modeling issues such as common cause failures and human interactions, and to demonstrate the impact of associated uncertainties on the uncertainty of the investigated accident sequence. This has been done independently by three working groups which used different approaches to modeling and to uncertainty analysis. The estimated uncertainty interval for the analyzed accident sequence is large. Also the discrepancies between the groups are substantial but can be explained. Sensitivity analyses which have been carried out concern e.g. use of different CCF-quantification models, alternative handling of CCF-data, time windows for operator actions and time dependences in phase mission operation, impact of state-of-knowledge dependences and ranking of dominating uncertainty contributors. Specific findings with respect to these issues are summarized in the paper

  8. Oral sensitization to food proteins: A Brown Norway rat model

    NARCIS (Netherlands)

    Knippels, L.M.J.; Penninks, A.H.; Spanhaak, S.; Houben, G.F.

    1998-01-01

    Background: Although several in vivo antigenicity assays using parenteral immunization are operational, no adequate enteral sensitization models are available to study food allergy and allergenicity of food proteins. Objective: This paper describes the development of an enteral model for food

  9. Sensitivity of tropospheric heating rates to aerosols: A modeling study

    International Nuclear Information System (INIS)

    Hanna, A.F.; Shankar, U.; Mathur, R.

    1994-01-01

    The effect of aerosols on the radiation balance is critical to the energetics of the atmosphere. Because of the relatively long residence of specific types of aerosols in the atmosphere and their complex thermal and chemical interactions, understanding their behavior is crucial for understanding global climate change. The authors used the Regional Particulate Model (RPM) to simulate aerosols in the eastern United States in order to identify the aerosol characteristics of specific rural and urban areas these characteristics include size, concentration, and vertical profile. A radiative transfer model based on an improved δ-Eddington approximation with 26 spectral intervals spanning the solar spectrum was then used to analyze the tropospheric heating rates associated with these different aerosol distributions. The authors compared heating rates forced by differences in surface albedo associated with different land-use characteristics, and found that tropospheric heating and surface cooling are sensitive to surface properties such as albedo

  10. Automated differentiation of computer models for sensitivity analysis

    International Nuclear Information System (INIS)

    Worley, B.A.

    1990-01-01

    Sensitivity analysis of reactor physics computer models is an established discipline after more than twenty years of active development of generalized perturbations theory based on direct and adjoint methods. Many reactor physics models have been enhanced to solve for sensitivities of model results to model data. The calculated sensitivities are usually normalized first derivatives although some codes are capable of solving for higher-order sensitivities. The purpose of this paper is to report on the development and application of the GRESS system for automating the implementation of the direct and adjoint techniques into existing FORTRAN computer codes. The GRESS system was developed at ORNL to eliminate the costly man-power intensive effort required to implement the direct and adjoint techniques into already-existing FORTRAN codes. GRESS has been successfully tested for a number of codes over a wide range of applications and presently operates on VAX machines under both VMS and UNIX operating systems

  11. Automated differentiation of computer models for sensitivity analysis

    International Nuclear Information System (INIS)

    Worley, B.A.

    1991-01-01

    Sensitivity analysis of reactor physics computer models is an established discipline after more than twenty years of active development of generalized perturbations theory based on direct and adjoint methods. Many reactor physics models have been enhanced to solve for sensitivities of model results to model data. The calculated sensitivities are usually normalized first derivatives, although some codes are capable of solving for higher-order sensitivities. The purpose of this paper is to report on the development and application of the GRESS system for automating the implementation of the direct and adjoint techniques into existing FORTRAN computer codes. The GRESS system was developed at ORNL to eliminate the costly man-power intensive effort required to implement the direct and adjoint techniques into already-existing FORTRAN codes. GRESS has been successfully tested for a number of codes over a wide range of applications and presently operates on VAX machines under both VMS and UNIX operating systems. (author). 9 refs, 1 tab

  12. Transient dynamic and modeling parameter sensitivity analysis of 1D solid oxide fuel cell model

    International Nuclear Information System (INIS)

    Huangfu, Yigeng; Gao, Fei; Abbas-Turki, Abdeljalil; Bouquain, David; Miraoui, Abdellatif

    2013-01-01

    Highlights: • A multiphysics, 1D, dynamic SOFC model is developed. • The presented model is validated experimentally in eight different operating conditions. • Electrochemical and thermal dynamic transient time expressions are given in explicit forms. • Parameter sensitivity is discussed for different semi-empirical parameters in the model. - Abstract: In this paper, a multiphysics solid oxide fuel cell (SOFC) dynamic model is developed by using a one dimensional (1D) modeling approach. The dynamic effects of double layer capacitance on the electrochemical domain and the dynamic effect of thermal capacity on thermal domain are thoroughly considered. The 1D approach allows the model to predict the non-uniform distributions of current density, gas pressure and temperature in SOFC during its operation. The developed model has been experimentally validated, under different conditions of temperature and gas pressure. Based on the proposed model, the explicit time constant expressions for different dynamic phenomena in SOFC have been given and discussed in detail. A parameters sensitivity study has also been performed and discussed by using statistical Multi Parameter Sensitivity Analysis (MPSA) method, in order to investigate the impact of parameters on the modeling accuracy

  13. Importance measures in global sensitivity analysis of nonlinear models

    International Nuclear Information System (INIS)

    Homma, Toshimitsu; Saltelli, Andrea

    1996-01-01

    The present paper deals with a new method of global sensitivity analysis of nonlinear models. This is based on a measure of importance to calculate the fractional contribution of the input parameters to the variance of the model prediction. Measures of importance in sensitivity analysis have been suggested by several authors, whose work is reviewed in this article. More emphasis is given to the developments of sensitivity indices by the Russian mathematician I.M. Sobol'. Given that Sobol' treatment of the measure of importance is the most general, his formalism is employed throughout this paper where conceptual and computational improvements of the method are presented. The computational novelty of this study is the introduction of the 'total effect' parameter index. This index provides a measure of the total effect of a given parameter, including all the possible synergetic terms between that parameter and all the others. Rank transformation of the data is also introduced in order to increase the reproducibility of the method. These methods are tested on a few analytical and computer models. The main conclusion of this work is the identification of a sensitivity analysis methodology which is both flexible, accurate and informative, and which can be achieved at reasonable computational cost

  14. Structure and sensitivity analysis of individual-based predator–prey models

    International Nuclear Information System (INIS)

    Imron, Muhammad Ali; Gergs, Andre; Berger, Uta

    2012-01-01

    The expensive computational cost of sensitivity analyses has hampered the use of these techniques for analysing individual-based models in ecology. A relatively cheap computational cost, referred to as the Morris method, was chosen to assess the relative effects of all parameters on the model’s outputs and to gain insights into predator–prey systems. Structure and results of the sensitivity analysis of the Sumatran tiger model – the Panthera Population Persistence (PPP) and the Notonecta foraging model (NFM) – were compared. Both models are based on a general predation cycle and designed to understand the mechanisms behind the predator–prey interaction being considered. However, the models differ significantly in their complexity and the details of the processes involved. In the sensitivity analysis, parameters that directly contribute to the number of prey items killed were found to be most influential. These were the growth rate of prey and the hunting radius of tigers in the PPP model as well as attack rate parameters and encounter distance of backswimmers in the NFM model. Analysis of distances in both of the models revealed further similarities in the sensitivity of the two individual-based models. The findings highlight the applicability and importance of sensitivity analyses in general, and screening design methods in particular, during early development of ecological individual-based models. Comparison of model structures and sensitivity analyses provides a first step for the derivation of general rules in the design of predator–prey models for both practical conservation and conceptual understanding. - Highlights: ► Structure of predation processes is similar in tiger and backswimmer model. ► The two individual-based models (IBM) differ in space formulations. ► In both models foraging distance is among the sensitive parameters. ► Morris method is applicable for the sensitivity analysis even of complex IBMs.

  15. Modeling and Sensitivity Study of Consensus Algorithm-Based Distributed Hierarchical Control for DC Microgrids

    DEFF Research Database (Denmark)

    Meng, Lexuan; Dragicevic, Tomislav; Roldan Perez, Javier

    2016-01-01

    Distributed control methods based on consensus algorithms have become popular in recent years for microgrid (MG) systems. These kinds of algorithms can be applied to share information in order to coordinate multiple distributed generators within a MG. However, stability analysis becomes a challen......Distributed control methods based on consensus algorithms have become popular in recent years for microgrid (MG) systems. These kinds of algorithms can be applied to share information in order to coordinate multiple distributed generators within a MG. However, stability analysis becomes...... in the communication network, continuous-time methods can be inaccurate for this kind of dynamic study. Therefore, this paper aims at modeling a complete DC MG using a discrete-time approach in order to perform a sensitivity analysis taking into account the effects of the consensus algorithm. To this end......, a generalized modeling method is proposed and the influence of key control parameters, the communication topology and the communication speed are studied in detail. The theoretical results obtained with the proposed model are verified by comparing them with the results obtained with a detailed switching...

  16. Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?: NUDGING AND MODEL SENSITIVITIES

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Guangxing [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Wan, Hui [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Zhang, Kai [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Qian, Yun [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Ghan, Steven J. [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA

    2016-07-10

    Efficient simulation strategies are crucial for the development and evaluation of high resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low-level stratiform clouds (rhminl). Results suggest that the fidelity and computational efficiency of the constrained simulations depend strongly on 3 factors: the detailed implementation of nudging, the mechanism through which the perturbed parameter affects precipitation and cloud, and the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature and/or wind nudging with a 6-hour relaxation time scale leads to non-negligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while a 1-year free running simulation can satisfactorily capture the annual mean precipitation sensitivity in terms of both global average and geographical distribution. In the case of a relatively weak perturbation the large-scale condensation scheme, results from 1-year free-running simulations are strongly affected by noise associated with internal variability, while nudging winds effectively reduces the noise, and reasonably reproduces the response of precipitation and cloud forcing to parameter perturbation. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.

  17. Sensitivity and uncertainty studies of the CRAC2 computer code

    International Nuclear Information System (INIS)

    Kocher, D.C.; Ward, R.C.; Killough, G.G.; Dunning, D.E. Jr.; Hicks, B.B.; Hosker, R.P. Jr.; Ku, J.Y.; Rao, K.S.

    1987-01-01

    The authors have studied the sensitivity of health impacts from nuclear reactor accidents, as predicted by the CRAC2 computer code, to the following sources of uncertainty: (1) the model for plume rise, (2) the model for wet deposition, (3) the meteorological bin-sampling procedure for selecting weather sequences with rain, (4) the dose conversion factors for inhalation as affected by uncertainties in the particle size of the carrier aerosol and the clearance rates of radionuclides from the respiratory tract, (5) the weathering half-time for external ground-surface exposure, and (6) the transfer coefficients for terrestrial foodchain pathways. Predicted health impacts usually showed little sensitivity to use of an alternative plume-rise model or a modified rain-bin structure in bin-sampling. Health impacts often were quite sensitive to use of an alternative wet-deposition model in single-trial runs with rain during plume passage, but were less sensitive to the model in bin-sampling runs. Uncertainties in the inhalation dose conversion factors had important effects on early injuries in single-trial runs. Latent cancer fatalities were moderately sensitive to uncertainties in the weathering half-time for ground-surface exposures, but showed little sensitivity to the transfer coefficients for terrestrial foodchain pathways. Sensitivities of CRAC2 predictions to uncertainties in the models and parameters also depended on the magnitude of the source term, and some of the effects on early health effects were comparable to those that were due only to selection of different sets of weather sequences in bin-sampling

  18. Modelling survival: exposure pattern, species sensitivity and uncertainty.

    Science.gov (United States)

    Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G

    2016-07-06

    The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

  19. Sensitivity Assessment of Ozone Models

    Energy Technology Data Exchange (ETDEWEB)

    Shorter, Jeffrey A.; Rabitz, Herschel A.; Armstrong, Russell A.

    2000-01-24

    The activities under this contract effort were aimed at developing sensitivity analysis techniques and fully equivalent operational models (FEOMs) for applications in the DOE Atmospheric Chemistry Program (ACP). MRC developed a new model representation algorithm that uses a hierarchical, correlated function expansion containing a finite number of terms. A full expansion of this type is an exact representation of the original model and each of the expansion functions is explicitly calculated using the original model. After calculating the expansion functions, they are assembled into a fully equivalent operational model (FEOM) that can directly replace the original mode.

  20. Uncertainty and Sensitivity of Alternative Rn-222 Flux Density Models Used in Performance Assessment

    International Nuclear Information System (INIS)

    Greg J. Shott, Vefa Yucel, Lloyd Desotell Non-Nstec Authors: G. Pyles and Jon Carilli

    2007-01-01

    Performance assessments for the Area 5 Radioactive Waste Management Site on the Nevada Test Site have used three different mathematical models to estimate Rn-222 flux density. This study describes the performance, uncertainty, and sensitivity of the three models which include the U.S. Nuclear Regulatory Commission Regulatory Guide 3.64 analytical method and two numerical methods. The uncertainty of each model was determined by Monte Carlo simulation using Latin hypercube sampling. The global sensitivity was investigated using Morris one-at-time screening method, sample-based correlation and regression methods, the variance-based extended Fourier amplitude sensitivity test, and Sobol's sensitivity indices. The models were found to produce similar estimates of the mean and median flux density, but to have different uncertainties and sensitivities. When the Rn-222 effective diffusion coefficient was estimated using five different published predictive models, the radon flux density models were found to be most sensitive to the effective diffusion coefficient model selected, the emanation coefficient, and the radionuclide inventory. Using a site-specific measured effective diffusion coefficient significantly reduced the output uncertainty. When a site-specific effective-diffusion coefficient was used, the models were most sensitive to the emanation coefficient and the radionuclide inventory

  1. A non-human primate model for gluten sensitivity.

    Directory of Open Access Journals (Sweden)

    Michael T Bethune

    2008-02-01

    Full Text Available Gluten sensitivity is widespread among humans. For example, in celiac disease patients, an inflammatory response to dietary gluten leads to enteropathy, malabsorption, circulating antibodies against gluten and transglutaminase 2, and clinical symptoms such as diarrhea. There is a growing need in fundamental and translational research for animal models that exhibit aspects of human gluten sensitivity.Using ELISA-based antibody assays, we screened a population of captive rhesus macaques with chronic diarrhea of non-infectious origin to estimate the incidence of gluten sensitivity. A selected animal with elevated anti-gliadin antibodies and a matched control were extensively studied through alternating periods of gluten-free diet and gluten challenge. Blinded clinical and histological evaluations were conducted to seek evidence for gluten sensitivity.When fed with a gluten-containing diet, gluten-sensitive macaques showed signs and symptoms of celiac disease including chronic diarrhea, malabsorptive steatorrhea, intestinal lesions and anti-gliadin antibodies. A gluten-free diet reversed these clinical, histological and serological features, while reintroduction of dietary gluten caused rapid relapse.Gluten-sensitive rhesus macaques may be an attractive resource for investigating both the pathogenesis and the treatment of celiac disease.

  2. Deterministic sensitivity and uncertainty analysis for large-scale computer models

    International Nuclear Information System (INIS)

    Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.

    1988-01-01

    This paper presents a comprehensive approach to sensitivity and uncertainty analysis of large-scale computer models that is analytic (deterministic) in principle and that is firmly based on the model equations. The theory and application of two systems based upon computer calculus, GRESS and ADGEN, are discussed relative to their role in calculating model derivatives and sensitivities without a prohibitive initial manpower investment. Storage and computational requirements for these two systems are compared for a gradient-enhanced version of the PRESTO-II computer model. A Deterministic Uncertainty Analysis (DUA) method that retains the characteristics of analytically computing result uncertainties based upon parameter probability distributions is then introduced and results from recent studies are shown. 29 refs., 4 figs., 1 tab

  3. Cough reflex sensitivity is increased in the guinea pig model of allergic rhinitis.

    Science.gov (United States)

    Brozmanova, M; Plevkova, J; Tatar, M; Kollarik, M

    2008-12-01

    Increased cough reflex sensitivity is found in patients with allergic rhinitis and may contribute to cough caused by rhinitis. We have reported that cough to citric acid is enhanced in the guinea pig model of allergic rhinitis. Here we address the hypothesis that the cough reflex sensitivity is increased in this model. The data from our previous studies were analyzed for the cough reflex sensitivity. The allergic inflammation in the nose was induced by repeated intranasal instillations of ovalbumin in the ovalbumin-sensitized guinea pigs. Cough was induced by inhalation of doubling concentrations of citric acid (0.05-1.6 M). Cough threshold was defined as the lowest concentration of citric acid causing two coughs (C2, expressed as geometric mean [95% confidence interval]). We found that the cough threshold was reduced in animals with allergic rhinitis. C2 was 0.5 M [0.36-0.71 M] and 0.15 M [0.1-0.23 M] prior and after repeated intranasal instillations of ovalbumin, respectively, Preflex sensitivity. C2 was reduced in animals with allergic rhinitis treated orally with vehicle (0.57 M [0.28-1.1] vs. 0.09 M [0.04-0.2 M], Preflex sensitivity is increased in the guinea pig model of allergic rhinitis. Our results suggest that guinea pig is a suitable model for mechanistic studies of increased cough reflex sensitivity in rhinitis.

  4. Multivariate Models for Prediction of Human Skin Sensitization ...

    Science.gov (United States)

    One of the lnteragency Coordinating Committee on the Validation of Alternative Method's (ICCVAM) top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary to produce skin sensitization suggests that no single alternative method will replace the currently accepted animal tests. ICCVAM is evaluating an integrated approach to testing and assessment based on the adverse outcome pathway for skin sensitization that uses machine learning approaches to predict human skin sensitization hazard. We combined data from three in chemico or in vitro assays - the direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT) and KeratinoSens TM assay - six physicochemical properties and an in silico read-across prediction of skin sensitization hazard into 12 variable groups. The variable groups were evaluated using two machine learning approaches , logistic regression and support vector machine, to predict human skin sensitization hazard. Models were trained on 72 substances and tested on an external set of 24 substances. The six models (three logistic regression and three support vector machine) with the highest accuracy (92%) used: (1) DPRA, h-CLAT and read-across; (2) DPRA, h-CLAT, read-across and KeratinoSens; or (3) DPRA, h-CLAT, read-across, KeratinoSens and log P. The models performed better at predicting human skin sensitization hazard than the murine

  5. A Study of Nonlinear Elasticity Effects on Permeability of Stress Sensitive Shale Rocks Using an Improved Coupled Flow and Geomechanics Model: A Case Study of the Longmaxi Shale in China

    Directory of Open Access Journals (Sweden)

    Chenji Wei

    2018-02-01

    Full Text Available Gas transport in shale gas reservoirs is largely affected by rock properties such as permeability. These properties are often sensitive to the in-situ stress state changes. Accurate modeling of shale gas transport in shale reservoir rocks considering the stress sensitive effects on rock petrophysical properties is important for successful shale gas extraction. Nonlinear elasticity in stress sensitive reservoir rocks depicts the nonlinear stress-strain relationship, yet it is not thoroughly studied in previous reservoir modeling works. In this study, an improved coupled flow and geomechanics model that considers nonlinear elasticity is proposed. The model is based on finite element methods, and the nonlinear elasticity in the model is validated with experimental data on shale samples selected from the Longmaxi Formation in Sichuan Basin China. Numerical results indicate that, in stress sensitive shale rocks, nonlinear elasticity affects shale permeability, shale porosity, and distributions of effective stress and pore pressure. Elastic modulus change is dependent on not only in-situ stress state but also stress history path. Without considering nonlinear elasticity, the modeling of shale rock permeability in Longmaxi Formation can overestimate permeability values by 1.6 to 53 times.

  6. Sensitivity of Fit Indices to Misspecification in Growth Curve Models

    Science.gov (United States)

    Wu, Wei; West, Stephen G.

    2010-01-01

    This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…

  7. An Animal Model of Trichloroethylene-Induced Skin Sensitization in BALB/c Mice.

    Science.gov (United States)

    Wang, Hui; Zhang, Jia-xiang; Li, Shu-long; Wang, Feng; Zha, Wan-sheng; Shen, Tong; Wu, Changhao; Zhu, Qi-xing

    2015-01-01

    Trichloroethylene (TCE) is a major occupational hazard and environmental contaminant that can cause multisystem disorders in the form of occupational medicamentosa-like dermatitis. Development of dermatitis involves several proinflammatory cytokines, but their role in TCE-mediated dermatitis has not been examined in a well-defined experimental model. In addition, few animal models of TCE sensitization are available, and the current guinea pig model has apparent limitations. This study aimed to establish a model of TCE-induced skin sensitization in BALB/c mice and to examine the role of several key inflammatory cytokines on TCE sensitization. The sensitization rate of dorsal painted group was 38.3%. Skin edema and erythema occurred in TCE-sensitized groups, as seen in 2,4-dinitrochlorobenzene (DNCB) positive control. Trichloroethylene sensitization-positive (dermatitis [+]) group exhibited increased thickness of epidermis, inflammatory cell infiltration, swelling, and necrosis in dermis and around hair follicle, but ear painted group did not show these histological changes. The concentrations of serum proinflammatory cytokines including tumor necrosis factor (TNF)-α, interferon (IFN)-γ, and interleukin (IL)-2 were significantly increased in 24, 48, and 72 hours dermatitis [+] groups treated with TCE and peaked at 72 hours. Deposition of TNF-α, IFN-γ, and IL-2 into the skin tissue was also revealed by immunohistochemistry. We have established a new animal model of skin sensitization induced by repeated TCE stimulations, and we provide the first evidence that key proinflammatory cytokines including TNF-α, IFN-γ, and IL-2 play an important role in the process of TCE sensitization. © The Author(s) 2015.

  8. Automated sensitivity analysis: New tools for modeling complex dynamic systems

    International Nuclear Information System (INIS)

    Pin, F.G.

    1987-01-01

    Sensitivity analysis is an established methodology used by researchers in almost every field to gain essential insight in design and modeling studies and in performance assessments of complex systems. Conventional sensitivity analysis methodologies, however, have not enjoyed the widespread use they deserve considering the wealth of information they can provide, partly because of their prohibitive cost or the large initial analytical investment they require. Automated systems have recently been developed at ORNL to eliminate these drawbacks. Compilers such as GRESS and EXAP now allow automatic and cost effective calculation of sensitivities in FORTRAN computer codes. In this paper, these and other related tools are described and their impact and applicability in the general areas of modeling, performance assessment and decision making for radioactive waste isolation problems are discussed

  9. Applying incentive sensitization models to behavioral addiction

    DEFF Research Database (Denmark)

    Rømer Thomsen, Kristine; Fjorback, Lone; Møller, Arne

    2014-01-01

    The incentive sensitization theory is a promising model for understanding the mechanisms underlying drug addiction, and has received support in animal and human studies. So far the theory has not been applied to the case of behavioral addictions like Gambling Disorder, despite sharing clinical...... symptoms and underlying neurobiology. We examine the relevance of this theory for Gambling Disorder and point to predictions for future studies. The theory promises a significant contribution to the understanding of behavioral addiction and opens new avenues for treatment....

  10. Evaluating two model reduction approaches for large scale hedonic models sensitive to omitted variables and multicollinearity

    DEFF Research Database (Denmark)

    Panduro, Toke Emil; Thorsen, Bo Jellesmark

    2014-01-01

    Hedonic models in environmental valuation studies have grown in terms of number of transactions and number of explanatory variables. We focus on the practical challenge of model reduction, when aiming for reliable parsimonious models, sensitive to omitted variable bias and multicollinearity. We...

  11. Uncertainty and Sensitivity of Alternative Rn-222 Flux Density Models Used in Performance Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Greg J. Shott, Vefa Yucel, Lloyd Desotell

    2007-06-01

    Performance assessments for the Area 5 Radioactive Waste Management Site on the Nevada Test Site have used three different mathematical models to estimate Rn-222 flux density. This study describes the performance, uncertainty, and sensitivity of the three models which include the U.S. Nuclear Regulatory Commission Regulatory Guide 3.64 analytical method and two numerical methods. The uncertainty of each model was determined by Monte Carlo simulation using Latin hypercube sampling. The global sensitivity was investigated using Morris one-at-time screening method, sample-based correlation and regression methods, the variance-based extended Fourier amplitude sensitivity test, and Sobol's sensitivity indices. The models were found to produce similar estimates of the mean and median flux density, but to have different uncertainties and sensitivities. When the Rn-222 effective diffusion coefficient was estimated using five different published predictive models, the radon flux density models were found to be most sensitive to the effective diffusion coefficient model selected, the emanation coefficient, and the radionuclide inventory. Using a site-specific measured effective diffusion coefficient significantly reduced the output uncertainty. When a site-specific effective-diffusion coefficient was used, the models were most sensitive to the emanation coefficient and the radionuclide inventory.

  12. INFLUENCE OF MODIFIED BIOFLAVONOIDS UPON EFFECTOR LYMPHOCYTES IN MURINE MODEL OF CONTACT SENSITIVITY

    Directory of Open Access Journals (Sweden)

    D. Z. Albegova

    2015-01-01

    Full Text Available Contact sensitivity reaction (CSR to 2,4-dinitrofluorobenzene (DNFB in mice is a model of in vivo immune response, being an experimental analogue to contact dermatitis in humans. CSR sensitization phase begins after primary contact with antigen, lasting for 10-15 days in humans, and 5-7 days, in mice. Repeated skin exposure to the sensitizing substance leads to its recognition and triggering immune inflammatory mechanisms involving DNFB-specific effector T lymphocytes. The CSR reaches its maximum 18-48 hours after re-exposure to a hapten. There is only scarce information in the literature about effects of flavonoids on CSR, including both stimulatory and inhibitory effects. Flavonoids possessed, predominantly, suppressive effects against the CSR development. In our laboratory, a model of contact sensitivity was reproduced in CBA mice by means of cutaneous sensitization by 2,4-dinitrofluorobenzene. The aim of the study was to identify the mechanisms of immunomodulatory action of quercetin dihydrate and modified bioflavonoids, using the method of adoptive transfer contact sensitivity by splenocytes and T-lymphocytes. As shown in our studies, a 30-min pre-treatment of splenocytes and T-lymphocytes from sensitized mice with modified bioflavonoids before the cell transfer caused complete prevention of contact sensitivity reaction in syngeneic recipient mice. Meanwhile, this effect was not associated with cell death induction due to apoptosis or cytotoxicity. Quercetin dihydrate caused only partially suppression the activity of adaptively formed T-lymphocytes, the contact sensitivity effectors. It was shown that the modified bioflavonoid more stronger suppress adoptive transfer of contact sensitivity in comparison with quercetin dehydrate, without inducing apoptosis of effector cells. Thus, the modified bioflavonoid is a promising compound for further studies in a model of contact sensitivity, due to its higher ability to suppress transfer of CSR with

  13. A tool model for predicting atmospheric kinetics with sensitivity analysis

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A package( a tool model) for program of predicting atmospheric chemical kinetics with sensitivity analysis is presented. The new direct method of calculating the first order sensitivity coefficients using sparse matrix technology to chemical kinetics is included in the tool model, it is only necessary to triangularize the matrix related to the Jacobian matrix of the model equation. The Gear type procedure is used to integrate amodel equation and its coupled auxiliary sensitivity coefficient equations. The FORTRAN subroutines of the model equation, the sensitivity coefficient equations, and their Jacobian analytical expressions are generated automatically from a chemical mechanism. The kinetic representation for the model equation and its sensitivity coefficient equations, and their Jacobian matrix is presented. Various FORTRAN subroutines in packages, such as SLODE, modified MA28, Gear package, with which the program runs in conjunction are recommended.The photo-oxidation of dimethyl disulfide is used for illustration.

  14. Sensitivity studies and a simple ozone perturbation experiment with a truncated two-dimensional model of the stratosphere

    Science.gov (United States)

    Stordal, Frode; Garcia, Rolando R.

    1987-01-01

    The 1-1/2-D model of Holton (1986), which is actually a highly truncated two-dimensional model, describes latitudinal variations of tracer mixing ratios in terms of their projections onto second-order Legendre polynomials. The present study extends the work of Holton by including tracers with photochemical production in the stratosphere (O3 and NOy). It also includes latitudinal variations in the photochemical sources and sinks, improving slightly the calculated global mean profiles for the long-lived tracers studied by Holton and improving substantially the latitudinal behavior of ozone. Sensitivity tests of the dynamical parameters in the model are performed, showing that the response of the model to changes in vertical residual meridional winds and horizontal diffusion coefficients is similar to that of a full two-dimensional model. A simple ozone perturbation experiment shows the model's ability to reproduce large-scale latitudinal variations in total ozone column depletions as well as ozone changes in the chemically controlled upper stratosphere.

  15. Influence of selecting secondary settling tank sub-models on the calibration of WWTP models – A global sensitivity analysis using BSM2

    DEFF Research Database (Denmark)

    Ramin, Elham; Flores Alsina, Xavier; Sin, Gürkan

    2014-01-01

    This study investigates the sensitivity of wastewater treatment plant (WWTP) model performance to the selection of one-dimensional secondary settling tanks (1-D SST) models with first-order and second-order mathematical structures. We performed a global sensitivity analysis (GSA) on the benchmark...... simulation model No.2 with the input uncertainty associated to the biokinetic parameters in the activated sludge model No. 1 (ASM1), a fractionation parameter in the primary clarifier, and the settling parameters in the SST model. Based on the parameter sensitivity rankings obtained in this study......, the settling parameters were found to be as influential as the biokinetic parameters on the uncertainty of WWTP model predictions, particularly for biogas production and treated water quality. However, the sensitivity measures were found to be dependent on the 1-D SST models selected. Accordingly, we suggest...

  16. Uncertainty Quantification and Sensitivity Analysis in the CICE v5.1 Sea Ice Model

    Science.gov (United States)

    Urrego-Blanco, J. R.; Urban, N. M.

    2015-12-01

    Changes in the high latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with mid latitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. In this work we characterize parametric uncertainty in Los Alamos Sea Ice model (CICE) and quantify the sensitivity of sea ice area, extent and volume with respect to uncertainty in about 40 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one-at-a-time, this study uses a global variance-based approach in which Sobol sequences are used to efficiently sample the full 40-dimensional parameter space. This approach requires a very large number of model evaluations, which are expensive to run. A more computationally efficient approach is implemented by training and cross-validating a surrogate (emulator) of the sea ice model with model output from 400 model runs. The emulator is used to make predictions of sea ice extent, area, and volume at several model configurations, which are then used to compute the Sobol sensitivity indices of the 40 parameters. A ranking based on the sensitivity indices indicates that model output is most sensitive to snow parameters such as conductivity and grain size, and the drainage of melt ponds. The main effects and interactions among the most influential parameters are also estimated by a non-parametric regression technique based on generalized additive models. It is recommended research to be prioritized towards more accurately determining these most influential parameters values by observational studies or by improving existing parameterizations in the sea ice model.

  17. Sensitivity analysis of an individual-based model for simulation of influenza epidemics.

    Directory of Open Access Journals (Sweden)

    Elaine O Nsoesie

    Full Text Available Individual-based epidemiology models are increasingly used in the study of influenza epidemics. Several studies on influenza dynamics and evaluation of intervention measures have used the same incubation and infectious period distribution parameters based on the natural history of influenza. A sensitivity analysis evaluating the influence of slight changes to these parameters (in addition to the transmissibility would be useful for future studies and real-time modeling during an influenza pandemic.In this study, we examined individual and joint effects of parameters and ranked parameters based on their influence on the dynamics of simulated epidemics. We also compared the sensitivity of the model across synthetic social networks for Montgomery County in Virginia and New York City (and surrounding metropolitan regions with demographic and rural-urban differences. In addition, we studied the effects of changing the mean infectious period on age-specific epidemics. The research was performed from a public health standpoint using three relevant measures: time to peak, peak infected proportion and total attack rate. We also used statistical methods in the design and analysis of the experiments. The results showed that: (i minute changes in the transmissibility and mean infectious period significantly influenced the attack rate; (ii the mean of the incubation period distribution appeared to be sufficient for determining its effects on the dynamics of epidemics; (iii the infectious period distribution had the strongest influence on the structure of the epidemic curves; (iv the sensitivity of the individual-based model was consistent across social networks investigated in this study and (v age-specific epidemics were sensitive to changes in the mean infectious period irrespective of the susceptibility of the other age groups. These findings suggest that small changes in some of the disease model parameters can significantly influence the uncertainty

  18. The sensitivity of flowline models of tidewater glaciers to parameter uncertainty

    Directory of Open Access Journals (Sweden)

    E. M. Enderlin

    2013-10-01

    Full Text Available Depth-integrated (1-D flowline models have been widely used to simulate fast-flowing tidewater glaciers and predict change because the continuous grounding line tracking, high horizontal resolution, and physically based calving criterion that are essential to realistic modeling of tidewater glaciers can easily be incorporated into the models while maintaining high computational efficiency. As with all models, the values for parameters describing ice rheology and basal friction must be assumed and/or tuned based on observations. For prognostic studies, these parameters are typically tuned so that the glacier matches observed thickness and speeds at an initial state, to which a perturbation is applied. While it is well know that ice flow models are sensitive to these parameters, the sensitivity of tidewater glacier models has not been systematically investigated. Here we investigate the sensitivity of such flowline models of outlet glacier dynamics to uncertainty in three key parameters that influence a glacier's resistive stress components. We find that, within typical observational uncertainty, similar initial (i.e., steady-state glacier configurations can be produced with substantially different combinations of parameter values, leading to differing transient responses after a perturbation is applied. In cases where the glacier is initially grounded near flotation across a basal over-deepening, as typically observed for rapidly changing glaciers, these differences can be dramatic owing to the threshold of stability imposed by the flotation criterion. The simulated transient response is particularly sensitive to the parameterization of ice rheology: differences in ice temperature of ~ 2 °C can determine whether the glaciers thin to flotation and retreat unstably or remain grounded on a marine shoal. Due to the highly non-linear dependence of tidewater glaciers on model parameters, we recommend that their predictions are accompanied by

  19. Sensitivity and uncertainty studies of the CRAC2 code for selected meteorological models and parameters

    International Nuclear Information System (INIS)

    Ward, R.C.; Kocher, D.C.; Hicks, B.B.; Hosker, R.P. Jr.; Ku, J.Y.; Rao, K.S.

    1985-01-01

    We have studied the sensitivity of results from the CRAC2 computer code, which predicts health impacts from a reactor-accident scenario, to uncertainties in selected meteorological models and parameters. The sources of uncertainty examined include the models for plume rise and wet deposition and the meteorological bin-sampling procedure. An alternative plume-rise model usually had little effect on predicted health impacts. In an alternative wet-deposition model, the scavenging rate depends only on storm type, rather than on rainfall rate and atmospheric stability class as in the CRAC2 model. Use of the alternative wet-deposition model in meteorological bin-sampling runs decreased predicted mean early injuries by as much as a factor of 2-3 and, for large release heights and sensible heat rates, decreased mean early fatalities by nearly an order of magnitude. The bin-sampling procedure in CRAC2 was expanded by dividing each rain bin into four bins that depend on rainfall rate. Use of the modified bin structure in conjunction with the CRAC2 wet-deposition model changed all predicted health impacts by less than a factor of 2. 9 references

  20. sensitivity analysis on flexible road pavement life cycle cost model

    African Journals Online (AJOL)

    user

    of sensitivity analysis on a developed flexible pavement life cycle cost model using varying discount rate. The study .... organizations and specific projects needs based. Life-cycle ... developed and completed urban road infrastructure corridor ...

  1. Sensitivity analysis technique for application to deterministic models

    International Nuclear Information System (INIS)

    Ishigami, T.; Cazzoli, E.; Khatib-Rahbar, M.; Unwin, S.D.

    1987-01-01

    The characterization of sever accident source terms for light water reactors should include consideration of uncertainties. An important element of any uncertainty analysis is an evaluation of the sensitivity of the output probability distributions reflecting source term uncertainties to assumptions regarding the input probability distributions. Historically, response surface methods (RSMs) were developed to replace physical models using, for example, regression techniques, with simplified models for example, regression techniques, with simplified models for extensive calculations. The purpose of this paper is to present a new method for sensitivity analysis that does not utilize RSM, but instead relies directly on the results obtained from the original computer code calculations. The merits of this approach are demonstrated by application of the proposed method to the suppression pool aerosol removal code (SPARC), and the results are compared with those obtained by sensitivity analysis with (a) the code itself, (b) a regression model, and (c) Iman's method

  2. The GFDL global atmosphere and land model AM4.0/LM4.0: 2. Model description, sensitivity studies, and tuning strategies

    Science.gov (United States)

    Zhao, M.; Golaz, J.-C.; Held, I. M.; Guo, H.; Balaji, V.; Benson, R.; Chen, J.-H.; Chen, X.; Donner, L. J.; Dunne, J. P.; Dunne, Krista A.; Durachta, J.; Fan, S.-M.; Freidenreich, S. M.; Garner, S. T.; Ginoux, P.; Harris, L. M.; Horowitz, L. W.; Krasting, J. P.; Langenhorst, A. R.; Liang, Z.; Lin, P.; Lin, S.-J.; Malyshev, S. L.; Mason, E.; Milly, Paul C.D.; Ming, Y.; Naik, V.; Paulot, F.; Paynter, D.; Phillipps, P.; Radhakrishnan, A.; Ramaswamy, V.; Robinson, T.; Schwarzkopf, D.; Seman, C. J.; Shevliakova, E.; Shen, Z.; Shin, H.; Silvers, L.; Wilson, J. R.; Winton, M.; Wittenberg, A. T.; Wyman, B.; Xiang, B.

    2018-01-01

    In Part 2 of this two‐part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.

  3. The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 2. Model Description, Sensitivity Studies, and Tuning Strategies

    Science.gov (United States)

    Zhao, M.; Golaz, J.-C.; Held, I. M.; Guo, H.; Balaji, V.; Benson, R.; Chen, J.-H.; Chen, X.; Donner, L. J.; Dunne, J. P.; Dunne, K.; Durachta, J.; Fan, S.-M.; Freidenreich, S. M.; Garner, S. T.; Ginoux, P.; Harris, L. M.; Horowitz, L. W.; Krasting, J. P.; Langenhorst, A. R.; Liang, Z.; Lin, P.; Lin, S.-J.; Malyshev, S. L.; Mason, E.; Milly, P. C. D.; Ming, Y.; Naik, V.; Paulot, F.; Paynter, D.; Phillipps, P.; Radhakrishnan, A.; Ramaswamy, V.; Robinson, T.; Schwarzkopf, D.; Seman, C. J.; Shevliakova, E.; Shen, Z.; Shin, H.; Silvers, L. G.; Wilson, J. R.; Winton, M.; Wittenberg, A. T.; Wyman, B.; Xiang, B.

    2018-03-01

    In Part 2 of this two-part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.

  4. Development of a model system to study leukotriene-induced modification of radiation sensitivity in mammalian cells

    Energy Technology Data Exchange (ETDEWEB)

    Walden, Jr, T L; Holahan, Jr, E V; Catravas, G N

    1986-01-01

    Leukotrienes (LT) are an important class of biological mediators for which no information exists concerning their synthesis following a radiation insult or on their ability to modify cellular response to a subsequent radiation exposure. Results are presented which illustrate that the Chinese hamster lung fibroblast cell line, V79A03, is useful as a model system to study the metabolic fate of leukotrienes and the effect of LT on radiation sensitivity of mammalian cells in vitro. (U.K.).

  5. Some Sensitivity Studies of Chemical Transport Simulated in Models of the Soil-Plant-Litter System

    Energy Technology Data Exchange (ETDEWEB)

    Begovich, C.L.

    2002-10-28

    Fifteen parameters in a set of five coupled models describing carbon, water, and chemical dynamics in the soil-plant-litter system were varied in a sensitivity analysis of model response. Results are presented for chemical distribution in the components of soil, plants, and litter along with selected responses of biomass, internal chemical transport (xylem and phloem pathways), and chemical uptake. Response and sensitivity coefficients are presented for up to 102 model outputs in an appendix. Two soil properties (chemical distribution coefficient and chemical solubility) and three plant properties (leaf chemical permeability, cuticle thickness, and root chemical conductivity) had the greatest influence on chemical transport in the soil-plant-litter system under the conditions examined. Pollutant gas uptake (SO{sub 2}) increased with change in plant properties that increased plant growth. Heavy metal dynamics in litter responded to plant properties (phloem resistance, respiration characteristics) which induced changes in the chemical cycling to the litter system. Some of the SO{sub 2} and heavy metal responses were not expected but became apparent through the modeling analysis.

  6. LBLOCA sensitivity analysis using meta models

    International Nuclear Information System (INIS)

    Villamizar, M.; Sanchez-Saez, F.; Villanueva, J.F.; Carlos, S.; Sanchez, A.I.; Martorell, S.

    2014-01-01

    This paper presents an approach to perform the sensitivity analysis of the results of simulation of thermal hydraulic codes within a BEPU approach. Sensitivity analysis is based on the computation of Sobol' indices that makes use of a meta model, It presents also an application to a Large-Break Loss of Coolant Accident, LBLOCA, in the cold leg of a pressurized water reactor, PWR, addressing the results of the BEMUSE program and using the thermal-hydraulic code TRACE. (authors)

  7. Sensitivity study of cloud/radiation interaction using a second order turbulence radiative-convective model

    International Nuclear Information System (INIS)

    Kao, C.Y.J.; Smith, W.S.

    1993-01-01

    A high resolution one-dimensional version of a second order turbulence convective/radiative model, developed at the Los Alamos National Laboratory, was used to conduct a sensitivity study of a stratocumulus cloud deck, based on data taken at San Nicolas Island during the intensive field observation marine stratocumulus phase of the First International Satellite Cloud Climatology Program (ISCCP) Regional Experiment (FIRE IFO), conducted during July, 1987. Initial profiles for liquid water potential temperature, and total water mixing ratio were abstracted from the FIRE data. The dependence of the diurnal behavior in liquid water content, cloud top height, and cloud base height were examined for variations in subsidence rate, sea surface temperature, and initial inversion strength. The modelled diurnal variation in the column integrated liquid water agrees quite well with the observed data, for the case of low subsidence. The modelled diurnal behavior for the height of the cloud top and base show qualitative agreement with the FIRE data, although the overall height of the cloud layer is about 200 meters too high

  8. Bayesian sensitivity analysis of a 1D vascular model with Gaussian process emulators.

    Science.gov (United States)

    Melis, Alessandro; Clayton, Richard H; Marzo, Alberto

    2017-12-01

    One-dimensional models of the cardiovascular system can capture the physics of pulse waves but involve many parameters. Since these may vary among individuals, patient-specific models are difficult to construct. Sensitivity analysis can be used to rank model parameters by their effect on outputs and to quantify how uncertainty in parameters influences output uncertainty. This type of analysis is often conducted with a Monte Carlo method, where large numbers of model runs are used to assess input-output relations. The aim of this study was to demonstrate the computational efficiency of variance-based sensitivity analysis of 1D vascular models using Gaussian process emulators, compared to a standard Monte Carlo approach. The methodology was tested on four vascular networks of increasing complexity to analyse its scalability. The computational time needed to perform the sensitivity analysis with an emulator was reduced by the 99.96% compared to a Monte Carlo approach. Despite the reduced computational time, sensitivity indices obtained using the two approaches were comparable. The scalability study showed that the number of mechanistic simulations needed to train a Gaussian process for sensitivity analysis was of the order O(d), rather than O(d×103) needed for Monte Carlo analysis (where d is the number of parameters in the model). The efficiency of this approach, combined with capacity to estimate the impact of uncertain parameters on model outputs, will enable development of patient-specific models of the vascular system, and has the potential to produce results with clinical relevance. © 2017 The Authors International Journal for Numerical Methods in Biomedical Engineering Published by John Wiley & Sons Ltd.

  9. A Sensitivity Analysis of fMRI Balloon Model

    KAUST Repository

    Zayane, Chadia; Laleg-Kirati, Taous-Meriem

    2015-01-01

    Functional magnetic resonance imaging (fMRI) allows the mapping of the brain activation through measurements of the Blood Oxygenation Level Dependent (BOLD) contrast. The characterization of the pathway from the input stimulus to the output BOLD signal requires the selection of an adequate hemodynamic model and the satisfaction of some specific conditions while conducting the experiment and calibrating the model. This paper, focuses on the identifiability of the Balloon hemodynamic model. By identifiability, we mean the ability to estimate accurately the model parameters given the input and the output measurement. Previous studies of the Balloon model have somehow added knowledge either by choosing prior distributions for the parameters, freezing some of them, or looking for the solution as a projection on a natural basis of some vector space. In these studies, the identification was generally assessed using event-related paradigms. This paper justifies the reasons behind the need of adding knowledge, choosing certain paradigms, and completing the few existing identifiability studies through a global sensitivity analysis of the Balloon model in the case of blocked design experiment.

  10. A Sensitivity Analysis of fMRI Balloon Model

    KAUST Repository

    Zayane, Chadia

    2015-04-22

    Functional magnetic resonance imaging (fMRI) allows the mapping of the brain activation through measurements of the Blood Oxygenation Level Dependent (BOLD) contrast. The characterization of the pathway from the input stimulus to the output BOLD signal requires the selection of an adequate hemodynamic model and the satisfaction of some specific conditions while conducting the experiment and calibrating the model. This paper, focuses on the identifiability of the Balloon hemodynamic model. By identifiability, we mean the ability to estimate accurately the model parameters given the input and the output measurement. Previous studies of the Balloon model have somehow added knowledge either by choosing prior distributions for the parameters, freezing some of them, or looking for the solution as a projection on a natural basis of some vector space. In these studies, the identification was generally assessed using event-related paradigms. This paper justifies the reasons behind the need of adding knowledge, choosing certain paradigms, and completing the few existing identifiability studies through a global sensitivity analysis of the Balloon model in the case of blocked design experiment.

  11. Sensitivity analysis of numerical model of prestressed concrete containment

    Energy Technology Data Exchange (ETDEWEB)

    Bílý, Petr, E-mail: petr.bily@fsv.cvut.cz; Kohoutková, Alena, E-mail: akohout@fsv.cvut.cz

    2015-12-15

    Graphical abstract: - Highlights: • FEM model of prestressed concrete containment with steel liner was created. • Sensitivity analysis of changes in geometry and loads was conducted. • Steel liner and temperature effects are the most important factors. • Creep and shrinkage parameters are essential for the long time analysis. • Prestressing schedule is a key factor in the early stages. - Abstract: Safety is always the main consideration in the design of containment of nuclear power plant. However, efficiency of the design process should be also taken into consideration. Despite the advances in computational abilities in recent years, simplified analyses may be found useful for preliminary scoping or trade studies. In the paper, a study on sensitivity of finite element model of prestressed concrete containment to changes in geometry, loads and other factors is presented. Importance of steel liner, reinforcement, prestressing process, temperature changes, nonlinearity of materials as well as density of finite elements mesh is assessed in the main stages of life cycle of the containment. Although the modeling adjustments have not produced any significant changes in computation time, it was found that in some cases simplified modeling process can lead to significant reduction of work time without degradation of the results.

  12. Sensitivity analysis of infectious disease models: methods, advances and their application

    Science.gov (United States)

    Wu, Jianyong; Dhingra, Radhika; Gambhir, Manoj; Remais, Justin V.

    2013-01-01

    Sensitivity analysis (SA) can aid in identifying influential model parameters and optimizing model structure, yet infectious disease modelling has yet to adopt advanced SA techniques that are capable of providing considerable insights over traditional methods. We investigate five global SA methods—scatter plots, the Morris and Sobol’ methods, Latin hypercube sampling-partial rank correlation coefficient and the sensitivity heat map method—and detail their relative merits and pitfalls when applied to a microparasite (cholera) and macroparasite (schistosomaisis) transmission model. The methods investigated yielded similar results with respect to identifying influential parameters, but offered specific insights that vary by method. The classical methods differed in their ability to provide information on the quantitative relationship between parameters and model output, particularly over time. The heat map approach provides information about the group sensitivity of all model state variables, and the parameter sensitivity spectrum obtained using this method reveals the sensitivity of all state variables to each parameter over the course of the simulation period, especially valuable for expressing the dynamic sensitivity of a microparasite epidemic model to its parameters. A summary comparison is presented to aid infectious disease modellers in selecting appropriate methods, with the goal of improving model performance and design. PMID:23864497

  13. Sensitivity of inferred climate model skill to evaluation decisions: a case study using CMIP5 evapotranspiration

    International Nuclear Information System (INIS)

    Schwalm, Christopher R; Huntinzger, Deborah N; Michalak, Anna M; Fisher, Joshua B; Kimball, John S; Mueller, Brigitte; Zhang, Ke; Zhang Yongqiang

    2013-01-01

    Confrontation of climate models with observationally-based reference datasets is widespread and integral to model development. These comparisons yield skill metrics quantifying the mismatch between simulated and reference values and also involve analyst choices, or meta-parameters, in structuring the analysis. Here, we systematically vary five such meta-parameters (reference dataset, spatial resolution, regridding approach, land mask, and time period) in evaluating evapotranspiration (ET) from eight CMIP5 models in a factorial design that yields 68 700 intercomparisons. The results show that while model–data comparisons can provide some feedback on overall model performance, model ranks are ambiguous and inferred model skill and rank are highly sensitive to the choice of meta-parameters for all models. This suggests that model skill and rank are best represented probabilistically rather than as scalar values. For this case study, the choice of reference dataset is found to have a dominant influence on inferred model skill, even larger than the choice of model itself. This is primarily due to large differences between reference datasets, indicating that further work in developing a community-accepted standard ET reference dataset is crucial in order to decrease ambiguity in model skill. (letter)

  14. Personalization of models with many model parameters : an efficient sensitivity analysis approach

    NARCIS (Netherlands)

    Donders, W.P.; Huberts, W.; van de Vosse, F.N.; Delhaas, T.

    2015-01-01

    Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific applications of models that enhance diagnosis or aid decision-making. Variance-based sensitivity analysis methods, which apportion each fraction of the output uncertainty (variance) to the effects of

  15. Universally sloppy parameter sensitivities in systems biology models.

    Directory of Open Access Journals (Sweden)

    Ryan N Gutenkunst

    2007-10-01

    Full Text Available Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

  16. Universally sloppy parameter sensitivities in systems biology models.

    Science.gov (United States)

    Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

    2007-10-01

    Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

  17. The Coda of the Transient Response in a Sensitive Cochlea: A Computational Modeling Study.

    Directory of Open Access Journals (Sweden)

    Yizeng Li

    2016-07-01

    Full Text Available In a sensitive cochlea, the basilar membrane response to transient excitation of any kind-normal acoustic or artificial intracochlear excitation-consists of not only a primary impulse but also a coda of delayed secondary responses with varying amplitudes but similar spectral content around the characteristic frequency of the measurement location. The coda, sometimes referred to as echoes or ringing, has been described as a form of local, short term memory which may influence the ability of the auditory system to detect gaps in an acoustic stimulus such as speech. Depending on the individual cochlea, the temporal gap between the primary impulse and the following coda ranges from once to thrice the group delay of the primary impulse (the group delay of the primary impulse is on the order of a few hundred microseconds. The coda is physiologically vulnerable, disappearing when the cochlea is compromised even slightly. The multicomponent sensitive response is not yet completely understood. We use a physiologically-based, mathematical model to investigate (i the generation of the primary impulse response and the dependence of the group delay on the various stimulation methods, (ii the effect of spatial perturbations in the properties of mechanically sensitive ion channels on the generation and separation of delayed secondary responses. The model suggests that the presence of the secondary responses depends on the wavenumber content of a perturbation and the activity level of the cochlea. In addition, the model shows that the varying temporal gaps between adjacent coda seen in experiments depend on the individual profiles of perturbations. Implications for non-invasive cochlear diagnosis are also discussed.

  18. Depressive symptoms, insulin sensitivity and insulin secretion in the RISC cohort study

    DEFF Research Database (Denmark)

    Bot, M; Pouwer, F; De Jonge, P

    2013-01-01

    Sensitivity and Cardiovascular Disease Risk (RISC) study. Presence of significant depressive symptoms was defined as a Center for Epidemiologic Studies Depression Scale (CES-D) score ≥ 16. Standard oral glucose tolerance tests were performed. Insulin sensitivity was assessed with the oral glucose insulin......AIM: This study explored the association of depressive symptoms with indices of insulin sensitivity and insulin secretion in a cohort of non-diabetic men and women aged 30 to 64 years. METHODS: The study population was derived from the 3-year follow-up of the Relationship between Insulin...... sensitivity (OGIS) index. Insulin secretion was estimated using three model-based parameters of insulin secretion (beta-cell glucose sensitivity, the potentiation factor ratio, and beta-cell rate sensitivity). RESULTS: A total of 162 out of 1027 participants (16%) had significant depressive symptoms. Having...

  19. Examining Equity Sensitivity: An Investigation Using the Big Five and HEXACO Models of Personality.

    Science.gov (United States)

    Woodley, Hayden J R; Bourdage, Joshua S; Ogunfowora, Babatunde; Nguyen, Brenda

    2015-01-01

    The construct of equity sensitivity describes an individual's preference about his/her desired input to outcome ratio. Individuals high on equity sensitivity tend to be more input oriented, and are often called "Benevolents." Individuals low on equity sensitivity are more outcome oriented, and are described as "Entitleds." Given that equity sensitivity has often been described as a trait, the purpose of the present study was to examine major personality correlates of equity sensitivity, so as to inform both the nature of equity sensitivity, and the potential processes through which certain broad personality traits may relate to outcomes. We examined the personality correlates of equity sensitivity across three studies (total N = 1170), two personality models (i.e., the Big Five and HEXACO), the two most common measures of equity sensitivity (i.e., the Equity Preference Questionnaire and Equity Sensitivity Inventory), and using both self and peer reports of personality (in Study 3). Although results varied somewhat across samples, the personality variables of Conscientiousness and Honesty-Humility, followed by Agreeableness, were the most robust predictors of equity sensitivity. Individuals higher on these traits were more likely to be Benevolents, whereas those lower on these traits were more likely to be Entitleds. Although some associations between Extraversion, Openness, and Neuroticism and equity sensitivity were observed, these were generally not robust. Overall, it appears that there are several prominent personality variables underlying equity sensitivity, and that the addition of the HEXACO model's dimension of Honesty-Humility substantially contributes to our understanding of equity sensitivity.

  20. Examining Equity Sensitivity: An Investigation Using the Big Five and HEXACO Models of Personality

    Science.gov (United States)

    Woodley, Hayden J. R.; Bourdage, Joshua S.; Ogunfowora, Babatunde; Nguyen, Brenda

    2016-01-01

    The construct of equity sensitivity describes an individual's preference about his/her desired input to outcome ratio. Individuals high on equity sensitivity tend to be more input oriented, and are often called “Benevolents.” Individuals low on equity sensitivity are more outcome oriented, and are described as “Entitleds.” Given that equity sensitivity has often been described as a trait, the purpose of the present study was to examine major personality correlates of equity sensitivity, so as to inform both the nature of equity sensitivity, and the potential processes through which certain broad personality traits may relate to outcomes. We examined the personality correlates of equity sensitivity across three studies (total N = 1170), two personality models (i.e., the Big Five and HEXACO), the two most common measures of equity sensitivity (i.e., the Equity Preference Questionnaire and Equity Sensitivity Inventory), and using both self and peer reports of personality (in Study 3). Although results varied somewhat across samples, the personality variables of Conscientiousness and Honesty-Humility, followed by Agreeableness, were the most robust predictors of equity sensitivity. Individuals higher on these traits were more likely to be Benevolents, whereas those lower on these traits were more likely to be Entitleds. Although some associations between Extraversion, Openness, and Neuroticism and equity sensitivity were observed, these were generally not robust. Overall, it appears that there are several prominent personality variables underlying equity sensitivity, and that the addition of the HEXACO model's dimension of Honesty-Humility substantially contributes to our understanding of equity sensitivity. PMID:26779102

  1. ATLAS MDT neutron sensitivity measurement and modeling

    International Nuclear Information System (INIS)

    Ahlen, S.; Hu, G.; Osborne, D.; Schulz, A.; Shank, J.; Xu, Q.; Zhou, B.

    2003-01-01

    The sensitivity of the ATLAS precision muon detector element, the Monitored Drift Tube (MDT), to fast neutrons has been measured using a 5.5 MeV Van de Graaff accelerator. The major mechanism of neutron-induced signals in the drift tubes is the elastic collisions between the neutrons and the gas nuclei. The recoil nuclei lose kinetic energy in the gas and produce the signals. By measuring the ATLAS drift tube neutron-induced signal rate and the total neutron flux, the MDT neutron signal sensitivities were determined for different drift gas mixtures and for different neutron beam energies. We also developed a sophisticated simulation model to calculate the neutron-induced signal rate and signal spectrum for ATLAS MDT operation configurations. The calculations agree with the measurements very well. This model can be used to calculate the neutron sensitivities for different gaseous detectors and for neutron energies above those available to this experiment

  2. Global sensitivity and uncertainty analysis of an atmospheric chemistry transport model: the FRAME model (version 9.15.0) as a case study

    Science.gov (United States)

    Aleksankina, Ksenia; Heal, Mathew R.; Dore, Anthony J.; Van Oijen, Marcel; Reis, Stefan

    2018-04-01

    Atmospheric chemistry transport models (ACTMs) are widely used to underpin policy decisions associated with the impact of potential changes in emissions on future pollutant concentrations and deposition. It is therefore essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input pollutant emissions. ACTMs incorporate complex and non-linear descriptions of chemical and physical processes which means that interactions and non-linearities in input-output relationships may not be revealed through the local one-at-a-time sensitivity analysis typically used. The aim of this work is to demonstrate a global sensitivity and uncertainty analysis approach for an ACTM, using as an example the FRAME model, which is extensively employed in the UK to generate source-receptor matrices for the UK Integrated Assessment Model and to estimate critical load exceedances. An optimised Latin hypercube sampling design was used to construct model runs within ±40 % variation range for the UK emissions of SO2, NOx, and NH3, from which regression coefficients for each input-output combination and each model grid ( > 10 000 across the UK) were calculated. Surface concentrations of SO2, NOx, and NH3 (and of deposition of S and N) were found to be predominantly sensitive to the emissions of the respective pollutant, while sensitivities of secondary species such as HNO3 and particulate SO42-, NO3-, and NH4+ to pollutant emissions were more complex and geographically variable. The uncertainties in model output variables were propagated from the uncertainty ranges reported by the UK National Atmospheric Emissions Inventory for the emissions of SO2, NOx, and NH3 (±4, ±10, and ±20 % respectively). The uncertainties in the surface concentrations of NH3 and NOx and the depositions of NHx and NOy were dominated by the uncertainties in emissions of NH3, and NOx respectively, whilst concentrations of SO2 and deposition of SOy were affected

  3. Environmental Impacts of a Multi-Borehole Geothermal System: Model Sensitivity Study

    Science.gov (United States)

    Krol, M.; Daemi, N.

    2017-12-01

    Problems associated with fossil fuel consumption has increased worldwide interest in discovering and developing sustainable energy systems. One such system is geothermal heating, which uses the constant temperature of the ground to heat or cool buildings. Since geothermal heating offers low maintenance, high heating/cooling comfort, and a low carbon footprint, compared to conventional systems, there has been an increasing trend in equipping large buildings with geothermal heating. However, little is known on the potential environmental impact geothermal heating can have on the subsurface, such as the creation of subsurface thermal plumes or changes in groundwater flow dynamics. In the present study, the environmental impacts of a closed-loop, ground source heat pump (GSHP) system was examined with respect to different system parameters. To do this a three-dimensional model, developed using FEFLOW, was used to examine the thermal plumes resulting from ten years of operation of a vertical closed-loop GSHP system with multiple boreholes. A required thermal load typical of an office building located in Canada was calculated and groundwater flow and heat transport in the geological formation was simulated. Consequently, the resulting thermal plumes were studied and a sensitivity analysis was conducted to determine the effect of different parameters like groundwater flow and soil type on the development and movement of thermal plumes. Since thermal plumes can affect the efficiency of a GSHP system, this study provides insight into important system parameters.

  4. Multivariate Models for Prediction of Human Skin Sensitization Hazard

    Science.gov (United States)

    Strickland, Judy; Zang, Qingda; Paris, Michael; Lehmann, David M.; Allen, David; Choksi, Neepa; Matheson, Joanna; Jacobs, Abigail; Casey, Warren; Kleinstreuer, Nicole

    2016-01-01

    One of ICCVAM’s top priorities is the development and evaluation of non-animal approaches to identify potential skin sensitizers. The complexity of biological events necessary to produce skin sensitization suggests that no single alternative method will replace the currently accepted animal tests. ICCVAM is evaluating an integrated approach to testing and assessment based on the adverse outcome pathway for skin sensitization that uses machine learning approaches to predict human skin sensitization hazard. We combined data from three in chemico or in vitro assays—the direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT), and KeratinoSens™ assay—six physicochemical properties, and an in silico read-across prediction of skin sensitization hazard into 12 variable groups. The variable groups were evaluated using two machine learning approaches, logistic regression (LR) and support vector machine (SVM), to predict human skin sensitization hazard. Models were trained on 72 substances and tested on an external set of 24 substances. The six models (three LR and three SVM) with the highest accuracy (92%) used: (1) DPRA, h-CLAT, and read-across; (2) DPRA, h-CLAT, read-across, and KeratinoSens; or (3) DPRA, h-CLAT, read-across, KeratinoSens, and log P. The models performed better at predicting human skin sensitization hazard than the murine local lymph node assay (accuracy = 88%), any of the alternative methods alone (accuracy = 63–79%), or test batteries combining data from the individual methods (accuracy = 75%). These results suggest that computational methods are promising tools to effectively identify potential human skin sensitizers without animal testing. PMID:27480324

  5. Sensitivity Analysis of a Simplified Fire Dynamic Model

    DEFF Research Database (Denmark)

    Sørensen, Lars Schiøtt; Nielsen, Anker

    2015-01-01

    This paper discusses a method for performing a sensitivity analysis of parameters used in a simplified fire model for temperature estimates in the upper smoke layer during a fire. The results from the sensitivity analysis can be used when individual parameters affecting fire safety are assessed...

  6. Sensitivity of hydrological performance assessment analysis to variations in material properties, conceptual models, and ventilation models

    Energy Technology Data Exchange (ETDEWEB)

    Sobolik, S.R.; Ho, C.K.; Dunn, E. [Sandia National Labs., Albuquerque, NM (United States); Robey, T.H. [Spectra Research Inst., Albuquerque, NM (United States); Cruz, W.T. [Univ. del Turabo, Gurabo (Puerto Rico)

    1996-07-01

    The Yucca Mountain Site Characterization Project is studying Yucca Mountain in southwestern Nevada as a potential site for a high-level nuclear waste repository. Site characterization includes surface- based and underground testing. Analyses have been performed to support the design of an Exploratory Studies Facility (ESF) and the design of the tests performed as part of the characterization process, in order to ascertain that they have minimal impact on the natural ability of the site to isolate waste. The information in this report pertains to sensitivity studies evaluating previous hydrological performance assessment analyses to variation in the material properties, conceptual models, and ventilation models, and the implications of this sensitivity on previous recommendations supporting ESF design. This document contains information that has been used in preparing recommendations for Appendix I of the Exploratory Studies Facility Design Requirements document.

  7. Sensitivity of hydrological performance assessment analysis to variations in material properties, conceptual models, and ventilation models

    International Nuclear Information System (INIS)

    Sobolik, S.R.; Ho, C.K.; Dunn, E.; Robey, T.H.; Cruz, W.T.

    1996-07-01

    The Yucca Mountain Site Characterization Project is studying Yucca Mountain in southwestern Nevada as a potential site for a high-level nuclear waste repository. Site characterization includes surface- based and underground testing. Analyses have been performed to support the design of an Exploratory Studies Facility (ESF) and the design of the tests performed as part of the characterization process, in order to ascertain that they have minimal impact on the natural ability of the site to isolate waste. The information in this report pertains to sensitivity studies evaluating previous hydrological performance assessment analyses to variation in the material properties, conceptual models, and ventilation models, and the implications of this sensitivity on previous recommendations supporting ESF design. This document contains information that has been used in preparing recommendations for Appendix I of the Exploratory Studies Facility Design Requirements document

  8. A New Computationally Frugal Method For Sensitivity Analysis Of Environmental Models

    Science.gov (United States)

    Rakovec, O.; Hill, M. C.; Clark, M. P.; Weerts, A.; Teuling, R.; Borgonovo, E.; Uijlenhoet, R.

    2013-12-01

    Effective and efficient parameter sensitivity analysis methods are crucial to understand the behaviour of complex environmental models and use of models in risk assessment. This paper proposes a new computationally frugal method for analyzing parameter sensitivity: the Distributed Evaluation of Local Sensitivity Analysis (DELSA). The DELSA method can be considered a hybrid of local and global methods, and focuses explicitly on multiscale evaluation of parameter sensitivity across the parameter space. Results of the DELSA method are compared with the popular global, variance-based Sobol' method and the delta method. We assess the parameter sensitivity of both (1) a simple non-linear reservoir model with only two parameters, and (2) five different "bucket-style" hydrologic models applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both the synthetic and real-world examples, the global Sobol' method and the DELSA method provide similar sensitivities, with the DELSA method providing more detailed insight at much lower computational cost. The ability to understand how sensitivity measures vary through parameter space with modest computational requirements provides exciting new opportunities.

  9. Sensitivity of tsunami evacuation modeling to direction and land cover assumptions

    Science.gov (United States)

    Schmidtlein, Mathew C.; Wood, Nathan J.

    2015-01-01

    Although anisotropic least-cost-distance (LCD) modeling is becoming a common tool for estimating pedestrian-evacuation travel times out of tsunami hazard zones, there has been insufficient attention paid to understanding model sensitivity behind the estimates. To support tsunami risk-reduction planning, we explore two aspects of LCD modeling as it applies to pedestrian evacuations and use the coastal community of Seward, Alaska, as our case study. First, we explore the sensitivity of modeling to the direction of movement by comparing standard safety-to-hazard evacuation times to hazard-to-safety evacuation times for a sample of 3985 points in Seward's tsunami-hazard zone. Safety-to-hazard evacuation times slightly overestimated hazard-to-safety evacuation times but the strong relationship to the hazard-to-safety evacuation times, slightly conservative bias, and shorter processing times of the safety-to-hazard approach make it the preferred approach. Second, we explore how variations in land cover speed conservation values (SCVs) influence model performance using a Monte Carlo approach with one thousand sets of land cover SCVs. The LCD model was relatively robust to changes in land cover SCVs with the magnitude of local model sensitivity greatest in areas with higher evacuation times or with wetland or shore land cover types, where model results may slightly underestimate travel times. This study demonstrates that emergency managers should be concerned not only with populations in locations with evacuation times greater than wave arrival times, but also with populations with evacuation times lower than but close to expected wave arrival times, particularly if they are required to cross wetlands or beaches.

  10. Sensitivity analysis of complex models: Coping with dynamic and static inputs

    International Nuclear Information System (INIS)

    Anstett-Collin, F.; Goffart, J.; Mara, T.; Denis-Vidal, L.

    2015-01-01

    In this paper, we address the issue of conducting a sensitivity analysis of complex models with both static and dynamic uncertain inputs. While several approaches have been proposed to compute the sensitivity indices of the static inputs (i.e. parameters), the one of the dynamic inputs (i.e. stochastic fields) have been rarely addressed. For this purpose, we first treat each dynamic as a Gaussian process. Then, the truncated Karhunen–Loève expansion of each dynamic input is performed. Such an expansion allows to generate independent Gaussian processes from a finite number of independent random variables. Given that a dynamic input is represented by a finite number of random variables, its variance-based sensitivity index is defined by the sensitivity index of this group of variables. Besides, an efficient sampling-based strategy is described to estimate the first-order indices of all the input factors by only using two input samples. The approach is applied to a building energy model, in order to assess the impact of the uncertainties of the material properties (static inputs) and the weather data (dynamic inputs) on the energy performance of a real low energy consumption house. - Highlights: • Sensitivity analysis of models with uncertain static and dynamic inputs is performed. • Karhunen–Loève (KL) decomposition of the spatio/temporal inputs is performed. • The influence of the dynamic inputs is studied through the modes of the KL expansion. • The proposed approach is applied to a building energy model. • Impact of weather data and material properties on performance of real house is given

  11. Sensitivity of subject-specific models to errors in musculo-skeletal geometry.

    Science.gov (United States)

    Carbone, V; van der Krogt, M M; Koopman, H F J M; Verdonschot, N

    2012-09-21

    Subject-specific musculo-skeletal models of the lower extremity are an important tool for investigating various biomechanical problems, for instance the results of surgery such as joint replacements and tendon transfers. The aim of this study was to assess the potential effects of errors in musculo-skeletal geometry on subject-specific model results. We performed an extensive sensitivity analysis to quantify the effect of the perturbation of origin, insertion and via points of each of the 56 musculo-tendon parts contained in the model. We used two metrics, namely a Local Sensitivity Index (LSI) and an Overall Sensitivity Index (OSI), to distinguish the effect of the perturbation on the predicted force produced by only the perturbed musculo-tendon parts and by all the remaining musculo-tendon parts, respectively, during a simulated gait cycle. Results indicated that, for each musculo-tendon part, only two points show a significant sensitivity: its origin, or pseudo-origin, point and its insertion, or pseudo-insertion, point. The most sensitive points belong to those musculo-tendon parts that act as prime movers in the walking movement (insertion point of the Achilles Tendon: LSI=15.56%, OSI=7.17%; origin points of the Rectus Femoris: LSI=13.89%, OSI=2.44%) and as hip stabilizers (insertion points of the Gluteus Medius Anterior: LSI=17.92%, OSI=2.79%; insertion point of the Gluteus Minimus: LSI=21.71%, OSI=2.41%). The proposed priority list provides quantitative information to improve the predictive accuracy of subject-specific musculo-skeletal models. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Precipitates/Salts Model Sensitivity Calculation

    International Nuclear Information System (INIS)

    Mariner, P.

    2001-01-01

    The objective and scope of this calculation is to assist Performance Assessment Operations and the Engineered Barrier System (EBS) Department in modeling the geochemical effects of evaporation on potential seepage waters within a potential repository drift. This work is developed and documented using procedure AP-3.12Q, ''Calculations'', in support of ''Technical Work Plan For Engineered Barrier System Department Modeling and Testing FY 02 Work Activities'' (BSC 2001a). The specific objective of this calculation is to examine the sensitivity and uncertainties of the Precipitates/Salts model. The Precipitates/Salts model is documented in an Analysis/Model Report (AMR), ''In-Drift Precipitates/Salts Analysis'' (BSC 2001b). The calculation in the current document examines the effects of starting water composition, mineral suppressions, and the fugacity of carbon dioxide (CO 2 ) on the chemical evolution of water in the drift

  13. Monte Carlo sensitivity analysis of an Eulerian large-scale air pollution model

    International Nuclear Information System (INIS)

    Dimov, I.; Georgieva, R.; Ostromsky, Tz.

    2012-01-01

    Variance-based approaches for global sensitivity analysis have been applied and analyzed to study the sensitivity of air pollutant concentrations according to variations of rates of chemical reactions. The Unified Danish Eulerian Model has been used as a mathematical model simulating a remote transport of air pollutants. Various Monte Carlo algorithms for numerical integration have been applied to compute Sobol's global sensitivity indices. A newly developed Monte Carlo algorithm based on Sobol's quasi-random points MCA-MSS has been applied for numerical integration. It has been compared with some existing approaches, namely Sobol's ΛΠ τ sequences, an adaptive Monte Carlo algorithm, the plain Monte Carlo algorithm, as well as, eFAST and Sobol's sensitivity approaches both implemented in SIMLAB software. The analysis and numerical results show advantages of MCA-MSS for relatively small sensitivity indices in terms of accuracy and efficiency. Practical guidelines on the estimation of Sobol's global sensitivity indices in the presence of computational difficulties have been provided. - Highlights: ► Variance-based global sensitivity analysis is performed for the air pollution model UNI-DEM. ► The main effect of input parameters dominates over higher-order interactions. ► Ozone concentrations are influenced mostly by variability of three chemical reactions rates. ► The newly developed MCA-MSS for multidimensional integration is compared with other approaches. ► More precise approaches like MCA-MSS should be applied when the needed accuracy has not been achieved.

  14. Supplementary Material for: A global sensitivity analysis approach for morphogenesis models

    KAUST Repository

    Boas, Sonja; Navarro, Marí a; Merks, Roeland; Blom, Joke

    2015-01-01

    ) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided

  15. Sensitivity study of tensions in distribution networks with respect to injected powers

    International Nuclear Information System (INIS)

    Tencio Alfaro, Ernie Fernando

    2013-01-01

    A study of the sensitivity of tension is submitted to small changes of active and reactive power of distributed generators (DG) of a 11 kV radial system of 8 circuits with 75 rods, in which 22 bars with DG and 38 bars with loads. The sensitivities are obtained for 6 load models 3 relations R / X of the lines interconnecting the distributed system, 3 equivalents of Thevenin and high load conditions with low generation and low load with high part of the DG and bars load. The study has obtained to determine which operating conditions of the system have presented the greatest tension sensitivities. A description of the theory of modeling loads and motor is developed for electrical power systems. The several ways to obtain the sensitivity matrix of tension are explained as central axis. (author) [es

  16. Sensitivity analysis of Repast computational ecology models with R/Repast.

    Science.gov (United States)

    Prestes García, Antonio; Rodríguez-Patón, Alfonso

    2016-12-01

    Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities, or populations due to individual variability. In addition, being a bottom-up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course, no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in-silico experimental setup. In this article, we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results.

  17. QSAR Study of Skin Sensitization Using Local Lymph Node Assay Data

    Directory of Open Access Journals (Sweden)

    Eugene Demchuk

    2004-01-01

    Full Text Available Abstract: Allergic Contact Dermatitis (ACD is a common work-related skin disease that often develops as a result of repetitive skin exposures to a sensitizing chemical agent. A variety of experimental tests have been suggested to assess the skin sensitization potential. We applied a method of Quantitative Structure-Activity Relationship (QSAR to relate measured and calculated physical-chemical properties of chemical compounds to their sensitization potential. Using statistical methods, each of these properties, called molecular descriptors, was tested for its propensity to predict the sensitization potential. A few of the most informative descriptors were subsequently selected to build a model of skin sensitization. In this work sensitization data for the murine Local Lymph Node Assay (LLNA were used. In principle, LLNA provides a standardized continuous scale suitable for quantitative assessment of skin sensitization. However, at present many LLNA results are still reported on a dichotomous scale, which is consistent with the scale of guinea pig tests, which were widely used in past years. Therefore, in this study only a dichotomous version of the LLNA data was used. To the statistical end, we relied on the logistic regression approach. This approach provides a statistical tool for investigating and predicting skin sensitization that is expressed only in categorical terms of activity and nonactivity. Based on the data of compounds used in this study, our results suggest a QSAR model of ACD that is based on the following descriptors: nDB (number of double bonds, C-003 (number of CHR3 molecular subfragments, GATS6M (autocorrelation coefficient and HATS6m (GETAWAY descriptor, although the relevance of the identified descriptors to the continuous ACD QSAR has yet to be shown. The proposed QSAR model gives a percentage of positively predicted responses of 83% on the training set of compounds, and in cross validation it correctly identifies 79% of

  18. Demonstration uncertainty/sensitivity analysis using the health and economic consequence model CRAC2

    International Nuclear Information System (INIS)

    Alpert, D.J.; Iman, R.L.; Johnson, J.D.; Helton, J.C.

    1985-01-01

    This paper summarizes a demonstration uncertainty/sensitivity analysis performed on the reactor accident consequence model CRAC2. The study was performed with uncertainty/sensitivity analysis techniques compiled as part of the MELCOR program. The principal objectives of the study were: 1) to demonstrate the use of the uncertainty/sensitivity analysis techniques on a health and economic consequence model, 2) to test the computer models which implement the techniques, 3) to identify possible difficulties in performing such an analysis, and 4) to explore alternative means of analyzing, displaying, and describing the results. Demonstration of the applicability of the techniques was the motivation for performing this study; thus, the results should not be taken as a definitive uncertainty analysis of health and economic consequences. Nevertheless, significant insights on health and economic consequence analysis can be drawn from the results of this type of study. Latin hypercube sampling (LHS), a modified Monte Carlo technique, was used in this study. LHS generates a multivariate input structure in which all the variables of interest are varied simultaneously and desired correlations between variables are preserved. LHS has been shown to produce estimates of output distribution functions that are comparable with results of larger random samples

  19. INFERENCE AND SENSITIVITY IN STOCHASTIC WIND POWER FORECAST MODELS.

    KAUST Repository

    Elkantassi, Soumaya

    2017-10-03

    Reliable forecasting of wind power generation is crucial to optimal control of costs in generation of electricity with respect to the electricity demand. Here, we propose and analyze stochastic wind power forecast models described by parametrized stochastic differential equations, which introduce appropriate fluctuations in numerical forecast outputs. We use an approximate maximum likelihood method to infer the model parameters taking into account the time correlated sets of data. Furthermore, we study the validity and sensitivity of the parameters for each model. We applied our models to Uruguayan wind power production as determined by historical data and corresponding numerical forecasts for the period of March 1 to May 31, 2016.

  20. INFERENCE AND SENSITIVITY IN STOCHASTIC WIND POWER FORECAST MODELS.

    KAUST Repository

    Elkantassi, Soumaya; Kalligiannaki, Evangelia; Tempone, Raul

    2017-01-01

    Reliable forecasting of wind power generation is crucial to optimal control of costs in generation of electricity with respect to the electricity demand. Here, we propose and analyze stochastic wind power forecast models described by parametrized stochastic differential equations, which introduce appropriate fluctuations in numerical forecast outputs. We use an approximate maximum likelihood method to infer the model parameters taking into account the time correlated sets of data. Furthermore, we study the validity and sensitivity of the parameters for each model. We applied our models to Uruguayan wind power production as determined by historical data and corresponding numerical forecasts for the period of March 1 to May 31, 2016.

  1. In silico modeling predicts drug sensitivity of patient-derived cancer cells.

    Science.gov (United States)

    Pingle, Sandeep C; Sultana, Zeba; Pastorino, Sandra; Jiang, Pengfei; Mukthavaram, Rajesh; Chao, Ying; Bharati, Ila Sri; Nomura, Natsuko; Makale, Milan; Abbasi, Taher; Kapoor, Shweta; Kumar, Ansu; Usmani, Shahabuddin; Agrawal, Ashish; Vali, Shireen; Kesari, Santosh

    2014-05-21

    Glioblastoma (GBM) is an aggressive disease associated with poor survival. It is essential to account for the complexity of GBM biology to improve diagnostic and therapeutic strategies. This complexity is best represented by the increasing amounts of profiling ("omics") data available due to advances in biotechnology. The challenge of integrating these vast genomic and proteomic data can be addressed by a comprehensive systems modeling approach. Here, we present an in silico model, where we simulate GBM tumor cells using genomic profiling data. We use this in silico tumor model to predict responses of cancer cells to targeted drugs. Initially, we probed the results from a recent hypothesis-independent, empirical study by Garnett and co-workers that analyzed the sensitivity of hundreds of profiled cancer cell lines to 130 different anticancer agents. We then used the tumor model to predict sensitivity of patient-derived GBM cell lines to different targeted therapeutic agents. Among the drug-mutation associations reported in the Garnett study, our in silico model accurately predicted ~85% of the associations. While testing the model in a prospective manner using simulations of patient-derived GBM cell lines, we compared our simulation predictions with experimental data using the same cells in vitro. This analysis yielded a ~75% agreement of in silico drug sensitivity with in vitro experimental findings. These results demonstrate a strong predictability of our simulation approach using the in silico tumor model presented here. Our ultimate goal is to use this model to stratify patients for clinical trials. By accurately predicting responses of cancer cells to targeted agents a priori, this in silico tumor model provides an innovative approach to personalizing therapy and promises to improve clinical management of cancer.

  2. Modelling of intermittent microwave convective drying: parameter sensitivity

    Directory of Open Access Journals (Sweden)

    Zhang Zhijun

    2017-06-01

    Full Text Available The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.

  3. Sensitivity analysis of an Advanced Gas-cooled Reactor control rod model

    International Nuclear Information System (INIS)

    Scott, M.; Green, P.L.; O’Driscoll, D.; Worden, K.; Sims, N.D.

    2016-01-01

    Highlights: • A model was made of the AGR control rod mechanism. • The aim was to better understand the performance when shutting down the reactor. • The model showed good agreement with test data. • Sensitivity analysis was carried out. • The results demonstrated the robustness of the system. - Abstract: A model has been made of the primary shutdown system of an Advanced Gas-cooled Reactor nuclear power station. The aim of this paper is to explore the use of sensitivity analysis techniques on this model. The two motivations for performing sensitivity analysis are to quantify how much individual uncertain parameters are responsible for the model output uncertainty, and to make predictions about what could happen if one or several parameters were to change. Global sensitivity analysis techniques were used based on Gaussian process emulation; the software package GEM-SA was used to calculate the main effects, the main effect index and the total sensitivity index for each parameter and these were compared to local sensitivity analysis results. The results suggest that the system performance is resistant to adverse changes in several parameters at once.

  4. Sensitivity of Greenland Ice Sheet surface mass balance to surface albedo parameterization: a study with a regional climate model

    OpenAIRE

    Angelen, J. H.; Lenaerts, J. T. M.; Lhermitte, S.; Fettweis, X.; Kuipers Munneke, P.; Broeke, M. R.; Meijgaard, E.; Smeets, C. J. P. P.

    2012-01-01

    We present a sensitivity study of the surface mass balance (SMB) of the Greenland Ice Sheet, as modeled using a regional atmospheric climate model, to various parameter settings in the albedo scheme. The snow albedo scheme uses grain size as a prognostic variable and further depends on cloud cover, solar zenith angle and black carbon concentration. For the control experiment the overestimation of absorbed shortwave radiation (+6%) at the K-transect (west Greenland) for the period 2004–2009 is...

  5. Implementation and evaluation of nonparametric regression procedures for sensitivity analysis of computationally demanding models

    International Nuclear Information System (INIS)

    Storlie, Curtis B.; Swiler, Laura P.; Helton, Jon C.; Sallaberry, Cedric J.

    2009-01-01

    The analysis of many physical and engineering problems involves running complex computational models (simulation models, computer codes). With problems of this type, it is important to understand the relationships between the input variables (whose values are often imprecisely known) and the output. The goal of sensitivity analysis (SA) is to study this relationship and identify the most significant factors or variables affecting the results of the model. In this presentation, an improvement on existing methods for SA of complex computer models is described for use when the model is too computationally expensive for a standard Monte-Carlo analysis. In these situations, a meta-model or surrogate model can be used to estimate the necessary sensitivity index for each input. A sensitivity index is a measure of the variance in the response that is due to the uncertainty in an input. Most existing approaches to this problem either do not work well with a large number of input variables and/or they ignore the error involved in estimating a sensitivity index. Here, a new approach to sensitivity index estimation using meta-models and bootstrap confidence intervals is described that provides solutions to these drawbacks. Further, an efficient yet effective approach to incorporate this methodology into an actual SA is presented. Several simulated and real examples illustrate the utility of this approach. This framework can be extended to uncertainty analysis as well.

  6. Rainfall-induced fecal indicator organisms transport from manured fields: model sensitivity analysis.

    Science.gov (United States)

    Martinez, Gonzalo; Pachepsky, Yakov A; Whelan, Gene; Yakirevich, Alexander M; Guber, Andrey; Gish, Timothy J

    2014-02-01

    Microbial quality of surface waters attracts attention due to food- and waterborne disease outbreaks. Fecal indicator organisms (FIOs) are commonly used for the microbial pollution level evaluation. Models predicting the fate and transport of FIOs are required to design and evaluate best management practices that reduce the microbial pollution in ecosystems and water sources and thus help to predict the risk of food and waterborne diseases. In this study we performed a sensitivity analysis for the KINEROS/STWIR model developed to predict the FIOs transport out of manured fields to other fields and water bodies in order to identify input variables that control the transport uncertainty. The distributions of model input parameters were set to encompass values found from three-year experiments at the USDA-ARS OPE3 experimental site in Beltsville and publicly available information. Sobol' indices and complementary regression trees were used to perform the global sensitivity analysis of the model and to explore the interactions between model input parameters on the proportion of FIO removed from fields. Regression trees provided a useful visualization of the differences in sensitivity of the model output in different parts of the input variable domain. Environmental controls such as soil saturation, rainfall duration and rainfall intensity had the largest influence in the model behavior, whereas soil and manure properties ranked lower. The field length had only moderate effect on the model output sensitivity to the model inputs. Among the manure-related properties the parameter determining the shape of the FIO release kinetic curve had the largest influence on the removal of FIOs from the fields. That underscored the need to better characterize the FIO release kinetics. Since the most sensitive model inputs are available in soil and weather databases or can be obtained using soil water models, results indicate the opportunity of obtaining large-scale estimates of FIO

  7. Sensitivity and uncertainty analysis of the PATHWAY radionuclide transport model

    International Nuclear Information System (INIS)

    Otis, M.D.

    1983-01-01

    Procedures were developed for the uncertainty and sensitivity analysis of a dynamic model of radionuclide transport through human food chains. Uncertainty in model predictions was estimated by propagation of parameter uncertainties using a Monte Carlo simulation technique. Sensitivity of model predictions to individual parameters was investigated using the partial correlation coefficient of each parameter with model output. Random values produced for the uncertainty analysis were used in the correlation analysis for sensitivity. These procedures were applied to the PATHWAY model which predicts concentrations of radionuclides in foods grown in Nevada and Utah and exposed to fallout during the period of atmospheric nuclear weapons testing in Nevada. Concentrations and time-integrated concentrations of iodine-131, cesium-136, and cesium-137 in milk and other foods were investigated. 9 figs., 13 tabs

  8. Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

    Science.gov (United States)

    Aires, Filipe; Rossow, William B.; Hansen, James E. (Technical Monitor)

    2001-01-01

    A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

  9. Sensitivity of using blunt and sharp crack models in elastic-plastic fracture mechanics

    International Nuclear Information System (INIS)

    Pan, Y.C.; Kennedy, J.M.; Marchertas, A.H.

    1985-01-01

    J-integral values are calculated for both the blunt (smeared) crack and the sharp (discrete) crack models in elastic-plastic fracture mechanics problems involving metallic materials. A sensitivity study is performed to show the relative strengths and weaknesses of the two cracking models. It is concluded that the blunt crack model is less dependent on the orientation of the mesh. For the mesh which is in line with the crack direction, however, the sharp crack model is less sensitive to the mesh size. Both models yield reasonable results for a properly discretized finite-element mesh. A subcycling technique is used in this study in the explicit integration scheme so that large time steps can be used for the coarse elements away from the crack tip. The savings of computation time by this technique are reported. 6 refs., 9 figs

  10. The sensitivity of the ESA DELTA model

    Science.gov (United States)

    Martin, C.; Walker, R.; Klinkrad, H.

    Long-term debris environment models play a vital role in furthering our understanding of the future debris environment, and in aiding the determination of a strategy to preserve the Earth orbital environment for future use. By their very nature these models have to make certain assumptions to enable informative future projections to be made. Examples of these assumptions include the projection of future traffic, including launch and explosion rates, and the methodology used to simulate break-up events. To ensure a sound basis for future projections, and consequently for assessing the effectiveness of various mitigation measures, it is essential that the sensitivity of these models to variations in key assumptions is examined. The DELTA (Debris Environment Long Term Analysis) model, developed by QinetiQ for the European Space Agency, allows the future projection of the debris environment throughout Earth orbit. Extensive analyses with this model have been performed under the auspices of the ESA Space Debris Mitigation Handbook and following the recent upgrade of the model to DELTA 3.0. This paper draws on these analyses to present the sensitivity of the DELTA model to changes in key model parameters and assumptions. Specifically the paper will address the variation in future traffic rates, including the deployment of satellite constellations, and the variation in the break-up model and criteria used to simulate future explosion and collision events.

  11. Sensitivity Studies on the Influence of Aerosols on Cloud and Precipitation Development Using WRF Mesoscale Model Simulations

    Science.gov (United States)

    Thompson, G.; Eidhammer, T.; Rasmussen, R.

    2011-12-01

    Using the WRF model in simulations of shallow and deep precipitating cloud systems, we investigated the sensitivity to aerosols initiating as cloud condensation and ice nuclei. A global climatological dataset of sulfates, sea salts, and dust was used as input for a control experiment. Sensitivity experiments with significantly more polluted conditions were conducted to analyze the resulting impacts to cloud and precipitation formation. Simulations were performed using the WRF model with explicit treatment of aerosols added to the Thompson et al (2008) bulk microphysics scheme. The modified scheme achieves droplet formation using pre-tabulated CCN activation tables provided by a parcel model. The ice nucleation is parameterized as a function of dust aerosols as well as homogeneous freezing of deliquesced aerosols. The basic processes of aerosol activation and removal by wet scavenging are considered, but aerosol characteristic size or hygroscopicity does not change due to evaporating droplets. In other words, aerosol processing was ignored. Unique aspects of this study include the usage of one to four kilometer grid spacings and the direct parameterization of ice nucleation from aerosols rather than typical temperature and/or supersaturation relationships alone. Initial results from simulations of a deep winter cloud system and its interaction with significant orography show contrasting sensitivities in regions of warm rain versus mixed liquid and ice conditions. The classical view of higher precipitation amounts in relatively clean maritime clouds with fewer but larger droplets is confirmed for regions dominated by the warm-rain process. However, due to complex interactions with the ice phase and snow riming, the simulations revealed the reverse situation in high terrain areas dominated by snow reaching the surface. Results of other cloud systems will be summarized at the conference.

  12. Sensitivity study of surface wind flow of a limited area model simulating the extratropical storm Delta affecting the Canary Islands

    Directory of Open Access Journals (Sweden)

    C. Marrero

    2009-04-01

    Full Text Available In November 2005 an extratropical storm named Delta affected the Canary Islands (Spain. The high sustained wind and intense gusts experienced caused significant damage. A numerical sensitivity study of Delta was conducted using the Weather Research & Forecasting Model (WRF-ARW. A total of 27 simulations were performed. Non-hydrostatic and hydrostatic experiments were designed taking into account physical parameterizations and geometrical factors (size and position of the outer domain, definition or not of nested grids, horizontal resolution and number of vertical levels. The Factor Separation Method was applied in order to identify the major model sensitivity parameters under this unusual meteorological situation. Results associated to percentage changes relatives to a control run simulation demonstrated that boundary layer and surface layer schemes, horizontal resolutions, hydrostaticity option and nesting grid activation were the model configuration parameters with the greatest impact on the 48 h maximum 10 m horizontal wind speed solution.

  13. Analysis of sensitivity of simulated recharge to selected parameters for seven watersheds modeled using the precipitation-runoff modeling system

    Science.gov (United States)

    Ely, D. Matthew

    2006-01-01

    routing parameter. Although the primary objective of this study was to identify, by geographic region, the importance of the parameter value to the simulation of ground-water recharge, the secondary objectives proved valuable for future modeling efforts. The value of a rigorous sensitivity analysis can (1) make the calibration process more efficient, (2) guide additional data collection, (3) identify model limitations, and (4) explain simulated results.

  14. The application of sensitivity analysis to models of large scale physiological systems

    Science.gov (United States)

    Leonard, J. I.

    1974-01-01

    A survey of the literature of sensitivity analysis as it applies to biological systems is reported as well as a brief development of sensitivity theory. A simple population model and a more complex thermoregulatory model illustrate the investigatory techniques and interpretation of parameter sensitivity analysis. The role of sensitivity analysis in validating and verifying models, and in identifying relative parameter influence in estimating errors in model behavior due to uncertainty in input data is presented. This analysis is valuable to the simulationist and the experimentalist in allocating resources for data collection. A method for reducing highly complex, nonlinear models to simple linear algebraic models that could be useful for making rapid, first order calculations of system behavior is presented.

  15. Modelling pesticides volatilisation in greenhouses: Sensitivity analysis of a modified PEARL model.

    Science.gov (United States)

    Houbraken, Michael; Doan Ngoc, Kim; van den Berg, Frederik; Spanoghe, Pieter

    2017-12-01

    The application of the existing PEARL model was extended to include estimations of the concentration of crop protection products in greenhouse (indoor) air due to volatilisation from the plant surface. The model was modified to include the processes of ventilation of the greenhouse air to the outside atmosphere and transformation in the air. A sensitivity analysis of the model was performed by varying selected input parameters on a one-by-one basis and comparing the model outputs with the outputs of the reference scenarios. The sensitivity analysis indicates that - in addition to vapour pressure - the model had the highest ratio of variation for the rate ventilation rate and thickness of the boundary layer on the day of application. On the days after application, competing processes, degradation and uptake in the plant, becomes more important. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Hydraulic head interpolation using ANFIS—model selection and sensitivity analysis

    Science.gov (United States)

    Kurtulus, Bedri; Flipo, Nicolas

    2012-01-01

    The aim of this study is to investigate the efficiency of ANFIS (adaptive neuro fuzzy inference system) for interpolating hydraulic head in a 40-km 2 agricultural watershed of the Seine basin (France). Inputs of ANFIS are Cartesian coordinates and the elevation of the ground. Hydraulic head was measured at 73 locations during a snapshot campaign on September 2009, which characterizes low-water-flow regime in the aquifer unit. The dataset was then split into three subsets using a square-based selection method: a calibration one (55%), a training one (27%), and a test one (18%). First, a method is proposed to select the best ANFIS model, which corresponds to a sensitivity analysis of ANFIS to the type and number of membership functions (MF). Triangular, Gaussian, general bell, and spline-based MF are used with 2, 3, 4, and 5 MF per input node. Performance criteria on the test subset are used to select the 5 best ANFIS models among 16. Then each is used to interpolate the hydraulic head distribution on a (50×50)-m grid, which is compared to the soil elevation. The cells where the hydraulic head is higher than the soil elevation are counted as "error cells." The ANFIS model that exhibits the less "error cells" is selected as the best ANFIS model. The best model selection reveals that ANFIS models are very sensitive to the type and number of MF. Finally, a sensibility analysis of the best ANFIS model with four triangular MF is performed on the interpolation grid, which shows that ANFIS remains stable to error propagation with a higher sensitivity to soil elevation.

  17. Defining and detecting structural sensitivity in biological models: developing a new framework.

    Science.gov (United States)

    Adamson, M W; Morozov, A Yu

    2014-12-01

    When we construct mathematical models to represent biological systems, there is always uncertainty with regards to the model specification--whether with respect to the parameters or to the formulation of model functions. Sometimes choosing two different functions with close shapes in a model can result in substantially different model predictions: a phenomenon known in the literature as structural sensitivity, which is a significant obstacle to improving the predictive power of biological models. In this paper, we revisit the general definition of structural sensitivity, compare several more specific definitions and discuss their usefulness for the construction and analysis of biological models. Then we propose a general approach to reveal structural sensitivity with regards to certain system properties, which considers infinite-dimensional neighbourhoods of the model functions: a far more powerful technique than the conventional approach of varying parameters for a fixed functional form. In particular, we suggest a rigorous method to unearth sensitivity with respect to the local stability of systems' equilibrium points. We present a method for specifying the neighbourhood of a general unknown function with [Formula: see text] inflection points in terms of a finite number of local function properties, and provide a rigorous proof of its completeness. Using this powerful result, we implement our method to explore sensitivity in several well-known multicomponent ecological models and demonstrate the existence of structural sensitivity in these models. Finally, we argue that structural sensitivity is an important intrinsic property of biological models, and a direct consequence of the complexity of the underlying real systems.

  18. Investigation of modern methods of probalistic sensitivity analysis of final repository performance assessment models (MOSEL)

    International Nuclear Information System (INIS)

    Spiessl, Sabine; Becker, Dirk-Alexander

    2017-06-01

    Sensitivity analysis is a mathematical means for analysing the sensitivities of a computational model to variations of its input parameters. Thus, it is a tool for managing parameter uncertainties. It is often performed probabilistically as global sensitivity analysis, running the model a large number of times with different parameter value combinations. Going along with the increase of computer capabilities, global sensitivity analysis has been a field of mathematical research for some decades. In the field of final repository modelling, probabilistic analysis is regarded a key element of a modern safety case. An appropriate uncertainty and sensitivity analysis can help identify parameters that need further dedicated research to reduce the overall uncertainty, generally leads to better system understanding and can thus contribute to building confidence in the models. The purpose of the project described here was to systematically investigate different numerical and graphical techniques of sensitivity analysis with typical repository models, which produce a distinctly right-skewed and tailed output distribution and can exhibit a highly nonlinear, non-monotonic or even non-continuous behaviour. For the investigations presented here, three test models were defined that describe generic, but typical repository systems. A number of numerical and graphical sensitivity analysis methods were selected for investigation and, in part, modified or adapted. Different sampling methods were applied to produce various parameter samples of different sizes and many individual runs with the test models were performed. The results were evaluated with the different methods of sensitivity analysis. On this basis the methods were compared and assessed. This report gives an overview of the background and the applied methods. The results obtained for three typical test models are presented and explained; conclusions in view of practical applications are drawn. At the end, a recommendation

  19. Investigation of modern methods of probalistic sensitivity analysis of final repository performance assessment models (MOSEL)

    Energy Technology Data Exchange (ETDEWEB)

    Spiessl, Sabine; Becker, Dirk-Alexander

    2017-06-15

    Sensitivity analysis is a mathematical means for analysing the sensitivities of a computational model to variations of its input parameters. Thus, it is a tool for managing parameter uncertainties. It is often performed probabilistically as global sensitivity analysis, running the model a large number of times with different parameter value combinations. Going along with the increase of computer capabilities, global sensitivity analysis has been a field of mathematical research for some decades. In the field of final repository modelling, probabilistic analysis is regarded a key element of a modern safety case. An appropriate uncertainty and sensitivity analysis can help identify parameters that need further dedicated research to reduce the overall uncertainty, generally leads to better system understanding and can thus contribute to building confidence in the models. The purpose of the project described here was to systematically investigate different numerical and graphical techniques of sensitivity analysis with typical repository models, which produce a distinctly right-skewed and tailed output distribution and can exhibit a highly nonlinear, non-monotonic or even non-continuous behaviour. For the investigations presented here, three test models were defined that describe generic, but typical repository systems. A number of numerical and graphical sensitivity analysis methods were selected for investigation and, in part, modified or adapted. Different sampling methods were applied to produce various parameter samples of different sizes and many individual runs with the test models were performed. The results were evaluated with the different methods of sensitivity analysis. On this basis the methods were compared and assessed. This report gives an overview of the background and the applied methods. The results obtained for three typical test models are presented and explained; conclusions in view of practical applications are drawn. At the end, a recommendation

  20. Climate and climate change sensitivity to model configuration in the Canadian RCM over North America

    Energy Technology Data Exchange (ETDEWEB)

    De Elia, Ramon [Ouranos Consortium on Regional Climate and Adaptation to Climate Change, Montreal (Canada); Centre ESCER, Univ. du Quebec a Montreal (Canada); Cote, Helene [Ouranos Consortium on Regional Climate and Adaptation to Climate Change, Montreal (Canada)

    2010-06-15

    Climate simulations performed with Regional Climate Models (RCMs) have been found to show sensitivity to parameter settings. The origin, consequences and interpretations of this sensitivity are varied, but it is generally accepted that sensitivity studies are very important for a better understanding and a more cautious manipulation of RCM results. In this work we present sensitivity experiments performed on the simulated climate produced by the Canadian Regional Climate Model (CRCM). In addition to climate sensitivity to parameter variation, we analyse the impact of the sensitivity on the climate change signal simulated by the CRCM. These studies are performed on 30-year long simulated present and future seasonal climates, and we have analysed the effect of seven kinds of configuration modifications: CRCM initial conditions, lateral boundary condition (LBC), nesting update interval, driving Global Climate Model (GCM), driving GCM member, large-scale spectral nudging, CRCM version, and domain size. Results show that large changes in both the driving model and the CRCM physics seem to be the main sources of sensitivity for the simulated climate and the climate change. Their effects dominate those of configuration issues, such as the use or not of large-scale nudging, domain size, or LBC update interval. Results suggest that in most cases, differences between simulated climates for different CRCM configurations are not transferred to the estimated climate change signal: in general, these tend to cancel each other out. (orig.)

  1. Orientation sensitive deformation in Zr alloys: experimental and modeling studies

    International Nuclear Information System (INIS)

    Srivastava, D.; Keskar, N.; Manikrishna, K.V.; Dey, G.K.; Jha, S.K.; Saibaba, N.

    2016-01-01

    Zirconium alloys are used for fuel cladding and other structural components in pressurised heavy water nuclear reactors (PHWR's). Currently there is a lot of interest in developing alloys for structural components for higher temperature reactor operation. There is also need for development of cladding material with better corrosion and mechanical property of cladding material for higher and extended burn up applications. The performance of the cladding material is primarily influenced by the microstructural features of the material such as constituent phases their morphology, precipitates characteristics, nature of defects etc. Therefore, the microstructure is tailored as per the performance requirement by through controlled additions of alloying elements, thermo-mechanical- treatments. In order to obtain the desired microstructure, it is important to know the deformation behaviour of the material. Orientation dependent deformation behavior was studied in Zr using a combination of experimental and modeling (both discrete and atomistic dislocation dynamics) methods. Under the conditions of plane strain deformation, it was observed that single phase Zr, had significant extent of deformation heterogeneity based on local orientations. Discrete dislocation dynamics simulations incorporating multi slip systems had captured the orientation sensitive deformation. MD dislocations on the other hand brought the fundamental difference in various crystallographic orientations in determining the nucleating stress for the dislocations. The deformed structure has been characterized using X-ray, electron and neutron diffraction techniques. The various operating deformation mechanism will be discussed in this presentation. (author)

  2. Stereo chromatic contrast sensitivity model to blue-yellow gratings.

    Science.gov (United States)

    Yang, Jiachen; Lin, Yancong; Liu, Yun

    2016-03-07

    As a fundamental metric of human visual system (HVS), contrast sensitivity function (CSF) is typically measured by sinusoidal gratings at the detection of thresholds for psychophysically defined cardinal channels: luminance, red-green, and blue-yellow. Chromatic CSF, which is a quick and valid index to measure human visual performance and various retinal diseases in two-dimensional (2D) space, can not be directly applied into the measurement of human stereo visual performance. And no existing perception model considers the influence of chromatic CSF of inclined planes on depth perception in three-dimensional (3D) space. The main aim of this research is to extend traditional chromatic contrast sensitivity characteristics to 3D space and build a model applicable in 3D space, for example, strengthening stereo quality of 3D images. This research also attempts to build a vision model or method to check human visual characteristics of stereo blindness. In this paper, CRT screen was clockwise and anti-clockwise rotated respectively to form the inclined planes. Four inclined planes were selected to investigate human chromatic vision in 3D space and contrast threshold of each inclined plane was measured with 18 observers. Stimuli were isoluminant blue-yellow sinusoidal gratings. Horizontal spatial frequencies ranged from 0.05 to 5 c/d. Contrast sensitivity was calculated as the inverse function of the pooled cone contrast threshold. According to the relationship between spatial frequency of inclined plane and horizontal spatial frequency, the chromatic contrast sensitivity characteristics in 3D space have been modeled based on the experimental data. The results show that the proposed model can well predicted human chromatic contrast sensitivity characteristics in 3D space.

  3. Drug-sensitive reward in crayfish: an invertebrate model system for the study of SEEKING, reward, addiction, and withdrawal.

    Science.gov (United States)

    Huber, Robert; Panksepp, Jules B; Nathaniel, Thomas; Alcaro, Antonio; Panksepp, Jaak

    2011-10-01

    In mammals, rewarding properties of drugs depend on their capacity to activate appetitive motivational states. With the underlying mechanisms strongly conserved in evolution, invertebrates have recently emerged as a powerful new model in addiction research. In crayfish natural reward has proven surprisingly sensitive to human drugs of abuse, opening an unlikely avenue of research into the basic biological mechanisms of drug addiction. In a series of studies we first examined the presence of natural reward systems in crayfish, then characterized its sensitivity to a wide range of human drugs of abuse. A conditioned place preference (CPP) paradigm was used to demonstrate that crayfish seek out those environments that had previously been paired with the psychostimulants cocaine and amphetamine, and the opioid morphine. The administration of amphetamine exerted its effects at a number of sites, including the stimulation of circuits for active exploratory behaviors (i.e., SEEKING). A further study examined morphine-induced reward, extinction and reinstatement in crayfish. Repeated intra-circulatory infusions of morphine served as a reward when paired with distinct visual or tactile cues. Morphine-induced CPP was extinguished after repeated saline injections. Following this extinction phase, morphine-experienced crayfish were once again challenged with the drug. The priming injections of morphine reinstated CPP at all tested doses, suggesting that morphine-induced CPP is unrelenting. In an exploration of drug-associated behavioral sensitization in crayfish we concurrently mapped measures of locomotion and rewarding properties of morphine. Single and repeated intra-circulatory infusions of morphine resulted in persistent locomotory sensitization, even 5 days following the infusion. Moreover, a single dose of morphine was sufficient to induce long-term behavioral sensitization. CPP for morphine and context-dependent cues could not be disrupted over a drug free period of 5

  4. Precipitates/Salts Model Sensitivity Calculation

    Energy Technology Data Exchange (ETDEWEB)

    P. Mariner

    2001-12-20

    The objective and scope of this calculation is to assist Performance Assessment Operations and the Engineered Barrier System (EBS) Department in modeling the geochemical effects of evaporation on potential seepage waters within a potential repository drift. This work is developed and documented using procedure AP-3.12Q, ''Calculations'', in support of ''Technical Work Plan For Engineered Barrier System Department Modeling and Testing FY 02 Work Activities'' (BSC 2001a). The specific objective of this calculation is to examine the sensitivity and uncertainties of the Precipitates/Salts model. The Precipitates/Salts model is documented in an Analysis/Model Report (AMR), ''In-Drift Precipitates/Salts Analysis'' (BSC 2001b). The calculation in the current document examines the effects of starting water composition, mineral suppressions, and the fugacity of carbon dioxide (CO{sub 2}) on the chemical evolution of water in the drift.

  5. [Parameter sensitivity of simulating net primary productivity of Larix olgensis forest based on BIOME-BGC model].

    Science.gov (United States)

    He, Li-hong; Wang, Hai-yan; Lei, Xiang-dong

    2016-02-01

    Model based on vegetation ecophysiological process contains many parameters, and reasonable parameter values will greatly improve simulation ability. Sensitivity analysis, as an important method to screen out the sensitive parameters, can comprehensively analyze how model parameters affect the simulation results. In this paper, we conducted parameter sensitivity analysis of BIOME-BGC model with a case study of simulating net primary productivity (NPP) of Larix olgensis forest in Wangqing, Jilin Province. First, with the contrastive analysis between field measurement data and the simulation results, we tested the BIOME-BGC model' s capability of simulating the NPP of L. olgensis forest. Then, Morris and EFAST sensitivity methods were used to screen the sensitive parameters that had strong influence on NPP. On this basis, we also quantitatively estimated the sensitivity of the screened parameters, and calculated the global, the first-order and the second-order sensitivity indices. The results showed that the BIOME-BGC model could well simulate the NPP of L. olgensis forest in the sample plot. The Morris sensitivity method provided a reliable parameter sensitivity analysis result under the condition of a relatively small sample size. The EFAST sensitivity method could quantitatively measure the impact of simulation result of a single parameter as well as the interaction between the parameters in BIOME-BGC model. The influential sensitive parameters for L. olgensis forest NPP were new stem carbon to new leaf carbon allocation and leaf carbon to nitrogen ratio, the effect of their interaction was significantly greater than the other parameter' teraction effect.

  6. Computational Study of pH-sensitive Hydrogel-based Microfluidic Flow Controllers

    Science.gov (United States)

    Kurnia, Jundika C.; Birgersson, Erik; Mujumdar, Arun S.

    2011-01-01

    This computational study investigates the sensing and actuating behavior of a pH-sensitive hydrogel-based microfluidic flow controller. This hydrogel-based flow controller has inherent advantage in its unique stimuli-sensitive properties, removing the need for an external power supply. The predicted swelling behavior the hydrogel is validated with steady-state and transient experiments. We then demonstrate how the model is implemented to study the sensing and actuating behavior of hydrogels for different microfluidic flow channel/hydrogel configurations: e.g., for flow in a T-junction with single and multiple hydrogels. In short, the results suggest that the response of the hydrogel-based flow controller is slow. Therefore, two strategies to improve the response rate of the hydrogels are proposed and demonstrated. Finally, we highlight that the model can be extended to include other stimuli-responsive hydrogels such as thermo-, electric-, and glucose-sensitive hydrogels. PMID:24956303

  7. Sensitivity analysis in the WWTP modelling community – new opportunities and applications

    DEFF Research Database (Denmark)

    Sin, Gürkan; Ruano, M.V.; Neumann, Marc B.

    2010-01-01

    design (BSM1 plant layout) using Standardized Regression Coefficients (SRC) and (ii) Applying sensitivity analysis to help fine-tuning a fuzzy controller for a BNPR plant using Morris Screening. The results obtained from each case study are then critically discussed in view of practical applications......A mainstream viewpoint on sensitivity analysis in the wastewater modelling community is that it is a first-order differential analysis of outputs with respect to the parameters – typically obtained by perturbing one parameter at a time with a small factor. An alternative viewpoint on sensitivity...

  8. Assessing parameter importance of the Common Land Model based on qualitative and quantitative sensitivity analysis

    Directory of Open Access Journals (Sweden)

    J. Li

    2013-08-01

    Full Text Available Proper specification of model parameters is critical to the performance of land surface models (LSMs. Due to high dimensionality and parameter interaction, estimating parameters of an LSM is a challenging task. Sensitivity analysis (SA is a tool that can screen out the most influential parameters on model outputs. In this study, we conducted parameter screening for six output fluxes for the Common Land Model: sensible heat, latent heat, upward longwave radiation, net radiation, soil temperature and soil moisture. A total of 40 adjustable parameters were considered. Five qualitative SA methods, including local, sum-of-trees, multivariate adaptive regression splines, delta test and Morris methods, were compared. The proper sampling design and sufficient sample size necessary to effectively screen out the sensitive parameters were examined. We found that there are 2–8 sensitive parameters, depending on the output type, and about 400 samples are adequate to reliably identify the most sensitive parameters. We also employed a revised Sobol' sensitivity method to quantify the importance of all parameters. The total effects of the parameters were used to assess the contribution of each parameter to the total variances of the model outputs. The results confirmed that global SA methods can generally identify the most sensitive parameters effectively, while local SA methods result in type I errors (i.e., sensitive parameters labeled as insensitive or type II errors (i.e., insensitive parameters labeled as sensitive. Finally, we evaluated and confirmed the screening results for their consistency with the physical interpretation of the model parameters.

  9. Sensitivity and uncertainty analysis for the annual phosphorus loss estimator model.

    Science.gov (United States)

    Bolster, Carl H; Vadas, Peter A

    2013-07-01

    Models are often used to predict phosphorus (P) loss from agricultural fields. Although it is commonly recognized that model predictions are inherently uncertain, few studies have addressed prediction uncertainties using P loss models. In this study we assessed the effect of model input error on predictions of annual P loss by the Annual P Loss Estimator (APLE) model. Our objectives were (i) to conduct a sensitivity analyses for all APLE input variables to determine which variables the model is most sensitive to, (ii) to determine whether the relatively easy-to-implement first-order approximation (FOA) method provides accurate estimates of model prediction uncertainties by comparing results with the more accurate Monte Carlo simulation (MCS) method, and (iii) to evaluate the performance of the APLE model against measured P loss data when uncertainties in model predictions and measured data are included. Our results showed that for low to moderate uncertainties in APLE input variables, the FOA method yields reasonable estimates of model prediction uncertainties, although for cases where manure solid content is between 14 and 17%, the FOA method may not be as accurate as the MCS method due to a discontinuity in the manure P loss component of APLE at a manure solid content of 15%. The estimated uncertainties in APLE predictions based on assumed errors in the input variables ranged from ±2 to 64% of the predicted value. Results from this study highlight the importance of including reasonable estimates of model uncertainty when using models to predict P loss. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  10. Sensitivity Analysis of Corrosion Rate Prediction Models Utilized for Reinforced Concrete Affected by Chloride

    Science.gov (United States)

    Siamphukdee, Kanjana; Collins, Frank; Zou, Roger

    2013-06-01

    Chloride-induced reinforcement corrosion is one of the major causes of premature deterioration in reinforced concrete (RC) structures. Given the high maintenance and replacement costs, accurate modeling of RC deterioration is indispensable for ensuring the optimal allocation of limited economic resources. Since corrosion rate is one of the major factors influencing the rate of deterioration, many predictive models exist. However, because the existing models use very different sets of input parameters, the choice of model for RC deterioration is made difficult. Although the factors affecting corrosion rate are frequently reported in the literature, there is no published quantitative study on the sensitivity of predicted corrosion rate to the various input parameters. This paper presents the results of the sensitivity analysis of the input parameters for nine selected corrosion rate prediction models. Three different methods of analysis are used to determine and compare the sensitivity of corrosion rate to various input parameters: (i) univariate regression analysis, (ii) multivariate regression analysis, and (iii) sensitivity index. The results from the analysis have quantitatively verified that the corrosion rate of steel reinforcement bars in RC structures is highly sensitive to corrosion duration time, concrete resistivity, and concrete chloride content. These important findings establish that future empirical models for predicting corrosion rate of RC should carefully consider and incorporate these input parameters.

  11. Sensitivity study of the wet deposition schemes in the modelling of the Fukushima accident.

    Science.gov (United States)

    Quérel, Arnaud; Quélo, Denis; Roustan, Yelva; Mathieu, Anne; Kajino, Mizuo; Sekiyama, Thomas; Adachi, Kouji; Didier, Damien; Igarashi, Yasuhito

    2016-04-01

    The Fukushima-Daiichi release of radioactivity is a relevant event to study the atmospheric dispersion modelling of radionuclides. Actually, the atmospheric deposition onto the ground may be studied through the map of measured Cs-137 established consecutively to the accident. The limits of detection were low enough to make the measurements possible as far as 250km from the nuclear power plant. This large scale deposition has been modelled with the Eulerian model ldX. However, several weeks of emissions in multiple weather conditions make it a real challenge. Besides, these measurements are accumulated deposition of Cs-137 over the whole period and do not inform of deposition mechanisms involved: in-cloud, below-cloud, dry deposition. A comprehensive sensitivity analysis is performed in order to understand wet deposition mechanisms. It has been shown in a previous study (Quérel et al, 2016) that the choice of the wet deposition scheme has a strong impact on the assessment of the deposition patterns. Nevertheless, a "best" scheme could not be highlighted as it depends on the selected criteria: the ranking differs according to the statistical indicators considered (correlation, figure of merit in space and factor 2). A possibility to explain the difficulty to discriminate between several schemes was the uncertainties in the modelling, resulting from the meteorological data for instance. Since the move of the plume is not properly modelled, the deposition processes are applied with an inaccurate activity in the air. In the framework of the SAKURA project, an MRI-IRSN collaboration, new meteorological fields at higher resolution (Sekiyama et al., 2013) were provided and allows to reconsider the previous study. An updated study including these new meteorology data is presented. In addition, a focus on several releases causing deposition in located areas during known period was done. This helps to better understand the mechanisms of deposition involved following the

  12. Parameter Sensitivity of High–Order Equivalent Circuit Models Of Turbine Generator

    Directory of Open Access Journals (Sweden)

    T. Niewierowicz–Swiecicka

    2010-01-01

    Full Text Available This work shows the results of a parametric sensitivity analysis applied to a state–space representation of high–order two–axis equivalent circuits (ECs of a turbo generator (150 MVA, 120 MW, 13.8 kV y 50 Hz. The main purpose of this study is to evaluate each parameter impact on the transient response of the analyzed two–axis models –d–axis ECs with one to five damper branches and q–axis ECs from one to four damper branches–. The parametric sensitivity concept is formulated in a general context and the sensibility function is established from the generator response to a short circuit condition. Results ponder the importance played by each parameter in the model behavior. The algorithms were design within MATLAB® environment. The study gives way to conclusions on electromagnetic aspects of solid rotor synchronous generators that have not been previously studied. The methodology presented here can be applied to any other physical system.

  13. 4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

    Science.gov (United States)

    Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

    2008-01-01

    Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934

  14. Sensitivity and Interaction Analysis Based on Sobol’ Method and Its Application in a Distributed Flood Forecasting Model

    Directory of Open Access Journals (Sweden)

    Hui Wan

    2015-06-01

    Full Text Available Sensitivity analysis is a fundamental approach to identify the most significant and sensitive parameters, helping us to understand complex hydrological models, particularly for time-consuming distributed flood forecasting models based on complicated theory with numerous parameters. Based on Sobol’ method, this study compared the sensitivity and interactions of distributed flood forecasting model parameters with and without accounting for correlation. Four objective functions: (1 Nash–Sutcliffe efficiency (ENS; (2 water balance coefficient (WB; (3 peak discharge efficiency (EP; and (4 time to peak efficiency (ETP were implemented to the Liuxihe model with hourly rainfall-runoff data collected in the Nanhua Creek catchment, Pearl River, China. Contrastive results for the sensitivity and interaction analysis were also illustrated among small, medium, and large flood magnitudes. Results demonstrated that the choice of objective functions had no effect on the sensitivity classification, while it had great influence on the sensitivity ranking for both uncorrelated and correlated cases. The Liuxihe model behaved and responded uniquely to various flood conditions. The results also indicated that the pairwise parameters interactions revealed a non-ignorable contribution to the model output variance. Parameters with high first or total order sensitivity indices presented a corresponding high second order sensitivity indices and correlation coefficients with other parameters. Without considering parameter correlations, the variance contributions of highly sensitive parameters might be underestimated and those of normally sensitive parameters might be overestimated. This research laid a basic foundation to improve the understanding of complex model behavior.

  15. Sensitivity Analysis of a Riparian Vegetation Growth Model

    Directory of Open Access Journals (Sweden)

    Michael Nones

    2016-11-01

    Full Text Available The paper presents a sensitivity analysis of two main parameters used in a mathematic model able to evaluate the effects of changing hydrology on the growth of riparian vegetation along rivers and its effects on the cross-section width. Due to a lack of data in existing literature, in a past study the schematization proposed here was applied only to two large rivers, assuming steady conditions for the vegetational carrying capacity and coupling the vegetal model with a 1D description of the river morphology. In this paper, the limitation set by steady conditions is overcome, imposing the vegetational evolution dependent upon the initial plant population and the growth rate, which represents the potential growth of the overall vegetation along the watercourse. The sensitivity analysis shows that, regardless of the initial population density, the growth rate can be considered the main parameter defining the development of riparian vegetation, but it results site-specific effects, with significant differences for large and small rivers. Despite the numerous simplifications adopted and the small database analyzed, the comparison between measured and computed river widths shows a quite good capability of the model in representing the typical interactions between riparian vegetation and water flow occurring along watercourses. After a thorough calibration, the relatively simple structure of the code permits further developments and applications to a wide range of alluvial rivers.

  16. [Temporal and spatial heterogeneity analysis of optimal value of sensitive parameters in ecological process model: The BIOME-BGC model as an example.

    Science.gov (United States)

    Li, Yi Zhe; Zhang, Ting Long; Liu, Qiu Yu; Li, Ying

    2018-01-01

    The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present. However, there are many parameters for these models, and weather the reasonable values of these parameters were taken, have important impact on the models simulation results. In the past, the sensitivity and the optimization of model parameters were analyzed and discussed in many researches. But the temporal and spatial heterogeneity of the optimal parameters is less concerned. In this paper, the BIOME-BGC model was used as an example. In the evergreen broad-leaved forest, deciduous broad-leaved forest and C3 grassland, the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type. The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site. Then we constructed the temporal heterogeneity judgment index, the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters. The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types, but the selected sensitive parameters were mostly consistent. The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types. The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity. In addition, the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation

  17. Sensitivity analysis of a modified energy model

    International Nuclear Information System (INIS)

    Suganthi, L.; Jagadeesan, T.R.

    1997-01-01

    Sensitivity analysis is carried out to validate model formulation. A modified model has been developed to predict the future energy requirement of coal, oil and electricity, considering price, income, technological and environmental factors. The impact and sensitivity of the independent variables on the dependent variable are analysed. The error distribution pattern in the modified model as compared to a conventional time series model indicated the absence of clusters. The residual plot of the modified model showed no distinct pattern of variation. The percentage variation of error in the conventional time series model for coal and oil ranges from -20% to +20%, while for electricity it ranges from -80% to +20%. However, in the case of the modified model the percentage variation in error is greatly reduced - for coal it ranges from -0.25% to +0.15%, for oil -0.6% to +0.6% and for electricity it ranges from -10% to +10%. The upper and lower limit consumption levels at 95% confidence is determined. The consumption at varying percentage changes in price and population are analysed. The gap between the modified model predictions at varying percentage changes in price and population over the years from 1990 to 2001 is found to be increasing. This is because of the increasing rate of energy consumption over the years and also the confidence level decreases as the projection is made far into the future. (author)

  18. Sensitivity analysis of predictive models with an automated adjoint generator

    International Nuclear Information System (INIS)

    Pin, F.G.; Oblow, E.M.

    1987-01-01

    The adjoint method is a well established sensitivity analysis methodology that is particularly efficient in large-scale modeling problems. The coefficients of sensitivity of a given response with respect to every parameter involved in the modeling code can be calculated from the solution of a single adjoint run of the code. Sensitivity coefficients provide a quantitative measure of the importance of the model data in calculating the final results. The major drawback of the adjoint method is the requirement for calculations of very large numbers of partial derivatives to set up the adjoint equations of the model. ADGEN is a software system that has been designed to eliminate this drawback and automatically implement the adjoint formulation in computer codes. The ADGEN system will be described and its use for improving performance assessments and predictive simulations will be discussed. 8 refs., 1 fig

  19. Micropollutants throughout an integrated urban drainage model: Sensitivity and uncertainty analysis

    Science.gov (United States)

    Mannina, Giorgio; Cosenza, Alida; Viviani, Gaspare

    2017-11-01

    The paper presents the sensitivity and uncertainty analysis of an integrated urban drainage model which includes micropollutants. Specifically, a bespoke integrated model developed in previous studies has been modified in order to include the micropollutant assessment (namely, sulfamethoxazole - SMX). The model takes into account also the interactions between the three components of the system: sewer system (SS), wastewater treatment plant (WWTP) and receiving water body (RWB). The analysis has been applied to an experimental catchment nearby Palermo (Italy): the Nocella catchment. Overall, five scenarios, each characterized by different uncertainty combinations of sub-systems (i.e., SS, WWTP and RWB), have been considered applying, for the sensitivity analysis, the Extended-FAST method in order to select the key factors affecting the RWB quality and to design a reliable/useful experimental campaign. Results have demonstrated that sensitivity analysis is a powerful tool for increasing operator confidence in the modelling results. The approach adopted here can be used for blocking some non-identifiable factors, thus wisely modifying the structure of the model and reducing the related uncertainty. The model factors related to the SS have been found to be the most relevant factors affecting the SMX modeling in the RWB when all model factors (scenario 1) or model factors of SS (scenarios 2 and 3) are varied. If the only factors related to the WWTP are changed (scenarios 4 and 5), the SMX concentration in the RWB is mainly influenced (till to 95% influence of the total variance for SSMX,max) by the aerobic sorption coefficient. A progressive uncertainty reduction from the upstream to downstream was found for the soluble fraction of SMX in the RWB.

  20. A bend thickness sensitivity study of Candu feeder piping

    International Nuclear Information System (INIS)

    Li, M.; Aggarwal, M.L.; Meysner, A.; Micelotta, C.

    2005-01-01

    In CANDU reactors, feeder bends close to the connection at the fuel channel may be subjected to the highest Flow Accelerated Corrosion (FAC) and stresses. Feeder pipe stress analysis is crucial in the life extension of aging CANDU plants. Typical feeder pipes are interconnected by upper link plates and spacers. It is well known that the stresses at the bends are sensitive to the local bend thicknesses. It is also known from the authors' study (Li and et al, 2005) that feeder inter linkage effect is significant and cannot be ignored. The field measurement of feeder bend thickness is difficult and may be subjected to uncertainty in accuracy. Hence, it is desirable to know how the stress on a subject feeder could be affected by the bend thickness variation of the neighboring feeders. This effect cannot be evaluated by the traditional 'single' feeder model approach. In this paper, the 'row' and 'combined' models developed in the previous study (Li and et al, 2005), which include the feeder interactions, are used to investigate the sensitivity of bend thickness. A series of random thickness bounded by maximum and minimum measured values were applied to feeders in the model. The results show that an individual feeder is not sensitive to the bend thickness variation of the remaining feeders in the model, but depends primarily on its own bend thickness. The highest stress at a feeder always occurs when the feeder has the smallest possible bend thickness. A minimum acceptable bend thickness for individual feeders can be computed by an iterative computing process. The dependency of field thickness measurement and the amount of required analysis work can be greatly reduced. (authors)

  1. Sensitivity study of the Storegga Slide tsunami using retrogressive and visco-plastic rheology models

    Science.gov (United States)

    Kim, Jihwan; Løvholt, Finn

    2016-04-01

    Enormous submarine landslides having volumes up to thousands of km3 and long run-out may cause tsunamis with widespread effects. Clay-rich landslides, such as Trænadjupet and Storegga offshore Norway commonly involve retrogressive mass and momentum release mechanisms that affect the tsunami generation. As a consequence, the failure mechanisms, soil parameters, and release rate of the retrogression are of importance for the tsunami generation. Previous attempts to model the tsunami generation due to retrogressive landslides are few, and limited to idealized conditions. Here, a visco-plastic model including additional effects such as remolding, time dependent mass release, and hydrodynamic resistance, is employed for simulating the Storegga Slide. As landslide strength parameters and their evolution in time are uncertain, it is necessary to conduct a sensitivity study to shed light on the tsunamigenic processes. The induced tsunami is simulated using Geoclaw. We also compare our tsunami simulations with recent analysis conducted using a pure retrogressive model for the landslide, as well as previously published results using a block model. The availability of paleotsunami run-up data and detailed slide deposits provides a suitable background for improved understanding of the slide mechanics and tsunami generation. The research leading to these results has received funding from the Research Council of Norway under grant number 231252 (Project TsunamiLand) and the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement 603839 (Project ASTARTE).

  2. Mars approach for global sensitivity analysis of differential equation models with applications to dynamics of influenza infection.

    Science.gov (United States)

    Lee, Yeonok; Wu, Hulin

    2012-01-01

    Differential equation models are widely used for the study of natural phenomena in many fields. The study usually involves unknown factors such as initial conditions and/or parameters. It is important to investigate the impact of unknown factors (parameters and initial conditions) on model outputs in order to better understand the system the model represents. Apportioning the uncertainty (variation) of output variables of a model according to the input factors is referred to as sensitivity analysis. In this paper, we focus on the global sensitivity analysis of ordinary differential equation (ODE) models over a time period using the multivariate adaptive regression spline (MARS) as a meta model based on the concept of the variance of conditional expectation (VCE). We suggest to evaluate the VCE analytically using the MARS model structure of univariate tensor-product functions which is more computationally efficient. Our simulation studies show that the MARS model approach performs very well and helps to significantly reduce the computational cost. We present an application example of sensitivity analysis of ODE models for influenza infection to further illustrate the usefulness of the proposed method.

  3. Global sensitivity analysis applied to drying models for one or a population of granules

    DEFF Research Database (Denmark)

    Mortier, Severine Therese F. C.; Gernaey, Krist; Thomas, De Beer

    2014-01-01

    The development of mechanistic models for pharmaceutical processes is of increasing importance due to a noticeable shift toward continuous production in the industry. Sensitivity analysis is a powerful tool during the model building process. A global sensitivity analysis (GSA), exploring sensitiv......The development of mechanistic models for pharmaceutical processes is of increasing importance due to a noticeable shift toward continuous production in the industry. Sensitivity analysis is a powerful tool during the model building process. A global sensitivity analysis (GSA), exploring...... sensitivity in a broad parameter space, is performed to detect the most sensitive factors in two models, that is, one for drying of a single granule and one for the drying of a population of granules [using population balance model (PBM)], which was extended by including the gas velocity as extra input...... compared to our earlier work. beta(2) was found to be the most important factor for the single particle model which is useful information when performing model calibration. For the PBM-model, the granule radius and gas temperature were found to be most sensitive. The former indicates that granulator...

  4. Using Structured Knowledge Representation for Context-Sensitive Probabilistic Modeling

    National Research Council Canada - National Science Library

    Sakhanenko, Nikita A; Luger, George F

    2008-01-01

    We propose a context-sensitive probabilistic modeling system (COSMOS) that reasons about a complex, dynamic environment through a series of applications of smaller, knowledge-focused models representing contextually relevant information...

  5. Experimental Design for Sensitivity Analysis of Simulation Models

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2001-01-01

    This introductory tutorial gives a survey on the use of statistical designs for what if-or sensitivity analysis in simulation.This analysis uses regression analysis to approximate the input/output transformation that is implied by the simulation model; the resulting regression model is also known as

  6. Modeling the Sensitivity of Field Surveys for Detection of Environmental DNA (eDNA.

    Directory of Open Access Journals (Sweden)

    Martin T Schultz

    Full Text Available The environmental DNA (eDNA method is the practice of collecting environmental samples and analyzing them for the presence of a genetic marker specific to a target species. Little is known about the sensitivity of the eDNA method. Sensitivity is the probability that the target marker will be detected if it is present in the water body. Methods and tools are needed to assess the sensitivity of sampling protocols, design eDNA surveys, and interpret survey results. In this study, the sensitivity of the eDNA method is modeled as a function of ambient target marker concentration. The model accounts for five steps of sample collection and analysis, including: 1 collection of a filtered water sample from the source; 2 extraction of DNA from the filter and isolation in a purified elution; 3 removal of aliquots from the elution for use in the polymerase chain reaction (PCR assay; 4 PCR; and 5 genetic sequencing. The model is applicable to any target species. For demonstration purposes, the model is parameterized for bighead carp (Hypophthalmichthys nobilis and silver carp (H. molitrix assuming sampling protocols used in the Chicago Area Waterway System (CAWS. Simulation results show that eDNA surveys have a high false negative rate at low concentrations of the genetic marker. This is attributed to processing of water samples and division of the extraction elution in preparation for the PCR assay. Increases in field survey sensitivity can be achieved by increasing sample volume, sample number, and PCR replicates. Increasing sample volume yields the greatest increase in sensitivity. It is recommended that investigators estimate and communicate the sensitivity of eDNA surveys to help facilitate interpretation of eDNA survey results. In the absence of such information, it is difficult to evaluate the results of surveys in which no water samples test positive for the target marker. It is also recommended that invasive species managers articulate concentration

  7. Mixing-model Sensitivity to Initial Conditions in Hydrodynamic Predictions

    Science.gov (United States)

    Bigelow, Josiah; Silva, Humberto; Truman, C. Randall; Vorobieff, Peter

    2017-11-01

    Amagat and Dalton mixing-models were studied to compare their thermodynamic prediction of shock states. Numerical simulations with the Sandia National Laboratories shock hydrodynamic code CTH modeled University of New Mexico (UNM) shock tube laboratory experiments shocking a 1:1 molar mixture of helium (He) and sulfur hexafluoride (SF6) . Five input parameters were varied for sensitivity analysis: driver section pressure, driver section density, test section pressure, test section density, and mixture ratio (mole fraction). We show via incremental Latin hypercube sampling (LHS) analysis that significant differences exist between Amagat and Dalton mixing-model predictions. The differences observed in predicted shock speeds, temperatures, and pressures grow more pronounced with higher shock speeds. Supported by NNSA Grant DE-0002913.

  8. Parameter sensitivity and uncertainty analysis for a storm surge and wave model

    Directory of Open Access Journals (Sweden)

    L. A. Bastidas

    2016-09-01

    Full Text Available Development and simulation of synthetic hurricane tracks is a common methodology used to estimate hurricane hazards in the absence of empirical coastal surge and wave observations. Such methods typically rely on numerical models to translate stochastically generated hurricane wind and pressure forcing into coastal surge and wave estimates. The model output uncertainty associated with selection of appropriate model parameters must therefore be addressed. The computational overburden of probabilistic surge hazard estimates is exacerbated by the high dimensionality of numerical surge and wave models. We present a model parameter sensitivity analysis of the Delft3D model for the simulation of hazards posed by Hurricane Bob (1991 utilizing three theoretical wind distributions (NWS23, modified Rankine, and Holland. The sensitive model parameters (of 11 total considered include wind drag, the depth-induced breaking γB, and the bottom roughness. Several parameters show no sensitivity (threshold depth, eddy viscosity, wave triad parameters, and depth-induced breaking αB and can therefore be excluded to reduce the computational overburden of probabilistic surge hazard estimates. The sensitive model parameters also demonstrate a large number of interactions between parameters and a nonlinear model response. While model outputs showed sensitivity to several parameters, the ability of these parameters to act as tuning parameters for calibration is somewhat limited as proper model calibration is strongly reliant on accurate wind and pressure forcing data. A comparison of the model performance with forcings from the different wind models is also presented.

  9. Revisiting the radionuclide atmospheric dispersion event of the Chernobyl disaster - modelling sensitivity and data assimilation

    Science.gov (United States)

    Roustan, Yelva; Duhanyan, Nora; Bocquet, Marc; Winiarek, Victor

    2013-04-01

    A sensitivity study of the numerical model, as well as, an inverse modelling approach applied to the atmospheric dispersion issues after the Chernobyl disaster are both presented in this paper. On the one hand, the robustness of the source term reconstruction through advanced data assimilation techniques was tested. On the other hand, the classical approaches for sensitivity analysis were enhanced by the use of an optimised forcing field which otherwise is known to be strongly uncertain. The POLYPHEMUS air quality system was used to perform the simulations of radionuclide dispersion. Activity concentrations in air and deposited to the ground of iodine-131, caesium-137 and caesium-134 were considered. The impact of the implemented parameterizations of the physical processes (dry and wet depositions, vertical turbulent diffusion), of the forcing fields (meteorology and source terms) and of the numerical configuration (horizontal resolution) were investigated for the sensitivity study of the model. A four dimensional variational scheme (4D-Var) based on the approximate adjoint of the chemistry transport model was used to invert the source term. The data assimilation is performed with measurements of activity concentrations in air extracted from the Radioactivity Environmental Monitoring (REM) database. For most of the investigated configurations (sensitivity study), the statistics to compare the model results to the field measurements as regards the concentrations in air are clearly improved while using a reconstructed source term. As regards the ground deposited concentrations, an improvement can only be seen in case of satisfactorily modelled episode. Through these studies, the source term and the meteorological fields are proved to have a major impact on the activity concentrations in air. These studies also reinforce the use of reconstructed source term instead of the usual estimated one. A more detailed parameterization of the deposition process seems also to be

  10. A context-sensitive trust model for online social networking

    CSIR Research Space (South Africa)

    Danny, MN

    2016-11-01

    Full Text Available of privacy attacks. In the quest to address this problem, this paper proposes a context-sensitive trust model. The proposed trust model was designed using fuzzy logic theory and implemented using MATLAB. Contrary to existing trust models, the context...

  11. Sensitivity, Error and Uncertainty Quantification: Interfacing Models at Different Scales

    International Nuclear Information System (INIS)

    Krstic, Predrag S.

    2014-01-01

    Discussion on accuracy of AMO data to be used in the plasma modeling codes for astrophysics and nuclear fusion applications, including plasma-material interfaces (PMI), involves many orders of magnitude of energy, spatial and temporal scales. Thus, energies run from tens of K to hundreds of millions of K, temporal and spatial scales go from fs to years and from nm’s to m’s and more, respectively. The key challenge for the theory and simulation in this field is the consistent integration of all processes and scales, i.e. an “integrated AMO science” (IAMO). The principal goal of the IAMO science is to enable accurate studies of interactions of electrons, atoms, molecules, photons, in many-body environment, including complex collision physics of plasma-material interfaces, leading to the best decisions and predictions. However, the accuracy requirement for a particular data strongly depends on the sensitivity of the respective plasma modeling applications to these data, which stresses a need for immediate sensitivity analysis feedback of the plasma modeling and material design communities. Thus, the data provision to the plasma modeling community is a “two-way road” as long as the accuracy of the data is considered, requiring close interactions of the AMO and plasma modeling communities.

  12. Uncertainty and sensitivity analysis of biokinetic models for radiopharmaceuticals used in nuclear medicine

    International Nuclear Information System (INIS)

    Li, W. B.; Hoeschen, C.

    2010-01-01

    Mathematical models for kinetics of radiopharmaceuticals in humans were developed and are used to estimate the radiation absorbed dose for patients in nuclear medicine by the International Commission on Radiological Protection and the Medical Internal Radiation Dose (MIRD) Committee. However, due to the fact that the residence times used were derived from different subjects, partially even with different ethnic backgrounds, a large variation in the model parameters propagates to a high uncertainty of the dose estimation. In this work, a method was developed for analysing the uncertainty and sensitivity of biokinetic models that are used to calculate the residence times. The biokinetic model of 18 F-FDG (FDG) developed by the MIRD Committee was analysed by this developed method. The sources of uncertainty of all model parameters were evaluated based on the experiments. The Latin hypercube sampling technique was used to sample the parameters for model input. Kinetic modelling of FDG in humans was performed. Sensitivity of model parameters was indicated by combining the model input and output, using regression and partial correlation analysis. The transfer rate parameter of plasma to other tissue fast is the parameter with the greatest influence on the residence time of plasma. Optimisation of biokinetic data acquisition in the clinical practice by exploitation of the sensitivity of model parameters obtained in this study is discussed. (authors)

  13. Sensitivity studies for supernovae type Ia

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, Thien Tam; Goebel, Kathrin; Reifarth, Rene [Goethe University Frankfurt am Main (Germany); Calder, Alan [SUNY - Department of Physics and Astronomy, New York (United States); Pignatari, Marco [Konkoly Observatory of the Hungarian Academy of Sciences (Hungary); Townsley, Dean [The University of Alabama (United States); Travaglio, Claudia [INAF - Astrophysical Observatory, Turin (Italy); Collaboration: NuGrid collaboration

    2016-07-01

    The NuGrid research platform provides a simulation framework to study the nucleosynthesis in multi-dimensional Supernovae Type Ia models. We use a large network of over 5,000 isotopes and more than 60,000 reactions. The nucleosynthesis is investigated in post-processing simulations with temperature and density profiles, initial abundance distributions and a set of reaction rates as input. The sensitivity of the isotopic abundances to α-, proton-, and neutron-capture reaction, their inverse reactions, as well as fusion reactions were investigated. First results have been achieved for different mass coordinates of the exploding star.

  14. THE INFLUENCE OF CONVERSION MODEL CHOICE FOR EROSION RATE ESTIMATION AND THE SENSITIVITY OF THE RESULTS TO CHANGES IN THE MODEL PARAMETER

    Directory of Open Access Journals (Sweden)

    Nita Suhartini

    2010-06-01

    Full Text Available A study of soil erosion rates had been done on a slightly and long slope of cultivated area in Ciawi - Bogor, using 137Cs technique. The objective of the present study was to evaluate the applicability of the 137Cs technique in obtaining spatially distributed information of soil redistribution at small catchment. This paper reports the result of the choice of conversion model for erosion rate estimates and the sensitive of the changes in the model parameter. For this purpose, small site was selected, namely landuse I (LU-I. The top of a slope was chosen as a reference site. The erosion/deposit rate of individual sampling points was estimated using the conversion models, namely Proportional Model (PM, Mass Balance Model 1 (MBM1 and Mass Balance Model 2 (MBM2. A comparison of the conversion models showed that the lowest value is obtained by the PM. The MBM1 gave values closer to MBM2, but MBM2 gave a reliable values. In this study, a sensitivity analysis suggest that the conversion models are sensitive to changes in parameters that depend on the site conditions, but insensitive to changes in  parameters that interact to the onset of 137Cs fallout input.   Keywords: soil erosion, environmental radioisotope, cesium

  15. [Application of Fourier amplitude sensitivity test in Chinese healthy volunteer population pharmacokinetic model of tacrolimus].

    Science.gov (United States)

    Guan, Zheng; Zhang, Guan-min; Ma, Ping; Liu, Li-hong; Zhou, Tian-yan; Lu, Wei

    2010-07-01

    In this study, we evaluated the influence of different variance from each of the parameters on the output of tacrolimus population pharmacokinetic (PopPK) model in Chinese healthy volunteers, using Fourier amplitude sensitivity test (FAST). Besides, we estimated the index of sensitivity within whole course of blood sampling, designed different sampling times, and evaluated the quality of parameters' and the efficiency of prediction. It was observed that besides CL1/F, the index of sensitivity for all of the other four parameters (V1/F, V2/F, CL2/F and k(a)) in tacrolimus PopPK model showed relatively high level and changed fast with the time passing. With the increase of the variance of k(a), its indices of sensitivity increased obviously, associated with significant decrease in sensitivity index for the other parameters, and obvious change in peak time as well. According to the simulation of NONMEM and the comparison among different fitting results, we found that the sampling time points designed according to FAST surpassed the other time points. It suggests that FAST can access the sensitivities of model parameters effectively, and assist the design of clinical sampling times and the construction of PopPK model.

  16. Sensitivity experiments to mountain representations in spectral models

    Directory of Open Access Journals (Sweden)

    U. Schlese

    2000-06-01

    Full Text Available This paper describes a set of sensitivity experiments to several formulations of orography. Three sets are considered: a "Standard" orography consisting of an envelope orography produced originally for the ECMWF model, a"Navy" orography directly from the US Navy data and a "Scripps" orography based on the data set originally compiled several years ago at Scripps. The last two are mean orographies which do not use the envelope enhancement. A new filtering technique for handling the problem of Gibbs oscillations in spectral models has been used to produce the "Navy" and "Scripps" orographies, resulting in smoother fields than the "Standard" orography. The sensitivity experiments show that orography is still an important factor in controlling the model performance even in this class of models that use a semi-lagrangian formulation for water vapour, that in principle should be less sensitive to Gibbs oscillations than the Eulerian formulation. The largest impact can be seen in the stationary waves (asymmetric part of the geopotential at 500 mb where the differences in total height and spatial pattern generate up to 60 m differences, and in the surface fields where the Gibbs removal procedure is successful in alleviating the appearance of unrealistic oscillations over the ocean. These results indicate that Gibbs oscillations also need to be treated in this class of models. The best overall result is obtained using the "Navy" data set, that achieves a good compromise between amplitude of the stationary waves and smoothness of the surface fields.

  17. Gut Microbiota in a Rat Oral Sensitization Model: Effect of a Cocoa-Enriched Diet.

    Science.gov (United States)

    Camps-Bossacoma, Mariona; Pérez-Cano, Francisco J; Franch, Àngels; Castell, Margarida

    2017-01-01

    Increasing evidence is emerging suggesting a relation between dietary compounds, microbiota, and the susceptibility to allergic diseases, particularly food allergy. Cocoa, a source of antioxidant polyphenols, has shown effects on gut microbiota and the ability to promote tolerance in an oral sensitization model. Taking these facts into consideration, the aim of the present study was to establish the influence of an oral sensitization model, both alone and together with a cocoa-enriched diet, on gut microbiota. Lewis rats were orally sensitized and fed with either a standard or 10% cocoa diet. Faecal microbiota was analysed through metagenomics study. Intestinal IgA concentration was also determined. Oral sensitization produced few changes in intestinal microbiota, but in those rats fed a cocoa diet significant modifications appeared. Decreased bacteria from the Firmicutes and Proteobacteria phyla and a higher percentage of bacteria belonging to the Tenericutes and Cyanobacteria phyla were observed. In conclusion, a cocoa diet is able to modify the microbiota bacterial pattern in orally sensitized animals. As cocoa inhibits the synthesis of specific antibodies and also intestinal IgA, those changes in microbiota pattern, particularly those of the Proteobacteria phylum, might be partially responsible for the tolerogenic effect of cocoa.

  18. Quantifying uncertainty and sensitivity in sea ice models

    Energy Technology Data Exchange (ETDEWEB)

    Urrego Blanco, Jorge Rolando [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hunke, Elizabeth Clare [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Urban, Nathan Mark [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-07-15

    The Los Alamos Sea Ice model has a number of input parameters for which accurate values are not always well established. We conduct a variance-based sensitivity analysis of hemispheric sea ice properties to 39 input parameters. The method accounts for non-linear and non-additive effects in the model.

  19. Deterministic sensitivity and uncertainty analysis for large-scale computer models

    International Nuclear Information System (INIS)

    Worley, B.A.; Pin, F.G.; Oblow, E.M.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.

    1988-01-01

    The fields of sensitivity and uncertainty analysis have traditionally been dominated by statistical techniques when large-scale modeling codes are being analyzed. These methods are able to estimate sensitivities, generate response surfaces, and estimate response probability distributions given the input parameter probability distributions. Because the statistical methods are computationally costly, they are usually applied only to problems with relatively small parameter sets. Deterministic methods, on the other hand, are very efficient and can handle large data sets, but generally require simpler models because of the considerable programming effort required for their implementation. The first part of this paper reports on the development and availability of two systems, GRESS and ADGEN, that make use of computer calculus compilers to automate the implementation of deterministic sensitivity analysis capability into existing computer models. This automation removes the traditional limitation of deterministic sensitivity methods. This second part of the paper describes a deterministic uncertainty analysis method (DUA) that uses derivative information as a basis to propagate parameter probability distributions to obtain result probability distributions. This paper is applicable to low-level radioactive waste disposal system performance assessment

  20. Investigations of sensitivity and resolution of ECG and MCG in a realistically shaped thorax model

    International Nuclear Information System (INIS)

    Mäntynen, Ville; Konttila, Teijo; Stenroos, Matti

    2014-01-01

    Solving the inverse problem of electrocardiography (ECG) and magnetocardiography (MCG) is often referred to as cardiac source imaging. Spatial properties of ECG and MCG as imaging systems are, however, not well known. In this modelling study, we investigate the sensitivity and point-spread function (PSF) of ECG, MCG, and combined ECG+MCG as a function of source position and orientation, globally around the ventricles: signal topographies are modelled using a realistically-shaped volume conductor model, and the inverse problem is solved using a distributed source model and linear source estimation with minimal use of prior information. The results show that the sensitivity depends not only on the modality but also on the location and orientation of the source and that the sensitivity distribution is clearly reflected in the PSF. MCG can better characterize tangential anterior sources (with respect to the heart surface), while ECG excels with normally-oriented and posterior sources. Compared to either modality used alone, the sensitivity of combined ECG+MCG is less dependent on source orientation per source location, leading to better source estimates. Thus, for maximal sensitivity and optimal source estimation, the electric and magnetic measurements should be combined. (paper)

  1. A framework for 2-stage global sensitivity analysis of GastroPlus™ compartmental models.

    Science.gov (United States)

    Scherholz, Megerle L; Forder, James; Androulakis, Ioannis P

    2018-04-01

    Parameter sensitivity and uncertainty analysis for physiologically based pharmacokinetic (PBPK) models are becoming an important consideration for regulatory submissions, requiring further evaluation to establish the need for global sensitivity analysis. To demonstrate the benefits of an extensive analysis, global sensitivity was implemented for the GastroPlus™ model, a well-known commercially available platform, using four example drugs: acetaminophen, risperidone, atenolol, and furosemide. The capabilities of GastroPlus were expanded by developing an integrated framework to automate the GastroPlus graphical user interface with AutoIt and for execution of the sensitivity analysis in MATLAB ® . Global sensitivity analysis was performed in two stages using the Morris method to screen over 50 parameters for significant factors followed by quantitative assessment of variability using Sobol's sensitivity analysis. The 2-staged approach significantly reduced computational cost for the larger model without sacrificing interpretation of model behavior, showing that the sensitivity results were well aligned with the biopharmaceutical classification system. Both methods detected nonlinearities and parameter interactions that would have otherwise been missed by local approaches. Future work includes further exploration of how the input domain influences the calculated global sensitivity measures as well as extending the framework to consider a whole-body PBPK model.

  2. SOX sensitivity study

    Energy Technology Data Exchange (ETDEWEB)

    Martyn, Johann [Johannes Gutenberg-Universitaet, Mainz (Germany); Collaboration: BOREXINO-Collaboration

    2016-07-01

    To this day most experimental results on neutrino oscillations can be explained in the standard three neutrino model. There are however a few experiments that show anomalous behaviour at a very short baselines. These anomalies can hypothetically be explained with the existence of one or additional more light neutrino states that do not take part in weak interactions and are thus called sterile. Although the anomalies only give a hint that such sterile neutrinos could exist the prospect for physics beyond the standard model is a major motivation to investigate the neutrino oscillations in new very short baseline experiments. The SOX (Short distance Oscillations in BoreXino) experiment will use the Borexino detector and a {sup 144}Ce source to search for sterile neutrinos via the occurance of an oscillation pattern at a baseline of several meters. This talk examines the impact of the Borexino detector systematics on the experimental sensitivity of SOX.

  3. [Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

    Science.gov (United States)

    Xi, Qing; Li, Zhao-Fu; Luo, Chuan

    2014-05-01

    Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

  4. Sediment fingerprinting experiments to test the sensitivity of multivariate mixing models

    Science.gov (United States)

    Gaspar, Leticia; Blake, Will; Smith, Hugh; Navas, Ana

    2014-05-01

    Sediment fingerprinting techniques provide insight into the dynamics of sediment transfer processes and support for catchment management decisions. As questions being asked of fingerprinting datasets become increasingly complex, validation of model output and sensitivity tests are increasingly important. This study adopts an experimental approach to explore the validity and sensitivity of mixing model outputs for materials with contrasting geochemical and particle size composition. The experiments reported here focused on (i) the sensitivity of model output to different fingerprint selection procedures and (ii) the influence of source material particle size distributions on model output. Five soils with significantly different geochemistry, soil organic matter and particle size distributions were selected as experimental source materials. A total of twelve sediment mixtures were prepared in the laboratory by combining different quantified proportions of the Kruskal-Wallis test, Discriminant Function Analysis (DFA), Principal Component Analysis (PCA), or correlation matrix). Summary results for the use of the mixing model with the different sets of fingerprint properties for the twelve mixed soils were reasonably consistent with the initial mixing percentages initially known. Given the experimental nature of the work and dry mixing of materials, geochemical conservative behavior was assumed for all elements, even for those that might be disregarded in aquatic systems (e.g. P). In general, the best fits between actual and modeled proportions were found using a set of nine tracer properties (Sr, Rb, Fe, Ti, Ca, Al, P, Si, K, Si) that were derived using DFA coupled with a multivariate stepwise algorithm, with errors between real and estimated value that did not exceed 6.7 % and values of GOF above 94.5 %. The second set of experiments aimed to explore the sensitivity of model output to variability in the particle size of source materials assuming that a degree of

  5. Time-Dependent Global Sensitivity Analysis for Long-Term Degeneracy Model Using Polynomial Chaos

    Directory of Open Access Journals (Sweden)

    Jianbin Guo

    2014-07-01

    Full Text Available Global sensitivity is used to quantify the influence of uncertain model inputs on the output variability of static models in general. However, very few approaches can be applied for the sensitivity analysis of long-term degeneracy models, as far as time-dependent reliability is concerned. The reason is that the static sensitivity may not reflect the completed sensitivity during the entire life circle. This paper presents time-dependent global sensitivity analysis for long-term degeneracy models based on polynomial chaos expansion (PCE. Sobol’ indices are employed as the time-dependent global sensitivity since they provide accurate information on the selected uncertain inputs. In order to compute Sobol’ indices more efficiently, this paper proposes a moving least squares (MLS method to obtain the time-dependent PCE coefficients with acceptable simulation effort. Then Sobol’ indices can be calculated analytically as a postprocessing of the time-dependent PCE coefficients with almost no additional cost. A test case is used to show how to conduct the proposed method, then this approach is applied to an engineering case, and the time-dependent global sensitivity is obtained for the long-term degeneracy mechanism model.

  6. Application of perturbation theory to sensitivity calculations of PWR type reactor cores using the two-channel model

    International Nuclear Information System (INIS)

    Oliveira, A.C.J.G. de.

    1988-12-01

    Sensitivity calculations are very important in design and safety of nuclear reactor cores. Large codes with a great number of physical considerations have been used to perform sensitivity studies. However, these codes need long computation time involving high costs. The perturbation theory has constituted an efficient and economical method to perform sensitivity analysis. The present work is an application of the perturbation theory (matricial formalism) to a simplified model of DNB (Departure from Nucleate Boiling) analysis to perform sensitivity calculations in PWR cores. Expressions to calculate the sensitivity coefficients of enthalpy and coolant velocity with respect to coolant density and hot channel area were developed from the proposed model. The CASNUR.FOR code to evaluate these sensitivity coefficients was written in Fortran. The comparison between results obtained from the matricial formalism of perturbation theory with those obtained directly from the proposed model makes evident the efficiency and potentiality of this perturbation method for nuclear reactor cores sensitivity calculations (author). 23 refs, 4 figs, 7 tabs

  7. Efficient transfer of sensitivity information in multi-component models

    International Nuclear Information System (INIS)

    Abdel-Khalik, Hany S.; Rabiti, Cristian

    2011-01-01

    In support of adjoint-based sensitivity analysis, this manuscript presents a new method to efficiently transfer adjoint information between components in a multi-component model, whereas the output of one component is passed as input to the next component. Often, one is interested in evaluating the sensitivities of the responses calculated by the last component to the inputs of the first component in the overall model. The presented method has two advantages over existing methods which may be classified into two broad categories: brute force-type methods and amalgamated-type methods. First, the presented method determines the minimum number of adjoint evaluations for each component as opposed to the brute force-type methods which require full evaluation of all sensitivities for all responses calculated by each component in the overall model, which proves computationally prohibitive for realistic problems. Second, the new method treats each component as a black-box as opposed to amalgamated-type methods which requires explicit knowledge of the system of equations associated with each component in order to reach the minimum number of adjoint evaluations. (author)

  8. Sensitivity analysis of the near-road dispersion model RLINE - An evaluation at Detroit, Michigan

    Science.gov (United States)

    Milando, Chad W.; Batterman, Stuart A.

    2018-05-01

    The development of accurate and appropriate exposure metrics for health effect studies of traffic-related air pollutants (TRAPs) remains challenging and important given that traffic has become the dominant urban exposure source and that exposure estimates can affect estimates of associated health risk. Exposure estimates obtained using dispersion models can overcome many of the limitations of monitoring data, and such estimates have been used in several recent health studies. This study examines the sensitivity of exposure estimates produced by dispersion models to meteorological, emission and traffic allocation inputs, focusing on applications to health studies examining near-road exposures to TRAP. Daily average concentrations of CO and NOx predicted using the Research Line source model (RLINE) and a spatially and temporally resolved mobile source emissions inventory are compared to ambient measurements at near-road monitoring sites in Detroit, MI, and are used to assess the potential for exposure measurement error in cohort and population-based studies. Sensitivity of exposure estimates is assessed by comparing nominal and alternative model inputs using statistical performance evaluation metrics and three sets of receptors. The analysis shows considerable sensitivity to meteorological inputs; generally the best performance was obtained using data specific to each monitoring site. An updated emission factor database provided some improvement, particularly at near-road sites, while the use of site-specific diurnal traffic allocations did not improve performance compared to simpler default profiles. Overall, this study highlights the need for appropriate inputs, especially meteorological inputs, to dispersion models aimed at estimating near-road concentrations of TRAPs. It also highlights the potential for systematic biases that might affect analyses that use concentration predictions as exposure measures in health studies.

  9. Short ensembles: An Efficient Method for Discerning Climate-relevant Sensitivities in Atmospheric General Circulation Models

    Energy Technology Data Exchange (ETDEWEB)

    Wan, Hui; Rasch, Philip J.; Zhang, Kai; Qian, Yun; Yan, Huiping; Zhao, Chun

    2014-09-08

    This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivity of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model version 5. The first example demonstrates that the method is capable of characterizing the model cloud and precipitation sensitivity to time step length. A nudging technique is also applied to an additional set of simulations to help understand the contribution of physics-dynamics interaction to the detected time step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol lifecycle are perturbed simultaneously in order to explore which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. Results show that in both examples, short ensembles are able to correctly reproduce the main signals of model sensitivities revealed by traditional long-term climate simulations for fast processes in the climate system. The efficiency of the ensemble method makes it particularly useful for the development of high-resolution, costly and complex climate models.

  10. A reactive transport model for mercury fate in contaminated soil--sensitivity analysis.

    Science.gov (United States)

    Leterme, Bertrand; Jacques, Diederik

    2015-11-01

    We present a sensitivity analysis of a reactive transport model of mercury (Hg) fate in contaminated soil systems. The one-dimensional model, presented in Leterme et al. (2014), couples water flow in variably saturated conditions with Hg physico-chemical reactions. The sensitivity of Hg leaching and volatilisation to parameter uncertainty is examined using the elementary effect method. A test case is built using a hypothetical 1-m depth sandy soil and a 50-year time series of daily precipitation and evapotranspiration. Hg anthropogenic contamination is simulated in the topsoil by separately considering three different sources: cinnabar, non-aqueous phase liquid and aqueous mercuric chloride. The model sensitivity to a set of 13 input parameters is assessed, using three different model outputs (volatilized Hg, leached Hg, Hg still present in the contaminated soil horizon). Results show that dissolved organic matter (DOM) concentration in soil solution and the binding constant to DOM thiol groups are critical parameters, as well as parameters related to Hg sorption to humic and fulvic acids in solid organic matter. Initial Hg concentration is also identified as a sensitive parameter. The sensitivity analysis also brings out non-monotonic model behaviour for certain parameters.

  11. A diagnostic model for the detection of sensitization to wheat allergens was developed and validated in bakery workers

    NARCIS (Netherlands)

    Suarthana, Eva; Vergouwe, Yvonne; Moons, Karel G.; de Monchy, Jan; Grobbee, Diederick; Heederik, Dick; Meijer, Evert

    Objectives: To develop and validate a prediction model to detect sensitization to wheat allergens in bakery workers. Study Design and Setting: The prediction model was developed in 867 Dutch bakery workers (development set, prevalence of sensitization 13%) and included questionnaire items (candidate

  12. Sensitivity analysis using two-dimensional models of the Whiteshell geosphere

    Energy Technology Data Exchange (ETDEWEB)

    Scheier, N. W.; Chan, T.; Stanchell, F. W.

    1992-12-01

    As part of the assessment of the environmental impact of disposing of immobilized nuclear fuel waste in a vault deep within plutonic rock, detailed modelling of groundwater flow, heat transport and containment transport through the geosphere is being performed using the MOTIF finite-element computer code. The first geosphere model is being developed using data from the Whiteshell Research Area, with a hypothetical disposal vault at a depth of 500 m. This report briefly describes the conceptual model and then describes in detail the two-dimensional simulations used to help initially define an adequate three-dimensional representation, select a suitable form for the simplified model to be used in the overall systems assessment with the SYVAC computer code, and perform some sensitivity analysis. The sensitivity analysis considers variations in the rock layer properties, variations in fracture zone configurations, the impact of grouting a vault/fracture zone intersection, and variations in boundary conditions. This study shows that the configuration of major fracture zones can have a major influence on groundwater flow patterns. The flows in the major fracture zones can have high velocities and large volumes. The proximity of the radionuclide source to a major fracture zone may strongly influence the time it takes for a radionuclide to be transported to the surface. (auth)

  13. Global sensitivity analysis for models with spatially dependent outputs

    International Nuclear Information System (INIS)

    Iooss, B.; Marrel, A.; Jullien, M.; Laurent, B.

    2011-01-01

    The global sensitivity analysis of a complex numerical model often calls for the estimation of variance-based importance measures, named Sobol' indices. Meta-model-based techniques have been developed in order to replace the CPU time-expensive computer code with an inexpensive mathematical function, which predicts the computer code output. The common meta-model-based sensitivity analysis methods are well suited for computer codes with scalar outputs. However, in the environmental domain, as in many areas of application, the numerical model outputs are often spatial maps, which may also vary with time. In this paper, we introduce an innovative method to obtain a spatial map of Sobol' indices with a minimal number of numerical model computations. It is based upon the functional decomposition of the spatial output onto a wavelet basis and the meta-modeling of the wavelet coefficients by the Gaussian process. An analytical example is presented to clarify the various steps of our methodology. This technique is then applied to a real hydrogeological case: for each model input variable, a spatial map of Sobol' indices is thus obtained. (authors)

  14. Sensitivity of Mantel Haenszel Model and Rasch Model as Viewed From Sample Size

    OpenAIRE

    ALWI, IDRUS

    2011-01-01

    The aims of this research is to study the sensitivity comparison of Mantel Haenszel and Rasch Model for detection differential item functioning, observed from the sample size. These two differential item functioning (DIF) methods were compared using simulate binary item respon data sets of varying sample size,  200 and 400 examinees were used in the analyses, a detection method of differential item functioning (DIF) based on gender difference. These test conditions were replication 4 tim...

  15. Piezoresistive Cantilever Performance-Part I: Analytical Model for Sensitivity.

    Science.gov (United States)

    Park, Sung-Jin; Doll, Joseph C; Pruitt, Beth L

    2010-02-01

    An accurate analytical model for the change in resistance of a piezoresistor is necessary for the design of silicon piezoresistive transducers. Ion implantation requires a high-temperature oxidation or annealing process to activate the dopant atoms, and this treatment results in a distorted dopant profile due to diffusion. Existing analytical models do not account for the concentration dependence of piezoresistance and are not accurate for nonuniform dopant profiles. We extend previous analytical work by introducing two nondimensional factors, namely, the efficiency and geometry factors. A practical benefit of this efficiency factor is that it separates the process parameters from the design parameters; thus, designers may address requirements for cantilever geometry and fabrication process independently. To facilitate the design process, we provide a lookup table for the efficiency factor over an extensive range of process conditions. The model was validated by comparing simulation results with the experimentally determined sensitivities of piezoresistive cantilevers. We performed 9200 TSUPREM4 simulations and fabricated 50 devices from six unique process flows; we systematically explored the design space relating process parameters and cantilever sensitivity. Our treatment focuses on piezoresistive cantilevers, but the analytical sensitivity model is extensible to other piezoresistive transducers such as membrane pressure sensors.

  16. Piezoresistive Cantilever Performance—Part I: Analytical Model for Sensitivity

    Science.gov (United States)

    Park, Sung-Jin; Doll, Joseph C.; Pruitt, Beth L.

    2010-01-01

    An accurate analytical model for the change in resistance of a piezoresistor is necessary for the design of silicon piezoresistive transducers. Ion implantation requires a high-temperature oxidation or annealing process to activate the dopant atoms, and this treatment results in a distorted dopant profile due to diffusion. Existing analytical models do not account for the concentration dependence of piezoresistance and are not accurate for nonuniform dopant profiles. We extend previous analytical work by introducing two nondimensional factors, namely, the efficiency and geometry factors. A practical benefit of this efficiency factor is that it separates the process parameters from the design parameters; thus, designers may address requirements for cantilever geometry and fabrication process independently. To facilitate the design process, we provide a lookup table for the efficiency factor over an extensive range of process conditions. The model was validated by comparing simulation results with the experimentally determined sensitivities of piezoresistive cantilevers. We performed 9200 TSUPREM4 simulations and fabricated 50 devices from six unique process flows; we systematically explored the design space relating process parameters and cantilever sensitivity. Our treatment focuses on piezoresistive cantilevers, but the analytical sensitivity model is extensible to other piezoresistive transducers such as membrane pressure sensors. PMID:20336183

  17. Sensitivity Analysis of the Bone Fracture Risk Model

    Science.gov (United States)

    Lewandowski, Beth; Myers, Jerry; Sibonga, Jean Diane

    2017-01-01

    Introduction: The probability of bone fracture during and after spaceflight is quantified to aid in mission planning, to determine required astronaut fitness standards and training requirements and to inform countermeasure research and design. Probability is quantified with a probabilistic modeling approach where distributions of model parameter values, instead of single deterministic values, capture the parameter variability within the astronaut population and fracture predictions are probability distributions with a mean value and an associated uncertainty. Because of this uncertainty, the model in its current state cannot discern an effect of countermeasures on fracture probability, for example between use and non-use of bisphosphonates or between spaceflight exercise performed with the Advanced Resistive Exercise Device (ARED) or on devices prior to installation of ARED on the International Space Station. This is thought to be due to the inability to measure key contributors to bone strength, for example, geometry and volumetric distributions of bone mass, with areal bone mineral density (BMD) measurement techniques. To further the applicability of model, we performed a parameter sensitivity study aimed at identifying those parameter uncertainties that most effect the model forecasts in order to determine what areas of the model needed enhancements for reducing uncertainty. Methods: The bone fracture risk model (BFxRM), originally published in (Nelson et al) is a probabilistic model that can assess the risk of astronaut bone fracture. This is accomplished by utilizing biomechanical models to assess the applied loads; utilizing models of spaceflight BMD loss in at-risk skeletal locations; quantifying bone strength through a relationship between areal BMD and bone failure load; and relating fracture risk index (FRI), the ratio of applied load to bone strength, to fracture probability. There are many factors associated with these calculations including

  18. Response to the eruption of Mount Pinatubo in relation to climate sensitivity in the CMIP3 models

    Energy Technology Data Exchange (ETDEWEB)

    Bender, Frida A.M.; Ekman, Annica M.L.; Rodhe, Henning [Stockholm University, Department of Meteorology, Stockholm (Sweden)

    2010-10-15

    The radiative flux perturbations and subsequent temperature responses in relation to the eruption of Mount Pinatubo in 1991 are studied in the ten general circulation models incorporated in the Coupled Model Intercomparison Project, phase 3 (CMIP3), that include a parameterization of volcanic aerosol. Models and observations show decreases in global mean temperature of up to 0.5 K, in response to radiative perturbations of up to 10 W m{sup -2}, averaged over the tropics. The time scale representing the delay between radiative perturbation and temperature response is determined by the slow ocean response, and is estimated to be centered around 4 months in the models. Although the magnitude of the temperature response to a volcanic eruption has previously been used as an indicator of equilibrium climate sensitivity in models, we find these two quantities to be only weakly correlated. This may partly be due to the fact that the size of the volcano-induced radiative perturbation varies among the models. It is found that the magnitude of the modelled radiative perturbation increases with decreasing climate sensitivity, with the exception of one outlying model. Therefore, we scale the temperature perturbation by the radiative perturbation in each model, and use the ratio between the integrated temperature perturbation and the integrated radiative perturbation as a measure of sensitivity to volcanic forcing. This ratio is found to be well correlated with the model climate sensitivity, more sensitive models having a larger ratio. Further, if this correspondence between ''volcanic sensitivity'' and sensitivity to CO{sub 2} forcing is a feature not only among the models, but also of the real climate system, the alleged linear relation can be used to estimate the real climate sensitivity. The observational value of the ratio signifying volcanic sensitivity is hereby estimated to correspond to an equilibrium climate sensitivity, i.e. equilibrium temperature

  19. Gut Microbiota in a Rat Oral Sensitization Model: Effect of a Cocoa-Enriched Diet

    Directory of Open Access Journals (Sweden)

    Mariona Camps-Bossacoma

    2017-01-01

    Full Text Available Increasing evidence is emerging suggesting a relation between dietary compounds, microbiota, and the susceptibility to allergic diseases, particularly food allergy. Cocoa, a source of antioxidant polyphenols, has shown effects on gut microbiota and the ability to promote tolerance in an oral sensitization model. Taking these facts into consideration, the aim of the present study was to establish the influence of an oral sensitization model, both alone and together with a cocoa-enriched diet, on gut microbiota. Lewis rats were orally sensitized and fed with either a standard or 10% cocoa diet. Faecal microbiota was analysed through metagenomics study. Intestinal IgA concentration was also determined. Oral sensitization produced few changes in intestinal microbiota, but in those rats fed a cocoa diet significant modifications appeared. Decreased bacteria from the Firmicutes and Proteobacteria phyla and a higher percentage of bacteria belonging to the Tenericutes and Cyanobacteria phyla were observed. In conclusion, a cocoa diet is able to modify the microbiota bacterial pattern in orally sensitized animals. As cocoa inhibits the synthesis of specific antibodies and also intestinal IgA, those changes in microbiota pattern, particularly those of the Proteobacteria phylum, might be partially responsible for the tolerogenic effect of cocoa.

  20. Unique proteomic signature for radiation sensitive patients; a comparative study between normo-sensitive and radiation sensitive breast cancer patients

    Energy Technology Data Exchange (ETDEWEB)

    Skiöld, Sara [Center for Radiation Protection Research, Department of Molecular Biosciences, The Wernner-Gren Institute, Stockholm University, Stockholm (Sweden); Azimzadeh, Omid [Institute of Radiation Biology, German Research Center for Environmental Health, Helmholtz Zentrum München (Germany); Merl-Pham, Juliane [Research Unit Protein Science, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg (Germany); Naslund, Ingemar; Wersall, Peter; Lidbrink, Elisabet [Division of Radiotherapy, Radiumhemmet, Karolinska University Hospital, Stockholm (Sweden); Tapio, Soile [Institute of Radiation Biology, German Research Center for Environmental Health, Helmholtz Zentrum München (Germany); Harms-Ringdahl, Mats [Center for Radiation Protection Research, Department of Molecular Biosciences, The Wernner-Gren Institute, Stockholm University, Stockholm (Sweden); Haghdoost, Siamak, E-mail: Siamak.Haghdoost@su.se [Center for Radiation Protection Research, Department of Molecular Biosciences, The Wernner-Gren Institute, Stockholm University, Stockholm (Sweden)

    2015-06-15

    Highlights: • The unique protein expression profiles were found that separate radiosensitive from normal sensitive breast cancer patients. • The oxidative stress response, coagulation properties and acute phase response suggested to be the hallmarks of radiation sensitivity. - Abstract: Radiation therapy is a cornerstone of modern cancer treatment. Understanding the mechanisms behind normal tissue sensitivity is essential in order to minimize adverse side effects and yet to prevent local cancer reoccurrence. The aim of this study was to identify biomarkers of radiation sensitivity to enable personalized cancer treatment. To investigate the mechanisms behind radiation sensitivity a pilot study was made where eight radiation-sensitive and nine normo-sensitive patients were selected from a cohort of 2914 breast cancer patients, based on acute tissue reactions after radiation therapy. Whole blood was sampled and irradiated in vitro with 0, 1, or 150 mGy followed by 3 h incubation at 37 °C. The leukocytes of the two groups were isolated, pooled and protein expression profiles were investigated using isotope-coded protein labeling method (ICPL). First, leukocytes from the in vitro irradiated whole blood from normo-sensitive and extremely sensitive patients were compared to the non-irradiated controls. To validate this first study a second ICPL analysis comparing only the non-irradiated samples was conducted. Both approaches showed unique proteomic signatures separating the two groups at the basal level and after doses of 1 and 150 mGy. Pathway analyses of both proteomic approaches suggest that oxidative stress response, coagulation properties and acute phase response are hallmarks of radiation sensitivity supporting our previous study on oxidative stress response. This investigation provides unique characteristics of radiation sensitivity essential for individualized radiation therapy.

  1. Unique proteomic signature for radiation sensitive patients; a comparative study between normo-sensitive and radiation sensitive breast cancer patients

    International Nuclear Information System (INIS)

    Skiöld, Sara; Azimzadeh, Omid; Merl-Pham, Juliane; Naslund, Ingemar; Wersall, Peter; Lidbrink, Elisabet; Tapio, Soile; Harms-Ringdahl, Mats; Haghdoost, Siamak

    2015-01-01

    Highlights: • The unique protein expression profiles were found that separate radiosensitive from normal sensitive breast cancer patients. • The oxidative stress response, coagulation properties and acute phase response suggested to be the hallmarks of radiation sensitivity. - Abstract: Radiation therapy is a cornerstone of modern cancer treatment. Understanding the mechanisms behind normal tissue sensitivity is essential in order to minimize adverse side effects and yet to prevent local cancer reoccurrence. The aim of this study was to identify biomarkers of radiation sensitivity to enable personalized cancer treatment. To investigate the mechanisms behind radiation sensitivity a pilot study was made where eight radiation-sensitive and nine normo-sensitive patients were selected from a cohort of 2914 breast cancer patients, based on acute tissue reactions after radiation therapy. Whole blood was sampled and irradiated in vitro with 0, 1, or 150 mGy followed by 3 h incubation at 37 °C. The leukocytes of the two groups were isolated, pooled and protein expression profiles were investigated using isotope-coded protein labeling method (ICPL). First, leukocytes from the in vitro irradiated whole blood from normo-sensitive and extremely sensitive patients were compared to the non-irradiated controls. To validate this first study a second ICPL analysis comparing only the non-irradiated samples was conducted. Both approaches showed unique proteomic signatures separating the two groups at the basal level and after doses of 1 and 150 mGy. Pathway analyses of both proteomic approaches suggest that oxidative stress response, coagulation properties and acute phase response are hallmarks of radiation sensitivity supporting our previous study on oxidative stress response. This investigation provides unique characteristics of radiation sensitivity essential for individualized radiation therapy

  2. Preliminary sensitivity analyses of corrosion models for BWIP [Basalt Waste Isolation Project] container materials

    International Nuclear Information System (INIS)

    Anantatmula, R.P.

    1984-01-01

    A preliminary sensitivity analysis was performed for the corrosion models developed for Basalt Waste Isolation Project container materials. The models describe corrosion behavior of the candidate container materials (low carbon steel and Fe9Cr1Mo), in various environments that are expected in the vicinity of the waste package, by separate equations. The present sensitivity analysis yields an uncertainty in total uniform corrosion on the basis of assumed uncertainties in the parameters comprising the corrosion equations. Based on the sample scenario and the preliminary corrosion models, the uncertainty in total uniform corrosion of low carbon steel and Fe9Cr1Mo for the 1000 yr containment period are 20% and 15%, respectively. For containment periods ≥ 1000 yr, the uncertainty in corrosion during the post-closure aqueous periods controls the uncertainty in total uniform corrosion for both low carbon steel and Fe9Cr1Mo. The key parameters controlling the corrosion behavior of candidate container materials are temperature, radiation, groundwater species, etc. Tests are planned in the Basalt Waste Isolation Project containment materials test program to determine in detail the sensitivity of corrosion to these parameters. We also plan to expand the sensitivity analysis to include sensitivity coefficients and other parameters in future studies. 6 refs., 3 figs., 9 tabs

  3. Sensitivity Analysis and Parameter Estimation for a Reactive Transport Model of Uranium Bioremediation

    Science.gov (United States)

    Meyer, P. D.; Yabusaki, S.; Curtis, G. P.; Ye, M.; Fang, Y.

    2011-12-01

    A three-dimensional, variably-saturated flow and multicomponent biogeochemical reactive transport model of uranium bioremediation was used to generate synthetic data . The 3-D model was based on a field experiment at the U.S. Dept. of Energy Rifle Integrated Field Research Challenge site that used acetate biostimulation of indigenous metal reducing bacteria to catalyze the conversion of aqueous uranium in the +6 oxidation state to immobile solid-associated uranium in the +4 oxidation state. A key assumption in past modeling studies at this site was that a comprehensive reaction network could be developed largely through one-dimensional modeling. Sensitivity analyses and parameter estimation were completed for a 1-D reactive transport model abstracted from the 3-D model to test this assumption, to identify parameters with the greatest potential to contribute to model predictive uncertainty, and to evaluate model structure and data limitations. Results showed that sensitivities of key biogeochemical concentrations varied in space and time, that model nonlinearities and/or parameter interactions have a significant impact on calculated sensitivities, and that the complexity of the model's representation of processes affecting Fe(II) in the system may make it difficult to correctly attribute observed Fe(II) behavior to modeled processes. Non-uniformity of the 3-D simulated groundwater flux and averaging of the 3-D synthetic data for use as calibration targets in the 1-D modeling resulted in systematic errors in the 1-D model parameter estimates and outputs. This occurred despite using the same reaction network for 1-D modeling as used in the data-generating 3-D model. Predictive uncertainty of the 1-D model appeared to be significantly underestimated by linear parameter uncertainty estimates.

  4. Designing novel cellulase systems through agent-based modeling and global sensitivity analysis

    Science.gov (United States)

    Apte, Advait A; Senger, Ryan S; Fong, Stephen S

    2014-01-01

    Experimental techniques allow engineering of biological systems to modify functionality; however, there still remains a need to develop tools to prioritize targets for modification. In this study, agent-based modeling (ABM) was used to build stochastic models of complexed and non-complexed cellulose hydrolysis, including enzymatic mechanisms for endoglucanase, exoglucanase, and β-glucosidase activity. Modeling results were consistent with experimental observations of higher efficiency in complexed systems than non-complexed systems and established relationships between specific cellulolytic mechanisms and overall efficiency. Global sensitivity analysis (GSA) of model results identified key parameters for improving overall cellulose hydrolysis efficiency including: (1) the cellulase half-life, (2) the exoglucanase activity, and (3) the cellulase composition. Overall, the following parameters were found to significantly influence cellulose consumption in a consolidated bioprocess (CBP): (1) the glucose uptake rate of the culture, (2) the bacterial cell concentration, and (3) the nature of the cellulase enzyme system (complexed or non-complexed). Broadly, these results demonstrate the utility of combining modeling and sensitivity analysis to identify key parameters and/or targets for experimental improvement. PMID:24830736

  5. Designing novel cellulase systems through agent-based modeling and global sensitivity analysis.

    Science.gov (United States)

    Apte, Advait A; Senger, Ryan S; Fong, Stephen S

    2014-01-01

    Experimental techniques allow engineering of biological systems to modify functionality; however, there still remains a need to develop tools to prioritize targets for modification. In this study, agent-based modeling (ABM) was used to build stochastic models of complexed and non-complexed cellulose hydrolysis, including enzymatic mechanisms for endoglucanase, exoglucanase, and β-glucosidase activity. Modeling results were consistent with experimental observations of higher efficiency in complexed systems than non-complexed systems and established relationships between specific cellulolytic mechanisms and overall efficiency. Global sensitivity analysis (GSA) of model results identified key parameters for improving overall cellulose hydrolysis efficiency including: (1) the cellulase half-life, (2) the exoglucanase activity, and (3) the cellulase composition. Overall, the following parameters were found to significantly influence cellulose consumption in a consolidated bioprocess (CBP): (1) the glucose uptake rate of the culture, (2) the bacterial cell concentration, and (3) the nature of the cellulase enzyme system (complexed or non-complexed). Broadly, these results demonstrate the utility of combining modeling and sensitivity analysis to identify key parameters and/or targets for experimental improvement.

  6. Dynamic sensitivity analysis of long running landslide models through basis set expansion and meta-modelling

    Science.gov (United States)

    Rohmer, Jeremy

    2016-04-01

    Predicting the temporal evolution of landslides is typically supported by numerical modelling. Dynamic sensitivity analysis aims at assessing the influence of the landslide properties on the time-dependent predictions (e.g., time series of landslide displacements). Yet two major difficulties arise: 1. Global sensitivity analysis require running the landslide model a high number of times (> 1000), which may become impracticable when the landslide model has a high computation time cost (> several hours); 2. Landslide model outputs are not scalar, but function of time, i.e. they are n-dimensional vectors with n usually ranging from 100 to 1000. In this article, I explore the use of a basis set expansion, such as principal component analysis, to reduce the output dimensionality to a few components, each of them being interpreted as a dominant mode of variation in the overall structure of the temporal evolution. The computationally intensive calculation of the Sobol' indices for each of these components are then achieved through meta-modelling, i.e. by replacing the landslide model by a "costless-to-evaluate" approximation (e.g., a projection pursuit regression model). The methodology combining "basis set expansion - meta-model - Sobol' indices" is then applied to the La Frasse landslide to investigate the dynamic sensitivity analysis of the surface horizontal displacements to the slip surface properties during the pore pressure changes. I show how to extract information on the sensitivity of each main modes of temporal behaviour using a limited number (a few tens) of long running simulations. In particular, I identify the parameters, which trigger the occurrence of a turning point marking a shift between a regime of low values of landslide displacements and one of high values.

  7. Examining Equity Sensitivity: An Investigation Using the Big Five and HEXACO Models of Personality

    Directory of Open Access Journals (Sweden)

    Hayden J. R. Woodley

    2016-01-01

    Full Text Available The construct of equity sensitivity describes an individual’s preference about his/her desired input to outcome ratio. Individuals high on equity sensitivity tend to be more input oriented, and are often called Benevolents. Individuals low on equity sensitivity are more outcome oriented, and are described as Entitleds. Given that equity sensitivity has often been described as a trait, the purpose of the present study was to examine major personality correlates of equity sensitivity, so as to inform both the nature of equity sensitivity, and the potential processes through which certain broad personality traits may relate to outcomes. We examined the personality correlates of equity sensitivity across three studies (total N = 1170, two personality models (i.e., the Big Five and HEXACO, the two most common measures of equity sensitivity (i.e., the Equity Preference Questionnaire and Equity Sensitivity Inventory, and using both self and peer reports of personality (in Study 3. Although results varied somewhat across samples, the personality variables of Conscientiousness and Honesty-Humility, followed by Agreeableness, were the most robust predictors of equity sensitivity. Individuals higher on these traits were more likely to be Benevolents, whereas those lower on these traits were more likely to be Entitleds. Although some associations between Extraversion, Openness, and Neuroticism and equity sensitivity were observed, these were generally not robust. Overall, it appears that there are several prominent personality variables underlying equity sensitivity, and that the addition of the HEXACO model’s dimension of Honesty-Humility substantially contributes to our understanding of equity sensitivity.

  8. Model parameters estimation and sensitivity by genetic algorithms

    International Nuclear Information System (INIS)

    Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca

    2003-01-01

    In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The

  9. Stimulus Sensitivity of a Spiking Neural Network Model

    Science.gov (United States)

    Chevallier, Julien

    2018-02-01

    Some recent papers relate the criticality of complex systems to their maximal capacity of information processing. In the present paper, we consider high dimensional point processes, known as age-dependent Hawkes processes, which have been used to model spiking neural networks. Using mean-field approximation, the response of the network to a stimulus is computed and we provide a notion of stimulus sensitivity. It appears that the maximal sensitivity is achieved in the sub-critical regime, yet almost critical for a range of biologically relevant parameters.

  10. Sensitivity of a Simulated Derecho Event to Model Initial Conditions

    Science.gov (United States)

    Wang, Wei

    2014-05-01

    Since 2003, the MMM division at NCAR has been experimenting cloud-permitting scale weather forecasting using Weather Research and Forecasting (WRF) model. Over the years, we've tested different model physics, and tried different initial and boundary conditions. Not surprisingly, we found that the model's forecasts are more sensitive to the initial conditions than model physics. In 2012 real-time experiment, WRF-DART (Data Assimilation Research Testbed) at 15 km was employed to produce initial conditions for twice-a-day forecast at 3 km. On June 29, this forecast system captured one of the most destructive derecho event on record. In this presentation, we will examine forecast sensitivity to different model initial conditions, and try to understand the important features that may contribute to the success of the forecast.

  11. Variance-based sensitivity indices for stochastic models with correlated inputs

    Energy Technology Data Exchange (ETDEWEB)

    Kala, Zdeněk [Brno University of Technology, Faculty of Civil Engineering, Department of Structural Mechanics Veveří St. 95, ZIP 602 00, Brno (Czech Republic)

    2015-03-10

    The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics.

  12. Variance-based sensitivity indices for stochastic models with correlated inputs

    International Nuclear Information System (INIS)

    Kala, Zdeněk

    2015-01-01

    The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics

  13. Sensitivity study of surface wind flow of a limited area model simulating the extratropical storm Delta affecting the Canary Islands

    OpenAIRE

    Marrero, C.; Jorba, O.; Cuevas, E.; Baldasano, J. M.

    2009-01-01

    In November 2005 an extratropical storm named Delta affected the Canary Islands (Spain). The high sustained wind and intense gusts experienced caused significant damage. A numerical sensitivity study of Delta was conducted using the Weather Research & Forecasting Model (WRF-ARW). A total of 27 simulations were performed. Non-hydrostatic and hydrostatic experiments were designed taking into account physical parameterizations and geometrical factors (size and position of the outer domain, d...

  14. Sensitivity study of a method for updating a finite element model of a nuclear power station cooling tower

    International Nuclear Information System (INIS)

    Billet, L.

    1994-01-01

    The Research and Development Division of Electricite de France is developing a surveillance method of cooling towers involving on-site wind-induced measurements. The method is supposed to detect structural damage in the tower. The damage is identified by tuning a finite element model of the tower on experimental mode shapes and eigenfrequencies. The sensitivity of the method was evaluated through numerical tests. First, the dynamic response of a damaged tower was simulated by varying the stiffness of some area of the model shell (from 1 % to 24 % of the total shell area). Second, the structural parameters of the undamaged cooling tower model were updated in order to make the output of the undamaged model as close as possible to the synthetic experimental data. The updating method, based on the minimization of the differences between experimental modal energies and modal energies calculated by the model, did not detect a stiffness change over less than 3 % of the shell area. Such a sensitivity is thought to be insufficient to detect tower cracks which behave like highly localized defaults. (author). 8 refs., 9 figs., 6 tabs

  15. A Sensitivity Study on Modeling Black Carbon in Snow and its Radiative Forcing over the Arctic and Northern China

    Energy Technology Data Exchange (ETDEWEB)

    Qian, Yun; Wang, Hailong; Zhang, Rudong; Flanner, M. G.; Rasch, Philip J.

    2014-06-02

    Black carbon in snow (BCS) simulated in the Community Atmosphere Model (CAM5) is evaluated against measurements over Northern China and the Arctic, and its sensitivity to atmospheric deposition and two parameters that affect post-depositional enrichment is explored. The BCS concentration is overestimated (underestimated) by a factor of two in Northern China (Arctic) in the default model, but agreement with observations is good over both regions in the simulation with improvements in BC transport and deposition. Sensitivity studies indicate that uncertainty in the melt-water scavenging efficiency (MSE) parameter substantially affects BCS and its radiative forcing (by a factor of 2-7) in the Arctic through post-depositional enrichment. The MSE parameter has a relatively small effect on the magnitude of BCS seasonal cycle but can alter its phase in Northern China. The impact of the snow aging scaling factor (SAF) on BCS, partly through the post-depositional enrichment effect, shows more complex latitudinal and seasonal dependence. Similar to MSE, SAF affects more significantly the magnitude (phase) of BCS season cycle over the Arctic (Northern China). While uncertainty associated with the representation of BC transport and deposition processes in CAM5 is more important than that associated with the two snow model parameters in Northern China, the two uncertainties have comparable effect in the Arctic.

  16. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    Energy Technology Data Exchange (ETDEWEB)

    Alves, Vinicius M. [Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220 (Brazil); Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Muratov, Eugene [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Laboratory of Theoretical Chemistry, A.V. Bogatsky Physical-Chemical Institute NAS of Ukraine, Odessa 65080 (Ukraine); Fourches, Denis [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Strickland, Judy; Kleinstreuer, Nicole [ILS/Contractor Supporting the NTP Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), P.O. Box 13501, Research Triangle Park, NC 27709 (United States); Andrade, Carolina H. [Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220 (Brazil); Tropsha, Alexander, E-mail: alex_tropsha@unc.edu [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States)

    2015-04-15

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative

  17. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    International Nuclear Information System (INIS)

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

    2015-01-01

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using Random Forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers was 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR Toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the Scorecard database of possible skin or sense organ toxicants as primary candidates for experimental validation. - Highlights: • It was compiled the largest publicly-available skin sensitization dataset. • Predictive QSAR models were developed for skin sensitization. • Developed models have higher prediction accuracy than OECD QSAR Toolbox. • Putative

  18. Complexity, parameter sensitivity and parameter transferability in the modelling of floodplain inundation

    Science.gov (United States)

    Bates, P. D.; Neal, J. C.; Fewtrell, T. J.

    2012-12-01

    In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound

  19. Numerical modeling and sensitivity analysis of seawater intrusion in a dual-permeability coastal karst aquifer with conduit networks

    Directory of Open Access Journals (Sweden)

    Z. Xu

    2018-01-01

    Full Text Available Long-distance seawater intrusion has been widely observed through the subsurface conduit system in coastal karst aquifers as a source of groundwater contaminant. In this study, seawater intrusion in a dual-permeability karst aquifer with conduit networks is studied by the two-dimensional density-dependent flow and transport SEAWAT model. Local and global sensitivity analyses are used to evaluate the impacts of boundary conditions and hydrological characteristics on modeling seawater intrusion in a karst aquifer, including hydraulic conductivity, effective porosity, specific storage, and dispersivity of the conduit network and of the porous medium. The local sensitivity analysis evaluates the parameters' sensitivities for modeling seawater intrusion, specifically in the Woodville Karst Plain (WKP. A more comprehensive interpretation of parameter sensitivities, including the nonlinear relationship between simulations and parameters, and/or parameter interactions, is addressed in the global sensitivity analysis. The conduit parameters and boundary conditions are important to the simulations in the porous medium because of the dynamical exchanges between the two systems. The sensitivity study indicates that salinity and head simulations in the karst features, such as the conduit system and submarine springs, are critical for understanding seawater intrusion in a coastal karst aquifer. The evaluation of hydraulic conductivity sensitivity in the continuum SEAWAT model may be biased since the conduit flow velocity is not accurately calculated by Darcy's equation as a function of head difference and hydraulic conductivity. In addition, dispersivity is no longer an important parameter in an advection-dominated karst aquifer with a conduit system, compared to the sensitivity results in a porous medium aquifer. In the end, the extents of seawater intrusion are quantitatively evaluated and measured under different scenarios with the variabilities of

  20. Deterministic methods for sensitivity and uncertainty analysis in large-scale computer models

    International Nuclear Information System (INIS)

    Worley, B.A.; Oblow, E.M.; Pin, F.G.; Maerker, R.E.; Horwedel, J.E.; Wright, R.Q.; Lucius, J.L.

    1987-01-01

    The fields of sensitivity and uncertainty analysis are dominated by statistical techniques when large-scale modeling codes are being analyzed. This paper reports on the development and availability of two systems, GRESS and ADGEN, that make use of computer calculus compilers to automate the implementation of deterministic sensitivity analysis capability into existing computer models. This automation removes the traditional limitation of deterministic sensitivity methods. The paper describes a deterministic uncertainty analysis method (DUA) that uses derivative information as a basis to propagate parameter probability distributions to obtain result probability distributions. The paper demonstrates the deterministic approach to sensitivity and uncertainty analysis as applied to a sample problem that models the flow of water through a borehole. The sample problem is used as a basis to compare the cumulative distribution function of the flow rate as calculated by the standard statistical methods and the DUA method. The DUA method gives a more accurate result based upon only two model executions compared to fifty executions in the statistical case

  1. Modeling and sensitivity analysis of consensus algorithm based distributed hierarchical control for dc microgrids

    DEFF Research Database (Denmark)

    Meng, Lexuan; Dragicevic, Tomislav; Vasquez, Juan Carlos

    2015-01-01

    of dynamic study. The aim of this paper is to model the complete DC microgrid system in z-domain and perform sensitivity analysis for the complete system. A generalized modeling method is proposed and the system dynamics under different control parameters, communication topologies and communication speed...

  2. Healthy volunteers can be phenotyped using cutaneous sensitization pain models

    DEFF Research Database (Denmark)

    Werner, Mads U; Petersen, Karin; Rowbotham, Michael C

    2013-01-01

    Human experimental pain models leading to development of secondary hyperalgesia are used to estimate efficacy of analgesics and antihyperalgesics. The ability to develop an area of secondary hyperalgesia varies substantially between subjects, but little is known about the agreement following repe...... repeated measurements. The aim of this study was to determine if the areas of secondary hyperalgesia were consistently robust to be useful for phenotyping subjects, based on their pattern of sensitization by the heat pain models.......Human experimental pain models leading to development of secondary hyperalgesia are used to estimate efficacy of analgesics and antihyperalgesics. The ability to develop an area of secondary hyperalgesia varies substantially between subjects, but little is known about the agreement following...

  3. Spontaneous baroreflex sensitivity estimates during graded bicycle exercise: a comparative study

    International Nuclear Information System (INIS)

    Vallais, Frederic; Baselli, Giuseppe; Lucini, Daniela; Pagani, Massimo; Porta, Alberto

    2009-01-01

    In the literature, several methods have been proposed for the assessment of the baroreflex sensitivity from spontaneous variability of heart period and systolic arterial pressure. The present study compares the most utilized approaches for the evaluation of the spontaneous baroreflex sensitivity (i.e. sequence-based, spectral, cross-spectral and model-based techniques) over a protocol capable of inducing a progressive decrease of the baroreflex sensitivity in the presence of a relevant respiratory drive (i.e. a stepwise dynamic bicycle exercise at 10%, 20% and 30% of the maximum nominal individual effort) in 16 healthy humans. Results demonstrated that the degree of correlation among the estimates is related to the structure of the model explicitly or implicitly assumed by the method and depends on the experimental condition (i.e. on the physiological mechanisms contemporaneously active with baroreflex, e.g. cardiopulmonary reflexes). However, even in the presence of a significant correlation, proportional and/or constant biases can be present, thus rendering spontaneous baroreflex estimates not interchangeable. We suggest that the comparison among different baroreflex sensitivity estimates might elucidate physiological mechanisms responsible for the relationship between heart period and systolic arterial pressure

  4. Sensitivity analysis on the model to the DO and BODc of the Almendares river

    International Nuclear Information System (INIS)

    Dominguez, J.; Borroto, J.; Hernandez, A.

    2004-01-01

    In the present work, the sensitivity analysis of the model was done, to compare and evaluate the influence of the kinetic coefficients and other parameters, on the DO and BODc. The effect of the BODc and the DO which the river arrives to the studied zone, the influence of the BDO of the discharges and the flow rate, on the DO was modeled. The sensitivity analysis is the base for developing a calibration optimization procedure of the Streeter Phelps model, in order to make easier the process and to increase the precision of predictions. In the other hand, it will contribute to the definition of the strategies to improve river water quality

  5. Sensitivity study of experimental measures for the nuclear liquid-gas phase transition in the statistical multifragmentation model

    Science.gov (United States)

    Lin, W.; Ren, P.; Zheng, H.; Liu, X.; Huang, M.; Wada, R.; Qu, G.

    2018-05-01

    The experimental measures of the multiplicity derivatives—the moment parameters, the bimodal parameter, the fluctuation of maximum fragment charge number (normalized variance of Zmax, or NVZ), the Fisher exponent (τ ), and the Zipf law parameter (ξ )—are examined to search for the liquid-gas phase transition in nuclear multifragmention processes within the framework of the statistical multifragmentation model (SMM). The sensitivities of these measures are studied. All these measures predict a critical signature at or near to the critical point both for the primary and secondary fragments. Among these measures, the total multiplicity derivative and the NVZ provide accurate measures for the critical point from the final cold fragments as well as the primary fragments. The present study will provide a guide for future experiments and analyses in the study of the nuclear liquid-gas phase transition.

  6. Probabilistic sensitivity analysis for the 'initial defect in the canister' reference model

    International Nuclear Information System (INIS)

    Cormenzana, J. L.

    2013-08-01

    In Posiva Oy's Safety Case 'TURVA-2012' the repository system scenarios leading to radionuclide releases have been identified in Formulation of Radionuclide Release Scenarios. Three potential causes of canister failure and radionuclide release are considered: (i) the presence of an initial defect in the copper shell of one canister that penetrates the shell completely, (ii) corrosion of the copper overpack, that occurs more rapidly if buffer density is reduced, e.g. by erosion, (iii) shear movement on fractures intersecting the deposition hole. All three failure modes are analysed deterministically in Assessment of Radionuclide Release Scenarios, and for the 'initial defect in the canister' reference model a probabilistic sensitivity analysis (PSA) has been carried out. The main steps of the PSA have been: quantification of the uncertainties in the model input parameters through the creation of probability density distributions (PDFs), Monte Carlo simulations of the evolution of the system up to 106 years using parameters values sampled from the previous PDFs. Monte Carlo simulations with 10,000 individual calculations (realisations) have been used in the PSA, quantification of the uncertainty in the model outputs due to uncertainty in the input parameters (uncertainty analysis), and identification of the parameters whose uncertainty have the greatest effect on the uncertainty in the model outputs (sensitivity analysis) Since the biosphere is not included in the Monte Carlo simulations of the system, the model outputs studied are not doses, but total and radionuclide-specific normalised release rates from the near-field and to the biosphere. These outputs are calculated dividing the activity release rates by the constraints on the activity fluxes to the environment set out by the Finnish regulator. Two different cases are analysed in the PSA: (i) the 'hole forever' case, in which the small hole through the copper overpack remains unchanged during the assessment

  7. Investigation in clinical potential of polarization sensitive optical coherence tomography in laryngeal tumor model study

    Science.gov (United States)

    Zhou, Xin; Oak, Chulho; Ahn, Yeh-Chan; Kim, Sung Won; Tang, Shuo

    2018-02-01

    Polarization-sensitive optical coherence tomography (PS-OCT) is capable of measuring tissue birefringence. It has been widely applied to access the birefringence in tissues such as skin and cartilage. The vocal cord tissue consists of three anatomical layers from the surface to deep inside, the epithelium that contains almost no collagen, the lamina propria that is composed with abundant collagen, and the vocalis muscle layer. Due to the variation in the organization of collagen fibers, the different tissue layers show different tissue birefringence, which can be evaluated by PS-OCT phase retardation measurement. Furthermore, collagen fibers in healthy connective tissues are usually well organized, which provides relatively high birefringence. When the collagen organization is destroyed by diseases such as tumor, the birefringence of the tissue will decrease. In this study, a rabbit laryngeal tumor model with different stages of tumor progression is investigated ex-vivo by PS-OCT. The PS-OCT images show a gradual decrease in birefringence from normal tissue to severe tumor tissue. A phase retardation slope-based analysis is conducted to distinguish the epithelium, lamina propria, and muscle layers, respectively. The phase retardation slope quantifies the birefringence in different layers. The quantitative study provides a more detailed comparison among different stages of the rabbit laryngeal tumor model. The PS-OCT result is validated by the corresponding histology images of the same samples.

  8. Sensitivity of system stability to model structure

    Science.gov (United States)

    Hosack, G.R.; Li, H.W.; Rossignol, P.A.

    2009-01-01

    A community is stable, and resilient, if the levels of all community variables can return to the original steady state following a perturbation. The stability properties of a community depend on its structure, which is the network of direct effects (interactions) among the variables within the community. These direct effects form feedback cycles (loops) that determine community stability. Although feedback cycles have an intuitive interpretation, identifying how they form the feedback properties of a particular community can be intractable. Furthermore, determining the role that any specific direct effect plays in the stability of a system is even more daunting. Such information, however, would identify important direct effects for targeted experimental and management manipulation even in complex communities for which quantitative information is lacking. We therefore provide a method that determines the sensitivity of community stability to model structure, and identifies the relative role of particular direct effects, indirect effects, and feedback cycles in determining stability. Structural sensitivities summarize the degree to which each direct effect contributes to stabilizing feedback or destabilizing feedback or both. Structural sensitivities prove useful in identifying ecologically important feedback cycles within the community structure and for detecting direct effects that have strong, or weak, influences on community stability. The approach may guide the development of management intervention and research design. We demonstrate its value with two theoretical models and two empirical examples of different levels of complexity. ?? 2009 Elsevier B.V. All rights reserved.

  9. Analytic uncertainty and sensitivity analysis of models with input correlations

    Science.gov (United States)

    Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu

    2018-03-01

    Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

  10. An efficient computational method for global sensitivity analysis and its application to tree growth modelling

    International Nuclear Information System (INIS)

    Wu, Qiong-Li; Cournède, Paul-Henry; Mathieu, Amélie

    2012-01-01

    Global sensitivity analysis has a key role to play in the design and parameterisation of functional–structural plant growth models which combine the description of plant structural development (organogenesis and geometry) and functional growth (biomass accumulation and allocation). We are particularly interested in this study in Sobol's method which decomposes the variance of the output of interest into terms due to individual parameters but also to interactions between parameters. Such information is crucial for systems with potentially high levels of non-linearity and interactions between processes, like plant growth. However, the computation of Sobol's indices relies on Monte Carlo sampling and re-sampling, whose costs can be very high, especially when model evaluation is also expensive, as for tree models. In this paper, we thus propose a new method to compute Sobol's indices inspired by Homma–Saltelli, which improves slightly their use of model evaluations, and then derive for this generic type of computational methods an estimator of the error estimation of sensitivity indices with respect to the sampling size. It allows the detailed control of the balance between accuracy and computing time. Numerical tests on a simple non-linear model are convincing and the method is finally applied to a functional–structural model of tree growth, GreenLab, whose particularity is the strong level of interaction between plant functioning and organogenesis. - Highlights: ► We study global sensitivity analysis in the context of functional–structural plant modelling. ► A new estimator based on Homma–Saltelli method is proposed to compute Sobol indices, based on a more balanced re-sampling strategy. ► The estimation accuracy of sensitivity indices for a class of Sobol's estimators can be controlled by error analysis. ► The proposed algorithm is implemented efficiently to compute Sobol indices for a complex tree growth model.

  11. A comparison between the minimal model and the glucose clamp in the assessment of insulin sensitivity across the spectrum of glucose tolerance. Insulin Resistance Atherosclerosis Study.

    Science.gov (United States)

    Saad, M F; Anderson, R L; Laws, A; Watanabe, R M; Kades, W W; Chen, Y D; Sands, R E; Pei, D; Savage, P J; Bergman, R N

    1994-09-01

    An insulin-modified frequently sampled intravenous glucose tolerance test (FSIGTT) with minimal model analysis was compared with the glucose clamp in 11 subjects with normal glucose tolerance (NGT), 20 with impaired glucose tolerance (IGT), and 24 with non-insulin-dependent diabetes mellitus (NIDDM). The insulin sensitivity index (SI) was calculated from FSIGTT using 22- and 12-sample protocols (SI(22) and SI(12), respectively). Insulin sensitivity from the clamp was expressed as SI(clamp) and SIP(clamp). Minimal model parameters were similar when calculated with SI(22) and SI(12). SI could not be distinguished from 0 in approximately 50% of diabetic patients with either protocol. SI(22) correlated significantly with SI(clamp) in the whole group (r = 0.62), and in the NGT (r = 0.53), IGT (r = 0.48), and NIDDM (r = 0.41) groups (P SIP(clamp) were expressed in the same units, SI(22) was 66 +/- 5% (mean +/- SE) and 50 +/- 8% lower than SI(clamp) and SIP(clamp), respectively. Thus, minimal model analysis of the insulin-modified FSIGTT provides estimates of insulin sensitivity that correlate significantly with those from the glucose clamp. The correlation was weaker, however, in NIDDM. The insulin-modified FSIGTT can be used as a simple test for assessment of insulin sensitivity in population studies involving nondiabetic subjects. Additional studies are needed before using this test routinely in patients with NIDDM.

  12. Control strategies and sensitivity analysis of anthroponotic visceral leishmaniasis model.

    Science.gov (United States)

    Zamir, Muhammad; Zaman, Gul; Alshomrani, Ali Saleh

    2017-12-01

    This study proposes a mathematical model of Anthroponotic visceral leishmaniasis epidemic with saturated infection rate and recommends different control strategies to manage the spread of this disease in the community. To do this, first, a model formulation is presented to support these strategies, with quantifications of transmission and intervention parameters. To understand the nature of the initial transmission of the disease, the reproduction number [Formula: see text] is obtained by using the next-generation method. On the basis of sensitivity analysis of the reproduction number [Formula: see text], four different control strategies are proposed for managing disease transmission. For quantification of the prevalence period of the disease, a numerical simulation for each strategy is performed and a detailed summary is presented. Disease-free state is obtained with the help of control strategies. The threshold condition for globally asymptotic stability of the disease-free state is found, and it is ascertained that the state is globally stable. On the basis of sensitivity analysis of the reproduction number, it is shown that the disease can be eradicated by using the proposed strategies.

  13. Uncertainty and sensitivity analysis of environmental transport models

    International Nuclear Information System (INIS)

    Margulies, T.S.; Lancaster, L.E.

    1985-01-01

    An uncertainty and sensitivity analysis has been made of the CRAC-2 (Calculations of Reactor Accident Consequences) atmospheric transport and deposition models. Robustness and uncertainty aspects of air and ground deposited material and the relative contribution of input and model parameters were systematically studied. The underlying data structures were investigated using a multiway layout of factors over specified ranges generated via a Latin hypercube sampling scheme. The variables selected in our analysis include: weather bin, dry deposition velocity, rain washout coefficient/rain intensity, duration of release, heat content, sigma-z (vertical) plume dispersion parameter, sigma-y (crosswind) plume dispersion parameter, and mixing height. To determine the contributors to the output variability (versus distance from the site) step-wise regression analyses were performed on transformations of the spatial concentration patterns simulated. 27 references, 2 figures, 3 tables

  14. Adjoint sensitivity studies of loop current and eddy shedding in the Gulf of Mexico

    KAUST Repository

    Gopalakrishnan, Ganesh; Cornuelle, Bruce D.; Hoteit, Ibrahim

    2013-01-01

    Adjoint model sensitivity analyses were applied for the loop current (LC) and its eddy shedding in the Gulf of Mexico (GoM) using the MIT general circulation model (MITgcm). The circulation in the GoM is mainly driven by the energetic LC and subsequent LC eddy separation. In order to understand which ocean regions and features control the evolution of the LC, including anticyclonic warm-core eddy shedding in the GoM, forward and adjoint sensitivities with respect to previous model state and atmospheric forcing were computed using the MITgcm and its adjoint. Since the validity of the adjoint model sensitivities depends on the capability of the forward model to simulate the real LC system and the eddy shedding processes, a 5 year (2004–2008) forward model simulation was performed for the GoM using realistic atmospheric forcing, initial, and boundary conditions. This forward model simulation was compared to satellite measurements of sea-surface height (SSH) and sea-surface temperature (SST), and observed transport variability. Despite realistic mean state, standard deviations, and LC eddy shedding period, the simulated LC extension shows less variability and more regularity than the observations. However, the model is suitable for studying the LC system and can be utilized for examining the ocean influences leading to a simple, and hopefully generic LC eddy separation in the GoM. The adjoint sensitivities of the LC show influences from the Yucatan Channel (YC) flow and Loop Current Frontal Eddy (LCFE) on both LC extension and eddy separation, as suggested by earlier work. Some of the processes that control LC extension after eddy separation differ from those controlling eddy shedding, but include YC through-flow. The sensitivity remains stable for more than 30 days and moves generally upstream, entering the Caribbean Sea. The sensitivities of the LC for SST generally remain closer to the surface and move at speeds consistent with advection by the high-speed core of

  15. Adjoint sensitivity studies of loop current and eddy shedding in the Gulf of Mexico

    KAUST Repository

    Gopalakrishnan, Ganesh

    2013-07-01

    Adjoint model sensitivity analyses were applied for the loop current (LC) and its eddy shedding in the Gulf of Mexico (GoM) using the MIT general circulation model (MITgcm). The circulation in the GoM is mainly driven by the energetic LC and subsequent LC eddy separation. In order to understand which ocean regions and features control the evolution of the LC, including anticyclonic warm-core eddy shedding in the GoM, forward and adjoint sensitivities with respect to previous model state and atmospheric forcing were computed using the MITgcm and its adjoint. Since the validity of the adjoint model sensitivities depends on the capability of the forward model to simulate the real LC system and the eddy shedding processes, a 5 year (2004–2008) forward model simulation was performed for the GoM using realistic atmospheric forcing, initial, and boundary conditions. This forward model simulation was compared to satellite measurements of sea-surface height (SSH) and sea-surface temperature (SST), and observed transport variability. Despite realistic mean state, standard deviations, and LC eddy shedding period, the simulated LC extension shows less variability and more regularity than the observations. However, the model is suitable for studying the LC system and can be utilized for examining the ocean influences leading to a simple, and hopefully generic LC eddy separation in the GoM. The adjoint sensitivities of the LC show influences from the Yucatan Channel (YC) flow and Loop Current Frontal Eddy (LCFE) on both LC extension and eddy separation, as suggested by earlier work. Some of the processes that control LC extension after eddy separation differ from those controlling eddy shedding, but include YC through-flow. The sensitivity remains stable for more than 30 days and moves generally upstream, entering the Caribbean Sea. The sensitivities of the LC for SST generally remain closer to the surface and move at speeds consistent with advection by the high-speed core of

  16. Short ensembles: an efficient method for discerning climate-relevant sensitivities in atmospheric general circulation models

    Directory of Open Access Journals (Sweden)

    H. Wan

    2014-09-01

    Full Text Available This paper explores the feasibility of an experimentation strategy for investigating sensitivities in fast components of atmospheric general circulation models. The basic idea is to replace the traditional serial-in-time long-term climate integrations by representative ensembles of shorter simulations. The key advantage of the proposed method lies in its efficiency: since fewer days of simulation are needed, the computational cost is less, and because individual realizations are independent and can be integrated simultaneously, the new dimension of parallelism can dramatically reduce the turnaround time in benchmark tests, sensitivities studies, and model tuning exercises. The strategy is not appropriate for exploring sensitivity of all model features, but it is very effective in many situations. Two examples are presented using the Community Atmosphere Model, version 5. In the first example, the method is used to characterize sensitivities of the simulated clouds to time-step length. Results show that 3-day ensembles of 20 to 50 members are sufficient to reproduce the main signals revealed by traditional 5-year simulations. A nudging technique is applied to an additional set of simulations to help understand the contribution of physics–dynamics interaction to the detected time-step sensitivity. In the second example, multiple empirical parameters related to cloud microphysics and aerosol life cycle are perturbed simultaneously in order to find out which parameters have the largest impact on the simulated global mean top-of-atmosphere radiation balance. It turns out that 12-member ensembles of 10-day simulations are able to reveal the same sensitivities as seen in 4-year simulations performed in a previous study. In both cases, the ensemble method reduces the total computational time by a factor of about 15, and the turnaround time by a factor of several hundred. The efficiency of the method makes it particularly useful for the development of

  17. Implementation and use of Gaussian process meta model for sensitivity analysis of numerical models: application to a hydrogeological transport computer code

    International Nuclear Information System (INIS)

    Marrel, A.

    2008-01-01

    In the studies of environmental transfer and risk assessment, numerical models are used to simulate, understand and predict the transfer of pollutant. These computer codes can depend on a high number of uncertain input parameters (geophysical variables, chemical parameters, etc.) and can be often too computer time expensive. To conduct uncertainty propagation studies and to measure the importance of each input on the response variability, the computer code has to be approximated by a meta model which is build on an acceptable number of simulations of the code and requires a negligible calculation time. We focused our research work on the use of Gaussian process meta model to make the sensitivity analysis of the code. We proposed a methodology with estimation and input selection procedures in order to build the meta model in the case of a high number of inputs and with few simulations available. Then, we compared two approaches to compute the sensitivity indices with the meta model and proposed an algorithm to build prediction intervals for these indices. Afterwards, we were interested in the choice of the code simulations. We studied the influence of different sampling strategies on the predictiveness of the Gaussian process meta model. Finally, we extended our statistical tools to a functional output of a computer code. We combined a decomposition on a wavelet basis with the Gaussian process modelling before computing the functional sensitivity indices. All the tools and statistical methodologies that we developed were applied to the real case of a complex hydrogeological computer code, simulating radionuclide transport in groundwater. (author) [fr

  18. Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

    Science.gov (United States)

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

    2015-01-01

    Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation. PMID:25560674

  19. Illustrating sensitivity in environmental fate models using partitioning maps - application to selected contaminants

    Energy Technology Data Exchange (ETDEWEB)

    Meyer, T.; Wania, F. [Univ. of Toronto at Scarborough - DPES, Toronto (Canada)

    2004-09-15

    Generic environmental multimedia fate models are important tools in the assessment of the impact of organic pollutants. Because of limited possibilities to evaluate generic models by comparison with measured data and the increasing regulatory use of such models, uncertainties of model input and output are of considerable concern. This led to a demand for sensitivity and uncertainty analyses for the outputs of environmental fate models. Usually, variations of model predictions of the environmental fate of organic contaminants are analyzed for only one or at most a few selected chemicals, even though parameter sensitivity and contribution to uncertainty are widely different for different chemicals. We recently presented a graphical method that allows for the comprehensive investigation of model sensitivity and uncertainty for all neutral organic chemicals simultaneously. This is achieved by defining a two-dimensional hypothetical ''chemical space'' as a function of the equilibrium partition coefficients between air, water, and octanol (K{sub OW}, K{sub AW}, K{sub OA}), and plotting sensitivity and/or uncertainty of a specific model result to each input parameter as function of this chemical space. Here we show how such sensitivity maps can be used to quickly identify the variables with the highest influence on the environmental fate of selected, chlorobenzenes, polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), hexachlorocyclohexanes (HCHs) and brominated flame retardents (BFRs).

  20. Global sensitivity analysis of a filtration model for submerged anaerobic membrane bioreactors (AnMBR).

    Science.gov (United States)

    Robles, A; Ruano, M V; Ribes, J; Seco, A; Ferrer, J

    2014-04-01

    The results of a global sensitivity analysis of a filtration model for submerged anaerobic MBRs (AnMBRs) are assessed in this paper. This study aimed to (1) identify the less- (or non-) influential factors of the model in order to facilitate model calibration and (2) validate the modelling approach (i.e. to determine the need for each of the proposed factors to be included in the model). The sensitivity analysis was conducted using a revised version of the Morris screening method. The dynamic simulations were conducted using long-term data obtained from an AnMBR plant fitted with industrial-scale hollow-fibre membranes. Of the 14 factors in the model, six were identified as influential, i.e. those calibrated using off-line protocols. A dynamic calibration (based on optimisation algorithms) of these influential factors was conducted. The resulting estimated model factors accurately predicted membrane performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. Sensitivity analysis of specific activity model parameters for environmental transport of 3H and dose assessment

    International Nuclear Information System (INIS)

    Rout, S.; Mishra, D.G.; Ravi, P.M.; Tripathi, R.M.

    2016-01-01

    Tritium is one of the radionuclides likely to get released to the environment from Pressurized Heavy Water Reactors. Environmental models are extensively used to quantify the complex environmental transport processes of radionuclides and also to assess the impact to the environment. Model parameters exerting the significant influence on model results are identified through a sensitivity analysis (SA). SA is the study of how the variation (uncertainty) in the output of a mathematical model can be apportioned, qualitatively or quantitatively, to different sources of variation in the input parameters. This study was designed to identify the sensitive model parameters of specific activity model (TRS 1616, IAEA) for environmental transfer of 3 H following release to air and then to vegetation and animal products. Model includes parameters such as air to soil transfer factor (CRs), Tissue Free Water 3 H to Organically Bound 3 H ratio (Rp), Relative humidity (RH), WCP (fractional water content) and WEQp (water equivalent factor) any change in these parameters leads to change in 3 H level in vegetation and animal products consequently change in dose due to ingestion. All these parameters are function of climate and/or plant which change with time, space and species. Estimation of these parameters at every time is a time consuming and also required sophisticated instrumentation. Therefore it is necessary to identify the sensitive parameters and freeze the values of least sensitive parameters at constant values for more accurate estimation of 3 H dose in short time for routine assessment

  2. Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT.

    Science.gov (United States)

    Luo, Yuzhou; Zhang, Minghua

    2009-12-01

    The Soil and Water Assessment Tool (SWAT) was calibrated for hydrology conditions in an agricultural watershed of Orestimba Creek, California, and applied to simulate fate and transport of two organophosphate pesticides chlorpyrifos and diazinon. The model showed capability in evaluating pesticide fate and transport processes in agricultural fields and instream network. Management-oriented sensitivity analysis was conducted by applied stochastic SWAT simulations for pesticide distribution. Results of sensitivity analysis identified the governing processes in pesticide outputs as surface runoff, soil erosion, and sedimentation in the study area. By incorporating sensitive parameters in pesticide transport simulation, effects of structural best management practices (BMPs) in improving surface water quality were demonstrated by SWAT modeling. This study also recommends conservation practices designed to reduce field yield and in-stream transport capacity of sediment, such as filter strip, grassed waterway, crop residue management, and tailwater pond to be implemented in the Orestimba Creek watershed.

  3. Sensitivity of APSIM/ORYZA model due to estimation errors in solar radiation

    Directory of Open Access Journals (Sweden)

    Alexandre Bryan Heinemann

    2012-01-01

    Full Text Available Crop models are ideally suited to quantify existing climatic risks. However, they require historic climate data as input. While daily temperature and rainfall data are often available, the lack of observed solar radiation (Rs data severely limits site-specific crop modelling. The objective of this study was to estimate Rs based on air temperature solar radiation models and to quantify the propagation of errors in simulated radiation on several APSIM/ORYZA crop model seasonal outputs, yield, biomass, leaf area (LAI and total accumulated solar radiation (SRA during the crop cycle. The accuracy of the 5 models for estimated daily solar radiation was similar, and it was not substantially different among sites. For water limited environments (no irrigation, crop model outputs yield, biomass and LAI was not sensitive for the uncertainties in radiation models studied here.

  4. Modelling Nd-isotopes with a coarse resolution ocean circulation model: Sensitivities to model parameters and source/sink distributions

    International Nuclear Information System (INIS)

    Rempfer, Johannes; Stocker, Thomas F.; Joos, Fortunat; Dutay, Jean-Claude; Siddall, Mark

    2011-01-01

    The neodymium (Nd) isotopic composition (Nd) of seawater is a quasi-conservative tracer of water mass mixing and is assumed to hold great potential for paleo-oceanographic studies. Here we present a comprehensive approach for the simulation of the two neodymium isotopes 143 Nd, and 144 Nd using the Bern3D model, a low resolution ocean model. The high computational efficiency of the Bern3D model in conjunction with our comprehensive approach allows us to systematically and extensively explore the sensitivity of Nd concentrations and ε Nd to the parametrisation of sources and sinks. Previous studies have been restricted in doing so either by the chosen approach or by computational costs. Our study thus presents the most comprehensive survey of the marine Nd cycle to date. Our model simulates both Nd concentrations as well as ε Nd in good agreement with observations. ε Nd co-varies with salinity, thus underlining its potential as a water mass proxy. Results confirm that the continental margins are required as a Nd source to simulate Nd concentrations and ε Nd consistent with observations. We estimate this source to be slightly smaller than reported in previous studies and find that above a certain magnitude its magnitude affects ε Nd only to a small extent. On the other hand, the parametrisation of the reversible scavenging considerably affects the ability of the model to simulate both, Nd concentrations and ε Nd . Furthermore, despite their small contribution, we find dust and rivers to be important components of the Nd cycle. In additional experiments, we systematically varied the diapycnal diffusivity as well as the Atlantic-to-Pacific freshwater flux to explore the sensitivity of Nd concentrations and its isotopic signature to the strength and geometry of the overturning circulation. These experiments reveal that Nd concentrations and ε Nd are comparatively little affected by variations in diapycnal diffusivity and the Atlantic-to-Pacific freshwater flux

  5. Emulation of a complex global aerosol model to quantify sensitivity to uncertain parameters

    Directory of Open Access Journals (Sweden)

    L. A. Lee

    2011-12-01

    Full Text Available Sensitivity analysis of atmospheric models is necessary to identify the processes that lead to uncertainty in model predictions, to help understand model diversity through comparison of driving processes, and to prioritise research. Assessing the effect of parameter uncertainty in complex models is challenging and often limited by CPU constraints. Here we present a cost-effective application of variance-based sensitivity analysis to quantify the sensitivity of a 3-D global aerosol model to uncertain parameters. A Gaussian process emulator is used to estimate the model output across multi-dimensional parameter space, using information from a small number of model runs at points chosen using a Latin hypercube space-filling design. Gaussian process emulation is a Bayesian approach that uses information from the model runs along with some prior assumptions about the model behaviour to predict model output everywhere in the uncertainty space. We use the Gaussian process emulator to calculate the percentage of expected output variance explained by uncertainty in global aerosol model parameters and their interactions. To demonstrate the technique, we show examples of cloud condensation nuclei (CCN sensitivity to 8 model parameters in polluted and remote marine environments as a function of altitude. In the polluted environment 95 % of the variance of CCN concentration is described by uncertainty in the 8 parameters (excluding their interaction effects and is dominated by the uncertainty in the sulphur emissions, which explains 80 % of the variance. However, in the remote region parameter interaction effects become important, accounting for up to 40 % of the total variance. Some parameters are shown to have a negligible individual effect but a substantial interaction effect. Such sensitivities would not be detected in the commonly used single parameter perturbation experiments, which would therefore underpredict total uncertainty. Gaussian process

  6. Sensitivity Analysis of a Physiochemical Interaction Model ...

    African Journals Online (AJOL)

    In this analysis, we will study the sensitivity analysis due to a variation of the initial condition and experimental time. These results which we have not seen elsewhere are analysed and discussed quantitatively. Keywords: Passivation Rate, Sensitivity Analysis, ODE23, ODE45 J. Appl. Sci. Environ. Manage. June, 2012, Vol.

  7. Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models

    International Nuclear Information System (INIS)

    Lamboni, Matieyendou; Monod, Herve; Makowski, David

    2011-01-01

    Many dynamic models are used for risk assessment and decision support in ecology and crop science. Such models generate time-dependent model predictions, with time either discretised or continuous. Their global sensitivity analysis is usually applied separately on each time output, but Campbell et al. (2006 ) advocated global sensitivity analyses on the expansion of the dynamics in a well-chosen functional basis. This paper focuses on the particular case when principal components analysis is combined with analysis of variance. In addition to the indices associated with the principal components, generalised sensitivity indices are proposed to synthesize the influence of each parameter on the whole time series output. Index definitions are given when the uncertainty on the input factors is either discrete or continuous and when the dynamic model is either discrete or functional. A general estimation algorithm is proposed, based on classical methods of global sensitivity analysis. The method is applied to a dynamic wheat crop model with 13 uncertain parameters. Three methods of global sensitivity analysis are compared: the Sobol'-Saltelli method, the extended FAST method, and the fractional factorial design of resolution 6.

  8. Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models

    Energy Technology Data Exchange (ETDEWEB)

    Lamboni, Matieyendou [INRA, Unite MIA (UR341), F78352 Jouy en Josas Cedex (France); Monod, Herve, E-mail: herve.monod@jouy.inra.f [INRA, Unite MIA (UR341), F78352 Jouy en Josas Cedex (France); Makowski, David [INRA, UMR Agronomie INRA/AgroParisTech (UMR 211), BP 01, F78850 Thiverval-Grignon (France)

    2011-04-15

    Many dynamic models are used for risk assessment and decision support in ecology and crop science. Such models generate time-dependent model predictions, with time either discretised or continuous. Their global sensitivity analysis is usually applied separately on each time output, but Campbell et al. (2006) advocated global sensitivity analyses on the expansion of the dynamics in a well-chosen functional basis. This paper focuses on the particular case when principal components analysis is combined with analysis of variance. In addition to the indices associated with the principal components, generalised sensitivity indices are proposed to synthesize the influence of each parameter on the whole time series output. Index definitions are given when the uncertainty on the input factors is either discrete or continuous and when the dynamic model is either discrete or functional. A general estimation algorithm is proposed, based on classical methods of global sensitivity analysis. The method is applied to a dynamic wheat crop model with 13 uncertain parameters. Three methods of global sensitivity analysis are compared: the Sobol'-Saltelli method, the extended FAST method, and the fractional factorial design of resolution 6.

  9. Land Sensitivity Analysis of Degradation using MEDALUS model: Case Study of Deliblato Sands, Serbia

    Directory of Open Access Journals (Sweden)

    Kadović Ratko

    2016-12-01

    Full Text Available This paper studies the assessment of sensitivity to land degradation of Deliblato sands (the northern part of Serbia, as a special nature reserve. Sandy soils of Deliblato sands are highly sensitive to degradation (given their fragility, while the system of land use is regulated according to the law, consisting of three zones under protection. Based on the MEDALUS approach and the characteristics of the study area, four main factors were considered for evaluation: soil, climate, vegetation and management. Several indicators affecting the quality of each factor were identified. Each indicator was quantified according to its quality and given a weighting of between 1.0 and 2.0. ArcGIS 9 was utilized to analyze and prepare the layers of quality maps, using the geometric mean to integrate the individual indicator map. In turn, the geometric mean of all four quality indices was used to generate sensitivity of land degradation status map. Results showed that 56.26% of the area is classified as critical; 43.18% as fragile; 0.55% as potentially affected and 0.01% as not affected by degradation. The values of vegetation quality index, expressed as coverage, diversity of vegetation functions and management policy during the protection regime are clearly represented through correlation coefficient (0.87 and 0.47.

  10. Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization

    Energy Technology Data Exchange (ETDEWEB)

    Alves, Vinicius M. [Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220 (Brazil); Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Muratov, Eugene [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Laboratory of Theoretical Chemistry, A.V. Bogatsky Physical–Chemical Institute NAS of Ukraine, Odessa 65080 (Ukraine); Fourches, Denis [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States); Strickland, Judy; Kleinstreuer, Nicole [ILS/Contractor supporting the NTP Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), P.O. Box 13501, Research Triangle Park, NC 27709 (United States); Andrade, Carolina H. [Laboratory of Molecular Modeling and Design, Faculty of Pharmacy, Federal University of Goiás, Goiânia, GO 74605-220 (Brazil); Tropsha, Alexander, E-mail: alex_tropsha@unc.edu [Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC 27599 (United States)

    2015-04-15

    Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability. Based on the largest publicly available dataset compiled in this study, we found no overall correlation between skin permeability and skin sensitization. In addition, cross-species correlation coefficient between human and rodent permeability data was found to be as low as R{sup 2} = 0.44. Human skin permeability models based on the random forest method have been developed and validated using OECD-compliant QSAR modeling workflow. Their external accuracy was high (Q{sup 2}{sub ext} = 0.73 for 63% of external compounds inside the applicability domain). The extended analysis using both experimentally-measured and QSAR-imputed data still confirmed the absence of any overall concordance between skin permeability and skin sensitization. This observation suggests that chemical modifications that affect skin permeability should not be presumed a priori to modulate the sensitization potential of chemicals. The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential. - Highlights: • It was compiled the largest publicly-available skin permeability dataset. • Predictive QSAR models were developed for skin permeability. • No concordance between skin

  11. Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization

    International Nuclear Information System (INIS)

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

    2015-01-01

    Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability. Based on the largest publicly available dataset compiled in this study, we found no overall correlation between skin permeability and skin sensitization. In addition, cross-species correlation coefficient between human and rodent permeability data was found to be as low as R 2 = 0.44. Human skin permeability models based on the random forest method have been developed and validated using OECD-compliant QSAR modeling workflow. Their external accuracy was high (Q 2 ext = 0.73 for 63% of external compounds inside the applicability domain). The extended analysis using both experimentally-measured and QSAR-imputed data still confirmed the absence of any overall concordance between skin permeability and skin sensitization. This observation suggests that chemical modifications that affect skin permeability should not be presumed a priori to modulate the sensitization potential of chemicals. The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential. - Highlights: • It was compiled the largest publicly-available skin permeability dataset. • Predictive QSAR models were developed for skin permeability. • No concordance between skin sensitization and

  12. Uncertainty and sensitivity studies supporting the interpretation of the results of TVO I/II PRA

    International Nuclear Information System (INIS)

    Holmberg, J.

    1992-01-01

    A comprehensive Level 1 probabilistic risk assessment (PRA) has been performed for the TVO I/II nuclear power units. As a part of the PRA project, uncertainties of risk models and methods were systematically studied in order to describe them and to demonstrate their impact by way of results. The uncertainty study was divided into two phases: a qualitative and a quantitative study. The qualitative study contained identification of uncertainties and qualitative assessments of their importance. The PRA was introduced, and identified assumptions and uncertainties behind the models were documented. The most significant uncertainties were selected by importance measures or other judgements for further quantitative studies. The quantitative study included sensitivity studies and propagation of uncertainty ranges. In the sensitivity studies uncertain assumptions or parameters were varied in order to illustrate the sensitivity of the models. The propagation of the uncertainty ranges demonstrated the impact of the statistical uncertainties of the parameter values. The Monte Carlo method was used as a propagation method. The most significant uncertainties were those involved in modelling human interactions, dependences and common cause failures (CCFs), loss of coolant accident (LOCA) frequencies and pressure suppression. The qualitative mapping out of the uncertainty factors turned out to be useful in planning quantitative studies. It also served as internal review of the assumptions made in the PRA. The sensitivity studies were perhaps the most advantageous part of the quantitative study because they allowed individual analyses of the significance of uncertainty sources identified. The uncertainty study was found reasonable in systematically and critically assessing uncertainties in a risk analysis. The usefulness of this study depends on the decision maker (power company) since uncertainty studies are primarily carried out to support decision making when uncertainties are

  13. Sensitivity of wildlife habitat models to uncertainties in GIS data

    Science.gov (United States)

    Stoms, David M.; Davis, Frank W.; Cogan, Christopher B.

    1992-01-01

    Decision makers need to know the reliability of output products from GIS analysis. For many GIS applications, it is not possible to compare these products to an independent measure of 'truth'. Sensitivity analysis offers an alternative means of estimating reliability. In this paper, we present a CIS-based statistical procedure for estimating the sensitivity of wildlife habitat models to uncertainties in input data and model assumptions. The approach is demonstrated in an analysis of habitat associations derived from a GIS database for the endangered California condor. Alternative data sets were generated to compare results over a reasonable range of assumptions about several sources of uncertainty. Sensitivity analysis indicated that condor habitat associations are relatively robust, and the results have increased our confidence in our initial findings. Uncertainties and methods described in the paper have general relevance for many GIS applications.

  14. On Approaches to Analyze the Sensitivity of Simulated Hydrologic Fluxes to Model Parameters in the Community Land Model

    Directory of Open Access Journals (Sweden)

    Jie Bao

    2015-12-01

    Full Text Available Effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash–Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA approaches, including analysis of variance based on the generalized linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.

  15. Global sensitivity analysis for an integrated model for simulation of nitrogen dynamics under the irrigation with treated wastewater.

    Science.gov (United States)

    Sun, Huaiwei; Zhu, Yan; Yang, Jinzhong; Wang, Xiugui

    2015-11-01

    As the amount of water resources that can be utilized for agricultural production is limited, the reuse of treated wastewater (TWW) for irrigation is a practical solution to alleviate the water crisis in China. The process-based models, which estimate nitrogen dynamics under irrigation, are widely used to investigate the best irrigation and fertilization management practices in developed and developing countries. However, for modeling such a complex system for wastewater reuse, it is critical to conduct a sensitivity analysis to determine numerous input parameters and their interactions that contribute most to the variance of the model output for the development of process-based model. In this study, application of a comprehensive global sensitivity analysis for nitrogen dynamics was reported. The objective was to compare different global sensitivity analysis (GSA) on the key parameters for different model predictions of nitrogen and crop growth modules. The analysis was performed as two steps. Firstly, Morris screening method, which is one of the most commonly used screening method, was carried out to select the top affected parameters; then, a variance-based global sensitivity analysis method (extended Fourier amplitude sensitivity test, EFAST) was used to investigate more thoroughly the effects of selected parameters on model predictions. The results of GSA showed that strong parameter interactions exist in crop nitrogen uptake, nitrogen denitrification, crop yield, and evapotranspiration modules. Among all parameters, one of the soil physical-related parameters named as the van Genuchten air entry parameter showed the largest sensitivity effects on major model predictions. These results verified that more effort should be focused on quantifying soil parameters for more accurate model predictions in nitrogen- and crop-related predictions, and stress the need to better calibrate the model in a global sense. This study demonstrates the advantages of the GSA on a

  16. Sensitivity analysis practices: Strategies for model-based inference

    Energy Technology Data Exchange (ETDEWEB)

    Saltelli, Andrea [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (Vatican City State, Holy See,) (Italy)]. E-mail: andrea.saltelli@jrc.it; Ratto, Marco [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy); Tarantola, Stefano [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy); Campolongo, Francesca [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy)

    2006-10-15

    Fourteen years after Science's review of sensitivity analysis (SA) methods in 1989 (System analysis at molecular scale, by H. Rabitz) we search Science Online to identify and then review all recent articles having 'sensitivity analysis' as a keyword. In spite of the considerable developments which have taken place in this discipline, of the good practices which have emerged, and of existing guidelines for SA issued on both sides of the Atlantic, we could not find in our review other than very primitive SA tools, based on 'one-factor-at-a-time' (OAT) approaches. In the context of model corroboration or falsification, we demonstrate that this use of OAT methods is illicit and unjustified, unless the model under analysis is proved to be linear. We show that available good practices, such as variance based measures and others, are able to overcome OAT shortcomings and easy to implement. These methods also allow the concept of factors importance to be defined rigorously, thus making the factors importance ranking univocal. We analyse the requirements of SA in the context of modelling, and present best available practices on the basis of an elementary model. We also point the reader to available recipes for a rigorous SA.

  17. Sensitivity analysis practices: Strategies for model-based inference

    International Nuclear Information System (INIS)

    Saltelli, Andrea; Ratto, Marco; Tarantola, Stefano; Campolongo, Francesca

    2006-01-01

    Fourteen years after Science's review of sensitivity analysis (SA) methods in 1989 (System analysis at molecular scale, by H. Rabitz) we search Science Online to identify and then review all recent articles having 'sensitivity analysis' as a keyword. In spite of the considerable developments which have taken place in this discipline, of the good practices which have emerged, and of existing guidelines for SA issued on both sides of the Atlantic, we could not find in our review other than very primitive SA tools, based on 'one-factor-at-a-time' (OAT) approaches. In the context of model corroboration or falsification, we demonstrate that this use of OAT methods is illicit and unjustified, unless the model under analysis is proved to be linear. We show that available good practices, such as variance based measures and others, are able to overcome OAT shortcomings and easy to implement. These methods also allow the concept of factors importance to be defined rigorously, thus making the factors importance ranking univocal. We analyse the requirements of SA in the context of modelling, and present best available practices on the basis of an elementary model. We also point the reader to available recipes for a rigorous SA

  18. Sensitivity studies of unsaturated groundwater flow modeling for groundwater travel time calculations at Yucca Mountain, Nevada

    International Nuclear Information System (INIS)

    Altman, S.J.; Ho, C.K.; Arnold, B.W.; McKenna, S.A.

    1995-01-01

    Unsaturated flow has been modeled through four cross-sections at Yucca Mountain, Nevada, for the purpose of determining groundwater particle travel times from the potential repository to the water table. This work will be combined with the results of flow modeling in the saturated zone for the purpose of evaluating the suitability of the potential repository under the criteria of 10CFR960. One criterion states, in part, that the groundwater travel time (GWTT) from the repository to the accessible environment must exceed 1,000 years along the fastest path of likely and significant radionuclide travel. Sensitivity analyses have been conducted for one geostatistical realization of one cross-section for the purpose of (1) evaluating the importance of hydrological parameters having some uncertainty and (2) examining conceptual models of flow by altering the numerical implementation of the conceptual model (dual permeability (DK) and the equivalent continuum model (ECM). Results of comparisons of the ECM and DK model are also presented in Ho et al

  19. Wind climate estimation using WRF model output: method and model sensitivities over the sea

    DEFF Research Database (Denmark)

    Hahmann, Andrea N.; Vincent, Claire Louise; Peña, Alfredo

    2015-01-01

    setup parameters. The results of the year-long sensitivity simulations show that the long-term mean wind speed simulated by the WRF model offshore in the region studied is quite insensitive to the global reanalysis, the number of vertical levels, and the horizontal resolution of the sea surface...... temperature used as lower boundary conditions. Also, the strength and form (grid vs spectral) of the nudging is quite irrelevant for the mean wind speed at 100 m. Large sensitivity is found to the choice of boundary layer parametrization, and to the length of the period that is discarded as spin-up to produce...... a wind climatology. It is found that the spin-up period for the boundary layer winds is likely larger than 12 h over land and could affect the wind climatology for points offshore for quite a distance downstream from the coast....

  20. A Bayesian ensemble of sensitivity measures for severe accident modeling

    Energy Technology Data Exchange (ETDEWEB)

    Hoseyni, Seyed Mohsen [Department of Basic Sciences, East Tehran Branch, Islamic Azad University, Tehran (Iran, Islamic Republic of); Di Maio, Francesco, E-mail: francesco.dimaio@polimi.it [Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano (Italy); Vagnoli, Matteo [Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano (Italy); Zio, Enrico [Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano (Italy); Chair on System Science and Energetic Challenge, Fondation EDF – Electricite de France Ecole Centrale, Paris, and Supelec, Paris (France); Pourgol-Mohammad, Mohammad [Department of Mechanical Engineering, Sahand University of Technology, Tabriz (Iran, Islamic Republic of)

    2015-12-15

    Highlights: • We propose a sensitivity analysis (SA) method based on a Bayesian updating scheme. • The Bayesian updating schemes adjourns an ensemble of sensitivity measures. • Bootstrap replicates of a severe accident code output are fed to the Bayesian scheme. • The MELCOR code simulates the fission products release of LOFT LP-FP-2 experiment. • Results are compared with those of traditional SA methods. - Abstract: In this work, a sensitivity analysis framework is presented to identify the relevant input variables of a severe accident code, based on an incremental Bayesian ensemble updating method. The proposed methodology entails: (i) the propagation of the uncertainty in the input variables through the severe accident code; (ii) the collection of bootstrap replicates of the input and output of limited number of simulations for building a set of finite mixture models (FMMs) for approximating the probability density function (pdf) of the severe accident code output of the replicates; (iii) for each FMM, the calculation of an ensemble of sensitivity measures (i.e., input saliency, Hellinger distance and Kullback–Leibler divergence) and the updating when a new piece of evidence arrives, by a Bayesian scheme, based on the Bradley–Terry model for ranking the most relevant input model variables. An application is given with respect to a limited number of simulations of a MELCOR severe accident model describing the fission products release in the LP-FP-2 experiment of the loss of fluid test (LOFT) facility, which is a scaled-down facility of a pressurized water reactor (PWR).

  1. Hypersonic Separated Flows About "Tick" Configurations With Sensitivity to Model Design

    Science.gov (United States)

    Moss, J. N.; O'Byrne, S.; Gai, S. L.

    2014-01-01

    This paper presents computational results obtained by applying the direct simulation Monte Carlo (DSMC) method for hypersonic nonequilibrium flow about "tick-shaped" model configurations. These test models produces a complex flow where the nonequilibrium and rarefied aspects of the flow are initially enhanced as the flow passes over an expansion surface, and then the flow encounters a compression surface that can induce flow separation. The resulting flow is such that meaningful numerical simulations must have the capability to account for a significant range of rarefaction effects; hence the application of the DSMC method in the current study as the flow spans several flow regimes, including transitional, slip, and continuum. The current focus is to examine the sensitivity of both the model surface response (heating, friction and pressure) and flowfield structure to assumptions regarding surface boundary conditions and more extensively the impact of model design as influenced by leading edge configuration as well as the geometrical features of the expansion and compression surfaces. Numerical results indicate a strong sensitivity to both the extent of the leading edge sharpness and the magnitude of the leading edge bevel angle. Also, the length of the expansion surface for a fixed compression surface has a significant impact on the extent of separated flow.

  2. Development of the EM tomography system. Part 2. Sensitivity studies of anomalous body by model studies; EM tomography system no kaihatsu. 2. Model kaiseki ni yoru ijotai no kando chosa kekka

    Energy Technology Data Exchange (ETDEWEB)

    Kumekawa, Y; Miura, Y; Takasugi, S [GERD Geothermal Energy Research and Development Co. Ltd., Tokyo (Japan); Arai, E [Metal Mining Agency of Japan, Tokyo (Japan)

    1997-05-27

    A model analysis was used to investigate sensitivity of a two-dimensional structure on a resistivity anomalous body by using an electromagnetic tomography system. The resistivity model handled a three-dimensional structure. The model was prepared as a pseudo two-dimensional model in which a low resistivity anomalous body with 1 ohm-m was incorporated that has a basic length of 1000 m in the Y-direction in a homogenous medium having 100 ohm-m. As a result of the analysis, the following matters were elucidated: if a low resistivity anomalous body is present in a shallow subsurface, its impact starts appearing from lower frequencies than when the anomalous body exists only at a greater depth; if a high resistivity anomalous body exists, the detection sensitivity is lower than for the low resistivity anomalous body, but the analysis would be possible by using the phase because the phase has made a greater change; the source TxZ shows a change from lower frequencies than for the source TxX, and the amount of change is greater, hence the detection sensitivity on an anomalous body may be said higher with the source TxZ; however, for the anomalous body in shallow subsurface, the source TxX is more effective since it is not subjected to a too great impact at a greater depth. 5 refs., 7 figs.

  3. Sensitivity of precipitation to parameter values in the community atmosphere model version 5

    Energy Technology Data Exchange (ETDEWEB)

    Johannesson, Gardar; Lucas, Donald; Qian, Yun; Swiler, Laura Painton; Wildey, Timothy Michael

    2014-03-01

    One objective of the Climate Science for a Sustainable Energy Future (CSSEF) program is to develop the capability to thoroughly test and understand the uncertainties in the overall climate model and its components as they are being developed. The focus on uncertainties involves sensitivity analysis: the capability to determine which input parameters have a major influence on the output responses of interest. This report presents some initial sensitivity analysis results performed by Lawrence Livermore National Laboratory (LNNL), Sandia National Laboratories (SNL), and Pacific Northwest National Laboratory (PNNL). In the 2011-2012 timeframe, these laboratories worked in collaboration to perform sensitivity analyses of a set of CAM5, 2° runs, where the response metrics of interest were precipitation metrics. The three labs performed their sensitivity analysis (SA) studies separately and then compared results. Overall, the results were quite consistent with each other although the methods used were different. This exercise provided a robustness check of the global sensitivity analysis metrics and identified some strongly influential parameters.

  4. A surrogate-based sensitivity quantification and Bayesian inversion of a regional groundwater flow model

    Science.gov (United States)

    Chen, Mingjie; Izady, Azizallah; Abdalla, Osman A.; Amerjeed, Mansoor

    2018-02-01

    Bayesian inference using Markov Chain Monte Carlo (MCMC) provides an explicit framework for stochastic calibration of hydrogeologic models accounting for uncertainties; however, the MCMC sampling entails a large number of model calls, and could easily become computationally unwieldy if the high-fidelity hydrogeologic model simulation is time consuming. This study proposes a surrogate-based Bayesian framework to address this notorious issue, and illustrates the methodology by inverse modeling a regional MODFLOW model. The high-fidelity groundwater model is approximated by a fast statistical model using Bagging Multivariate Adaptive Regression Spline (BMARS) algorithm, and hence the MCMC sampling can be efficiently performed. In this study, the MODFLOW model is developed to simulate the groundwater flow in an arid region of Oman consisting of mountain-coast aquifers, and used to run representative simulations to generate training dataset for BMARS model construction. A BMARS-based Sobol' method is also employed to efficiently calculate input parameter sensitivities, which are used to evaluate and rank their importance for the groundwater flow model system. According to sensitivity analysis, insensitive parameters are screened out of Bayesian inversion of the MODFLOW model, further saving computing efforts. The posterior probability distribution of input parameters is efficiently inferred from the prescribed prior distribution using observed head data, demonstrating that the presented BMARS-based Bayesian framework is an efficient tool to reduce parameter uncertainties of a groundwater system.

  5. Probability density function shape sensitivity in the statistical modeling of turbulent particle dispersion

    Science.gov (United States)

    Litchford, Ron J.; Jeng, San-Mou

    1992-01-01

    The performance of a recently introduced statistical transport model for turbulent particle dispersion is studied here for rigid particles injected into a round turbulent jet. Both uniform and isosceles triangle pdfs are used. The statistical sensitivity to parcel pdf shape is demonstrated.

  6. Modelling ecological and human exposure to POPs in Venice lagoon - Part II: Quantitative uncertainty and sensitivity analysis in coupled exposure models.

    Science.gov (United States)

    Radomyski, Artur; Giubilato, Elisa; Ciffroy, Philippe; Critto, Andrea; Brochot, Céline; Marcomini, Antonio

    2016-11-01

    The study is focused on applying uncertainty and sensitivity analysis to support the application and evaluation of large exposure models where a significant number of parameters and complex exposure scenarios might be involved. The recently developed MERLIN-Expo exposure modelling tool was applied to probabilistically assess the ecological and human exposure to PCB 126 and 2,3,7,8-TCDD in the Venice lagoon (Italy). The 'Phytoplankton', 'Aquatic Invertebrate', 'Fish', 'Human intake' and PBPK models available in MERLIN-Expo library were integrated to create a specific food web to dynamically simulate bioaccumulation in various aquatic species and in the human body over individual lifetimes from 1932 until 1998. MERLIN-Expo is a high tier exposure modelling tool allowing propagation of uncertainty on the model predictions through Monte Carlo simulation. Uncertainty in model output can be further apportioned between parameters by applying built-in sensitivity analysis tools. In this study, uncertainty has been extensively addressed in the distribution functions to describe the data input and the effect on model results by applying sensitivity analysis techniques (screening Morris method, regression analysis, and variance-based method EFAST). In the exposure scenario developed for the Lagoon of Venice, the concentrations of 2,3,7,8-TCDD and PCB 126 in human blood turned out to be mainly influenced by a combination of parameters (half-lives of the chemicals, body weight variability, lipid fraction, food assimilation efficiency), physiological processes (uptake/elimination rates), environmental exposure concentrations (sediment, water, food) and eating behaviours (amount of food eaten). In conclusion, this case study demonstrated feasibility of MERLIN-Expo to be successfully employed in integrated, high tier exposure assessment. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Stability and Sensitive Analysis of a Model with Delay Quorum Sensing

    Directory of Open Access Journals (Sweden)

    Zhonghua Zhang

    2015-01-01

    Full Text Available This paper formulates a delay model characterizing the competition between bacteria and immune system. The center manifold reduction method and the normal form theory due to Faria and Magalhaes are used to compute the normal form of the model, and the stability of two nonhyperbolic equilibria is discussed. Sensitivity analysis suggests that the growth rate of bacteria is the most sensitive parameter of the threshold parameter R0 and should be targeted in the controlling strategies.

  8. Uncertainty and sensitivity analyses for age-dependent unavailability model integrating test and maintenance

    International Nuclear Information System (INIS)

    Kančev, Duško; Čepin, Marko

    2012-01-01

    Highlights: ► Application of analytical unavailability model integrating T and M, ageing, and test strategy. ► Ageing data uncertainty propagation on system level assessed via Monte Carlo simulation. ► Uncertainty impact is growing with the extension of the surveillance test interval. ► Calculated system unavailability dependence on two different sensitivity study ageing databases. ► System unavailability sensitivity insights regarding specific groups of BEs as test intervals extend. - Abstract: The interest in operational lifetime extension of the existing nuclear power plants is growing. Consequently, plants life management programs, considering safety components ageing, are being developed and employed. Ageing represents a gradual degradation of the physical properties and functional performance of different components consequently implying their reduced availability. Analyses, which are being made in the direction of nuclear power plants lifetime extension are based upon components ageing management programs. On the other side, the large uncertainties of the ageing parameters as well as the uncertainties associated with most of the reliability data collections are widely acknowledged. This paper addresses the uncertainty and sensitivity analyses conducted utilizing a previously developed age-dependent unavailability model, integrating effects of test and maintenance activities, for a selected stand-by safety system in a nuclear power plant. The most important problem is the lack of data concerning the effects of ageing as well as the relatively high uncertainty associated to these data, which would correspond to more detailed modelling of ageing. A standard Monte Carlo simulation was coded for the purpose of this paper and utilized in the process of assessment of the component ageing parameters uncertainty propagation on system level. The obtained results from the uncertainty analysis indicate the extent to which the uncertainty of the selected

  9. The sensitivity of catchment runoff models to rainfall data at different spatial scales

    Directory of Open Access Journals (Sweden)

    V. A. Bell

    2000-01-01

    Full Text Available The sensitivity of catchment runoff models to rainfall is investigated at a variety of spatial scales using data from a dense raingauge network and weather radar. These data form part of the HYREX (HYdrological Radar EXperiment dataset. They encompass records from 49 raingauges over the 135 km2 Brue catchment in south-west England together with 2 and 5 km grid-square radar data. Separate rainfall time-series for the radar and raingauge data are constructed on 2, 5 and 10 km grids, and as catchment average values, at a 15 minute time-step. The sensitivity of the catchment runoff models to these grid scales of input data is evaluated on selected convective and stratiform rainfall events. Each rainfall time-series is used to produce an ensemble of modelled hydrographs in order to investigate this sensitivity. The distributed model is shown to be sensitive to the locations of the raingauges within the catchment and hence to the spatial variability of rainfall over the catchment. Runoff sensitivity is strongest during convective rainfall when a broader spread of modelled hydrographs results, with twice the variability of that arising from stratiform rain. Sensitivity to rainfall data and model resolution is explored and, surprisingly, best performance is obtained using a lower resolution of rainfall data and model. Results from the distributed catchment model, the Simple Grid Model, are compared with those obtained from a lumped model, the PDM. Performance from the distributed model is found to be only marginally better during stratiform rain (R2 of 0.922 compared to 0.911 but significantly better during convective rain (R2 of 0.953 compared to 0.909. The improved performance from the distributed model can, in part, be accredited to the excellence of the dense raingauge network which would not be the norm for operational flood warning systems. In the final part of the paper, the effect of rainfall resolution on the performance of the 2 km distributed

  10. Parametric Sensitivity Study of Operating and Design Variables in Wellbore Heat Exchangers

    International Nuclear Information System (INIS)

    Nalla, G.; Shook, G.M.; Mines, G.L.; Bloomfield, K.K.

    2004-01-01

    This report documents the results of an extensive sensitivity study conducted by the Idaho National Engineering and Environmental Laboratory. This study investigated the effects of various operating and design parameters on wellbore heat exchanger performance to determine conditions for optimal thermal energy extraction and evaluate the potential for using a wellbore heat exchanger model for power generation. Variables studied included operational parameters such as circulation rates, wellbore geometries and working fluid properties, and regional properties including basal heat flux and formation rock type. Energy extraction is strongly affected by fluid residence time, heat transfer contact area, and formation thermal properties. Water appears to be the most appropriate working fluid. Aside from minimal tubing insulation, tubing properties are second order effects. On the basis of the sensitivity study, a best case model was simulated and the results compared against existing low-temperature power generation plants. Even assuming ideal work conversion to electric power, a wellbore heat exchange model cannot generate 200 kW (682.4e+3 BTU/h) at the onset of pseudosteady state. Using realistic conversion efficiency, the method is unlikely to generate 50 kW (170.6e+3 BTU/h)

  11. Natural Ocean Carbon Cycle Sensitivity to Parameterizations of the Recycling in a Climate Model

    Science.gov (United States)

    Romanou, A.; Romanski, J.; Gregg, W. W.

    2014-01-01

    Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10 %) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34 %, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which

  12. Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT

    International Nuclear Information System (INIS)

    Luo Yuzhou; Zhang Minghua

    2009-01-01

    The Soil and Water Assessment Tool (SWAT) was calibrated for hydrology conditions in an agricultural watershed of Orestimba Creek, California, and applied to simulate fate and transport of two organophosphate pesticides chlorpyrifos and diazinon. The model showed capability in evaluating pesticide fate and transport processes in agricultural fields and instream network. Management-oriented sensitivity analysis was conducted by applied stochastic SWAT simulations for pesticide distribution. Results of sensitivity analysis identified the governing processes in pesticide outputs as surface runoff, soil erosion, and sedimentation in the study area. By incorporating sensitive parameters in pesticide transport simulation, effects of structural best management practices (BMPs) in improving surface water quality were demonstrated by SWAT modeling. This study also recommends conservation practices designed to reduce field yield and in-stream transport capacity of sediment, such as filter strip, grassed waterway, crop residue management, and tailwater pond to be implemented in the Orestimba Creek watershed. - Selected structural BMPs are recommended for reducing loads of OP pesticides.

  13. Management-oriented sensitivity analysis for pesticide transport in watershed-scale water quality modeling using SWAT

    Energy Technology Data Exchange (ETDEWEB)

    Luo Yuzhou [University of California, Davis, CA 95616 (United States); Wenzhou Medical College, Wenzhou 325035 (China); Zhang Minghua, E-mail: mhzhang@ucdavis.ed [University of California, Davis, CA 95616 (United States); Wenzhou Medical College, Wenzhou 325035 (China)

    2009-12-15

    The Soil and Water Assessment Tool (SWAT) was calibrated for hydrology conditions in an agricultural watershed of Orestimba Creek, California, and applied to simulate fate and transport of two organophosphate pesticides chlorpyrifos and diazinon. The model showed capability in evaluating pesticide fate and transport processes in agricultural fields and instream network. Management-oriented sensitivity analysis was conducted by applied stochastic SWAT simulations for pesticide distribution. Results of sensitivity analysis identified the governing processes in pesticide outputs as surface runoff, soil erosion, and sedimentation in the study area. By incorporating sensitive parameters in pesticide transport simulation, effects of structural best management practices (BMPs) in improving surface water quality were demonstrated by SWAT modeling. This study also recommends conservation practices designed to reduce field yield and in-stream transport capacity of sediment, such as filter strip, grassed waterway, crop residue management, and tailwater pond to be implemented in the Orestimba Creek watershed. - Selected structural BMPs are recommended for reducing loads of OP pesticides.

  14. Global sensitivity analysis in wastewater treatment plant model applications: Prioritizing sources of uncertainty

    DEFF Research Database (Denmark)

    Sin, Gürkan; Gernaey, Krist; Neumann, Marc B.

    2011-01-01

    This study demonstrates the usefulness of global sensitivity analysis in wastewater treatment plant (WWTP) design to prioritize sources of uncertainty and quantify their impact on performance criteria. The study, which is performed with the Benchmark Simulation Model no. 1 plant design, complements...... insight into devising useful ways for reducing uncertainties in the plant performance. This information can help engineers design robust WWTP plants....... a previous paper on input uncertainty characterisation and propagation (Sin et al., 2009). A sampling-based sensitivity analysis is conducted to compute standardized regression coefficients. It was found that this method is able to decompose satisfactorily the variance of plant performance criteria (with R2...

  15. Sensitivity of microwave ablation models to tissue biophysical properties: A first step toward probabilistic modeling and treatment planning.

    Science.gov (United States)

    Sebek, Jan; Albin, Nathan; Bortel, Radoslav; Natarajan, Bala; Prakash, Punit

    2016-05-01

    Computational models of microwave ablation (MWA) are widely used during the design optimization of novel devices and are under consideration for patient-specific treatment planning. The objective of this study was to assess the sensitivity of computational models of MWA to tissue biophysical properties. The Morris method was employed to assess the global sensitivity of the coupled electromagnetic-thermal model, which was implemented with the finite element method (FEM). The FEM model incorporated temperature dependencies of tissue physical properties. The variability of the model was studied using six different outputs to characterize the size and shape of the ablation zone, as well as impedance matching of the ablation antenna. Furthermore, the sensitivity results were statistically analyzed and absolute influence of each input parameter was quantified. A framework for systematically incorporating model uncertainties for treatment planning was suggested. A total of 1221 simulations, incorporating 111 randomly sampled starting points, were performed. Tissue dielectric parameters, specifically relative permittivity, effective conductivity, and the threshold temperature at which they transitioned to lower values (i.e., signifying desiccation), were identified as the most influential parameters for the shape of the ablation zone and antenna impedance matching. Of the thermal parameters considered in this study, the nominal blood perfusion rate and the temperature interval across which the tissue changes phase were identified as the most influential. The latent heat of tissue water vaporization and the volumetric heat capacity of the vaporized tissue were recognized as the least influential parameters. Based on the evaluation of absolute changes, the most important parameter (perfusion) had approximately 40.23 times greater influence on ablation area than the least important parameter (volumetric heat capacity of vaporized tissue). Another significant input parameter

  16. Toward a more robust variance-based global sensitivity analysis of model outputs

    Energy Technology Data Exchange (ETDEWEB)

    Tong, C

    2007-10-15

    Global sensitivity analysis (GSA) measures the variation of a model output as a function of the variations of the model inputs given their ranges. In this paper we consider variance-based GSA methods that do not rely on certain assumptions about the model structure such as linearity or monotonicity. These variance-based methods decompose the output variance into terms of increasing dimensionality called 'sensitivity indices', first introduced by Sobol' [25]. Sobol' developed a method of estimating these sensitivity indices using Monte Carlo simulations. McKay [13] proposed an efficient method using replicated Latin hypercube sampling to compute the 'correlation ratios' or 'main effects', which have been shown to be equivalent to Sobol's first-order sensitivity indices. Practical issues with using these variance estimators are how to choose adequate sample sizes and how to assess the accuracy of the results. This paper proposes a modified McKay main effect method featuring an adaptive procedure for accuracy assessment and improvement. We also extend our adaptive technique to the computation of second-order sensitivity indices. Details of the proposed adaptive procedure as wells as numerical results are included in this paper.

  17. Global sensitivity analysis of a dynamic model for gene expression in Drosophila embryos

    Science.gov (United States)

    McCarthy, Gregory D.; Drewell, Robert A.

    2015-01-01

    It is well known that gene regulation is a tightly controlled process in early organismal development. However, the roles of key processes involved in this regulation, such as transcription and translation, are less well understood, and mathematical modeling approaches in this field are still in their infancy. In recent studies, biologists have taken precise measurements of protein and mRNA abundance to determine the relative contributions of key factors involved in regulating protein levels in mammalian cells. We now approach this question from a mathematical modeling perspective. In this study, we use a simple dynamic mathematical model that incorporates terms representing transcription, translation, mRNA and protein decay, and diffusion in an early Drosophila embryo. We perform global sensitivity analyses on this model using various different initial conditions and spatial and temporal outputs. Our results indicate that transcription and translation are often the key parameters to determine protein abundance. This observation is in close agreement with the experimental results from mammalian cells for various initial conditions at particular time points, suggesting that a simple dynamic model can capture the qualitative behavior of a gene. Additionally, we find that parameter sensitivites are temporally dynamic, illustrating the importance of conducting a thorough global sensitivity analysis across multiple time points when analyzing mathematical models of gene regulation. PMID:26157608

  18. Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization

    Science.gov (United States)

    Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

    2015-01-01

    Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability. Based on the largest publicly available dataset compiled in this study, we found no overall correlation between skin permeability and skin sensitization. In addition, cross-species correlation coefficient between human and rodent permeability data was found to be as low as R2=0.44. Human skin permeability models based on the random forest method have been developed and validated using OECD-compliant QSAR modeling workflow. Their external accuracy was high (Q2ext = 0.73 for 63% of external compounds inside the applicability domain). The extended analysis using both experimentally-measured and QSAR-imputed data still confirmed the absence of any overall concordance between skin permeability and skin sensitization. This observation suggests that chemical modifications that affect skin permeability should not be presumed a priori to modulate the sensitization potential of chemicals. The models reported herein as well as those developed in the companion paper on skin sensitization suggest that it may be possible to rationally design compounds with the desired high skin permeability but low sensitization potential. PMID:25560673

  19. Sensitivity analysis using contribution to sample variance plot: Application to a water hammer model

    International Nuclear Information System (INIS)

    Tarantola, S.; Kopustinskas, V.; Bolado-Lavin, R.; Kaliatka, A.; Ušpuras, E.; Vaišnoras, M.

    2012-01-01

    This paper presents “contribution to sample variance plot”, a natural extension of the “contribution to the sample mean plot”, which is a graphical tool for global sensitivity analysis originally proposed by Sinclair. These graphical tools have a great potential to display graphically sensitivity information given a generic input sample and its related model realizations. The contribution to the sample variance can be obtained at no extra computational cost, i.e. from the same points used for deriving the contribution to the sample mean and/or scatter-plots. The proposed approach effectively instructs the analyst on how to achieve a targeted reduction of the variance, by operating on the extremes of the input parameters' ranges. The approach is tested against a known benchmark for sensitivity studies, the Ishigami test function, and a numerical model simulating the behaviour of a water hammer effect in a piping system.

  20. About the use of rank transformation in sensitivity analysis of model output

    International Nuclear Information System (INIS)

    Saltelli, Andrea; Sobol', Ilya M

    1995-01-01

    Rank transformations are frequently employed in numerical experiments involving a computational model, especially in the context of sensitivity and uncertainty analyses. Response surface replacement and parameter screening are tasks which may benefit from a rank transformation. Ranks can cope with nonlinear (albeit monotonic) input-output distributions, allowing the use of linear regression techniques. Rank transformed statistics are more robust, and provide a useful solution in the presence of long tailed input and output distributions. As is known to practitioners, care must be employed when interpreting the results of such analyses, as any conclusion drawn using ranks does not translate easily to the original model. In the present note an heuristic approach is taken, to explore, by way of practical examples, the effect of a rank transformation on the outcome of a sensitivity analysis. An attempt is made to identify trends, and to correlate these effects to a model taxonomy. Employing sensitivity indices, whereby the total variance of the model output is decomposed into a sum of terms of increasing dimensionality, we show that the main effect of the rank transformation is to increase the relative weight of the first order terms (the 'main effects'), at the expense of the 'interactions' and 'higher order interactions'. As a result the influence of those parameters which influence the output mostly by way of interactions may be overlooked in an analysis based on the ranks. This difficulty increases with the dimensionality of the problem, and may lead to the failure of a rank based sensitivity analysis. We suggest that the models can be ranked, with respect to the complexity of their input-output relationship, by mean of an 'Association' index I y . I y may complement the usual model coefficient of determination R y 2 as a measure of model complexity for the purpose of uncertainty and sensitivity analysis

  1. Sampling and sensitivity analyses tools (SaSAT for computational modelling

    Directory of Open Access Journals (Sweden)

    Wilson David P

    2008-02-01

    Full Text Available Abstract SaSAT (Sampling and Sensitivity Analysis Tools is a user-friendly software package for applying uncertainty and sensitivity analyses to mathematical and computational models of arbitrary complexity and context. The toolbox is built in Matlab®, a numerical mathematical software package, and utilises algorithms contained in the Matlab® Statistics Toolbox. However, Matlab® is not required to use SaSAT as the software package is provided as an executable file with all the necessary supplementary files. The SaSAT package is also designed to work seamlessly with Microsoft Excel but no functionality is forfeited if that software is not available. A comprehensive suite of tools is provided to enable the following tasks to be easily performed: efficient and equitable sampling of parameter space by various methodologies; calculation of correlation coefficients; regression analysis; factor prioritisation; and graphical output of results, including response surfaces, tornado plots, and scatterplots. Use of SaSAT is exemplified by application to a simple epidemic model. To our knowledge, a number of the methods available in SaSAT for performing sensitivity analyses have not previously been used in epidemiological modelling and their usefulness in this context is demonstrated.

  2. Sensitivity of the WRF model to the lower boundary in an extreme precipitation event - Madeira island case study

    Science.gov (United States)

    Teixeira, J. C.; Carvalho, A. C.; Carvalho, M. J.; Luna, T.; Rocha, A.

    2014-08-01

    The advances in satellite technology in recent years have made feasible the acquisition of high-resolution information on the Earth's surface. Examples of such information include elevation and land use, which have become more detailed. Including this information in numerical atmospheric models can improve their results in simulating lower boundary forced events, by providing detailed information on their characteristics. Consequently, this work aims to study the sensitivity of the weather research and forecast (WRF) model to different topography as well as land-use simulations in an extreme precipitation event. The test case focused on a topographically driven precipitation event over the island of Madeira, which triggered flash floods and mudslides in the southern parts of the island. Difference fields between simulations were computed, showing that the change in the data sets produced statistically significant changes to the flow, the planetary boundary layer structure and precipitation patterns. Moreover, model results show an improvement in model skill in the windward region for precipitation and in the leeward region for wind, in spite of the non-significant enhancement in the overall results with higher-resolution data sets of topography and land use.

  3. Automating calibration, sensitivity and uncertainty analysis of complex models using the R package Flexible Modeling Environment (FME): SWAT as an example

    Science.gov (United States)

    Wu, Y.; Liu, S.

    2012-01-01

    Parameter optimization and uncertainty issues are a great challenge for the application of large environmental models like the Soil and Water Assessment Tool (SWAT), which is a physically-based hydrological model for simulating water and nutrient cycles at the watershed scale. In this study, we present a comprehensive modeling environment for SWAT, including automated calibration, and sensitivity and uncertainty analysis capabilities through integration with the R package Flexible Modeling Environment (FME). To address challenges (e.g., calling the model in R and transferring variables between Fortran and R) in developing such a two-language coupling framework, 1) we converted the Fortran-based SWAT model to an R function (R-SWAT) using the RFortran platform, and alternatively 2) we compiled SWAT as a Dynamic Link Library (DLL). We then wrapped SWAT (via R-SWAT) with FME to perform complex applications including parameter identifiability, inverse modeling, and sensitivity and uncertainty analysis in the R environment. The final R-SWAT-FME framework has the following key functionalities: automatic initialization of R, running Fortran-based SWAT and R commands in parallel, transferring parameters and model output between SWAT and R, and inverse modeling with visualization. To examine this framework and demonstrate how it works, a case study simulating streamflow in the Cedar River Basin in Iowa in the United Sates was used, and we compared it with the built-in auto-calibration tool of SWAT in parameter optimization. Results indicate that both methods performed well and similarly in searching a set of optimal parameters. Nonetheless, the R-SWAT-FME is more attractive due to its instant visualization, and potential to take advantage of other R packages (e.g., inverse modeling and statistical graphics). The methods presented in the paper are readily adaptable to other model applications that require capability for automated calibration, and sensitivity and uncertainty

  4. Sensitivity analysis of hydraulic fracturing Using an extended finite element method for the PKN model

    NARCIS (Netherlands)

    Garikapati, Hasini; Verhoosel, Clemens V.; van Brummelen, Harald; Diez, Pedro; Papadrakakis, M.; Papadopoulos, V.; Stefanou, G.; Plevris, V.

    2016-01-01

    Hydraulic fracturing is a process that is surrounded by uncertainty, as available data on e.g. rock formations is scant and available models are still rudimentary. In this contribution sensitivity analysis is carried out as first step in studying the uncertainties in the model. This is done to

  5. A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities across Categories

    Science.gov (United States)

    Duvvuri, Sri Devi; Gruca, Thomas S.

    2010-01-01

    Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to…

  6. Sensitivity Analysis of Biome-Bgc Model for Dry Tropical Forests of Vindhyan Highlands, India

    Science.gov (United States)

    Kumar, M.; Raghubanshi, A. S.

    2011-08-01

    A process-based model BIOME-BGC was run for sensitivity analysis to see the effect of ecophysiological parameters on net primary production (NPP) of dry tropical forest of India. The sensitivity test reveals that the forest NPP was highly sensitive to the following ecophysiological parameters: Canopy light extinction coefficient (k), Canopy average specific leaf area (SLA), New stem C : New leaf C (SC:LC), Maximum stomatal conductance (gs,max), C:N of fine roots (C:Nfr), All-sided to projected leaf area ratio and Canopy water interception coefficient (Wint). Therefore, these parameters need more precision and attention during estimation and observation in the field studies.

  7. A model to estimate insulin sensitivity in dairy cows

    OpenAIRE

    Holtenius, Paul; Holtenius, Kjell

    2007-01-01

    Abstract Impairment of the insulin regulation of energy metabolism is considered to be an etiologic key component for metabolic disturbances. Methods for studies of insulin sensitivity thus are highly topical. There are clear indications that reduced insulin sensitivity contributes to the metabolic disturbances that occurs especially among obese lactating cows. Direct measurements of insulin sensitivity are laborious and not suitable for epidemiological studies. We have therefore adopted an i...

  8. A two dimensional modeling study of the sensitivity of ozone to radiative flux uncertainties

    International Nuclear Information System (INIS)

    Grant, K.E.; Wuebbles, D.J.

    1988-08-01

    Radiative processes strongly effect equilibrium trace gas concentrations both directly, through photolysis reactions, and indirectly through temperature and transport processes. We have used the LLNL 2-D chemical-radiative-transport model to investigate the net sensitivity of equilibrium ozone concentrations to several changes in radiative forcing. Doubling CO 2 from 300 ppmv to 600 ppmv resulted in a temperature decrease of 5 K to 8 K in the middle stratosphere along with an 8% to 16% increase in ozone in the same region. Replacing our usual shortwave scattering algorithms with a simplified Rayleigh algorithm led to a 1% to 2% increase in ozone in the lower stratosphere. Finally, modifying our normal CO 2 cooling rates by corrections derived from line-by-line calculations resulted in several regions of heating and cooling. We observed temperature changes on the order of 1 K to 1.5 K with corresponding changes of 0.5% to 1.5% in O 3 . Our results for doubled CO 2 compare favorably with those by other authors. Results for our two perturbation scenarios stress the need for accurately modeling radiative processes while confirming the general validity of current models. 15 refs., 5 figs

  9. Physically-based slope stability modelling and parameter sensitivity: a case study in the Quitite and Papagaio catchments, Rio de Janeiro, Brazil

    Science.gov (United States)

    de Lima Neves Seefelder, Carolina; Mergili, Martin

    2016-04-01

    We use the software tools r.slope.stability and TRIGRS to produce factor of safety and slope failure susceptibility maps for the Quitite and Papagaio catchments, Rio de Janeiro, Brazil. The key objective of the work consists in exploring the sensitivity of the geotechnical (r.slope.stability) and geohydraulic (TRIGRS) parameterization on the model outcomes in order to define suitable parameterization strategies for future slope stability modelling. The two landslide-prone catchments Quitite and Papagaio together cover an area of 4.4 km², extending between 12 and 995 m a.s.l. The study area is dominated by granitic bedrock and soil depths of 1-3 m. Ranges of geotechnical and geohydraulic parameters are derived from literature values. A landslide inventory related to a rainfall event in 1996 (250 mm in 48 hours) is used for model evaluation. We attempt to identify those combinations of effective cohesion and effective internal friction angle yielding the best correspondence with the observed landslide release areas in terms of the area under the ROC Curve (AUCROC), and in terms of the fraction of the area affected by the release of landslides. Thereby we test multiple parameter combinations within defined ranges to derive the slope failure susceptibility (fraction of tested parameter combinations yielding a factor of safety smaller than 1). We use the tool r.slope.stability (comparing the infinite slope stability model and an ellipsoid-based sliding surface model) to test and to optimize the geotechnical parameters, and TRIGRS (a coupled hydraulic-infinite slope stability model) to explore the sensitivity of the model results to the geohydraulic parameters. The model performance in terms of AUCROC is insensitive to the variation of the geotechnical parameterization within much of the tested ranges. Assuming fully saturated soils, r.slope.stability produces rather conservative predictions, whereby the results yielded with the sliding surface model are more

  10. Global sensitivity analysis of the joint kinematics during gait to the parameters of a lower limb multi-body model.

    Science.gov (United States)

    El Habachi, Aimad; Moissenet, Florent; Duprey, Sonia; Cheze, Laurence; Dumas, Raphaël

    2015-07-01

    Sensitivity analysis is a typical part of biomechanical models evaluation. For lower limb multi-body models, sensitivity analyses have been mainly performed on musculoskeletal parameters, more rarely on the parameters of the joint models. This study deals with a global sensitivity analysis achieved on a lower limb multi-body model that introduces anatomical constraints at the ankle, tibiofemoral, and patellofemoral joints. The aim of the study was to take into account the uncertainty of parameters (e.g. 2.5 cm on the positions of the skin markers embedded in the segments, 5° on the orientation of hinge axis, 2.5 mm on the origin and insertion of ligaments) using statistical distributions and propagate it through a multi-body optimisation method used for the computation of joint kinematics from skin markers during gait. This will allow us to identify the most influential parameters on the minimum of the objective function of the multi-body optimisation (i.e. the sum of the squared distances between measured and model-determined skin marker positions) and on the joint angles and displacements. To quantify this influence, a Fourier-based algorithm of global sensitivity analysis coupled with a Latin hypercube sampling is used. This sensitivity analysis shows that some parameters of the motor constraints, that is to say the distances between measured and model-determined skin marker positions, and the kinematic constraints are highly influencing the joint kinematics obtained from the lower limb multi-body model, for example, positions of the skin markers embedded in the shank and pelvis, parameters of the patellofemoral hinge axis, and parameters of the ankle and tibiofemoral ligaments. The resulting standard deviations on the joint angles and displacements reach 36° and 12 mm. Therefore, personalisation, customisation or identification of these most sensitive parameters of the lower limb multi-body models may be considered as essential.

  11. A sensitivity analysis for a thermomechanical model of the Antarctic ice sheet and ice shelves

    Science.gov (United States)

    Baratelli, F.; Castellani, G.; Vassena, C.; Giudici, M.

    2012-04-01

    The outcomes of an ice sheet model depend on a number of parameters and physical quantities which are often estimated with large uncertainty, because of lack of sufficient experimental measurements in such remote environments. Therefore, the efforts to improve the accuracy of the predictions of ice sheet models by including more physical processes and interactions with atmosphere, hydrosphere and lithosphere can be affected by the inaccuracy of the fundamental input data. A sensitivity analysis can help to understand which are the input data that most affect the different predictions of the model. In this context, a finite difference thermomechanical ice sheet model based on the Shallow-Ice Approximation (SIA) and on the Shallow-Shelf Approximation (SSA) has been developed and applied for the simulation of the evolution of the Antarctic ice sheet and ice shelves for the last 200 000 years. The sensitivity analysis of the model outcomes (e.g., the volume of the ice sheet and of the ice shelves, the basal melt rate of the ice sheet, the mean velocity of the Ross and Ronne-Filchner ice shelves, the wet area at the base of the ice sheet) with respect to the model parameters (e.g., the basal sliding coefficient, the geothermal heat flux, the present-day surface accumulation and temperature, the mean ice shelves viscosity, the melt rate at the base of the ice shelves) has been performed by computing three synthetic numerical indices: two local sensitivity indices and a global sensitivity index. Local sensitivity indices imply a linearization of the model and neglect both non-linear and joint effects of the parameters. The global variance-based sensitivity index, instead, takes into account the complete variability of the input parameters but is usually conducted with a Monte Carlo approach which is computationally very demanding for non-linear complex models. Therefore, the global sensitivity index has been computed using a development of the model outputs in a

  12. Sensitivity Analysis for Iceberg Geometry Shape in Ship-Iceberg Collision in View of Different Material Models

    Directory of Open Access Journals (Sweden)

    Yan Gao

    2014-01-01

    Full Text Available The increasing marine activities in Arctic area have brought growing interest in ship-iceberg collision study. The purpose of this paper is to study the iceberg geometry shape effect on the collision process. In order to estimate the sensitivity parameter, five different geometry iceberg models and two iceberg material models are adopted in the analysis. The FEM numerical simulation is used to predict the scenario and the related responses. The simulation results including energy dissipation and impact force are investigated and compared. It is shown that the collision process and energy dissipation are more sensitive to iceberg local shape than other factors when the elastic-plastic iceberg material model is applied. The blunt iceberg models act rigidly while the sharp ones crush easily during the simulation process. With respect to the crushable foam iceberg material model, the iceberg geometry has relatively small influence on the collision process. The spherical iceberg model shows the most rigidity for both iceberg material models and should be paid the most attention for ice-resist design for ships.

  13. Uncertainty and sensitivity analysis of fission gas behavior in engineering-scale fuel modeling

    Energy Technology Data Exchange (ETDEWEB)

    Pastore, Giovanni, E-mail: Giovanni.Pastore@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Swiler, L.P., E-mail: LPSwile@sandia.gov [Optimization and Uncertainty Quantification, Sandia National Laboratories, P.O. Box 5800, Albuquerque, NM 87185-1318 (United States); Hales, J.D., E-mail: Jason.Hales@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Novascone, S.R., E-mail: Stephen.Novascone@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Perez, D.M., E-mail: Danielle.Perez@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Spencer, B.W., E-mail: Benjamin.Spencer@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States); Luzzi, L., E-mail: Lelio.Luzzi@polimi.it [Politecnico di Milano, Department of Energy, Nuclear Engineering Division, via La Masa 34, I-20156 Milano (Italy); Van Uffelen, P., E-mail: Paul.Van-Uffelen@ec.europa.eu [European Commission, Joint Research Centre, Institute for Transuranium Elements, Hermann-von-Helmholtz-Platz 1, D-76344 Karlsruhe (Germany); Williamson, R.L., E-mail: Richard.Williamson@inl.gov [Fuel Modeling and Simulation, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-3840 (United States)

    2015-01-15

    The role of uncertainties in fission gas behavior calculations as part of engineering-scale nuclear fuel modeling is investigated using the BISON fuel performance code with a recently implemented physics-based model for fission gas release and swelling. Through the integration of BISON with the DAKOTA software, a sensitivity analysis of the results to selected model parameters is carried out based on UO{sub 2} single-pellet simulations covering different power regimes. The parameters are varied within ranges representative of the relative uncertainties and consistent with the information in the open literature. The study leads to an initial quantitative assessment of the uncertainty in fission gas behavior predictions with the parameter characterization presently available. Also, the relative importance of the single parameters is evaluated. Moreover, a sensitivity analysis is carried out based on simulations of a fuel rod irradiation experiment, pointing out a significant impact of the considered uncertainties on the calculated fission gas release and cladding diametral strain. The results of the study indicate that the commonly accepted deviation between calculated and measured fission gas release by a factor of 2 approximately corresponds to the inherent modeling uncertainty at high fission gas release. Nevertheless, significantly higher deviations may be expected for values around 10% and lower. Implications are discussed in terms of directions of research for the improved modeling of fission gas behavior for engineering purposes.

  14. Sensitivity analysis of physiochemical interaction model: which pair ...

    African Journals Online (AJOL)

    ... of two model parameters at a time on the solution trajectory of physiochemical interaction over a time interval. Our aim is to use this powerful mathematical technique to select the important pair of parameters of this physical process which is cost-effective. Keywords: Passivation Rate, Sensitivity Analysis, ODE23, ODE45 ...

  15. Tuning the climate sensitivity of a global model to match 20th Century warming

    Science.gov (United States)

    Mauritsen, T.; Roeckner, E.

    2015-12-01

    A climate models ability to reproduce observed historical warming is sometimes viewed as a measure of quality. Yet, for practical reasons historical warming cannot be considered a purely empirical result of the modelling efforts because the desired result is known in advance and so is a potential target of tuning. Here we explain how the latest edition of the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2) atmospheric model (ECHAM6.3) had its climate sensitivity systematically tuned to about 3 K; the MPI model to be used during CMIP6. This was deliberately done in order to improve the match to observed 20th Century warming over the previous model generation (MPI-ESM, ECHAM6.1) which warmed too much and had a sensitivity of 3.5 K. In the process we identified several controls on model cloud feedback that confirm recently proposed hypotheses concerning trade-wind cumulus and high-latitude mixed-phase clouds. We then evaluate the model fidelity with centennial global warming and discuss the relative importance of climate sensitivity, forcing and ocean heat uptake efficiency in determining the response as well as possible systematic biases. The activity of targeting historical warming during model development is polarizing the modeling community with 35 percent of modelers stating that 20th Century warming was rated very important to decisive, whereas 30 percent would not consider it at all. Likewise, opinions diverge as to which measures are legitimate means for improving the model match to observed warming. These results are from a survey conducted in conjunction with the first WCRP Workshop on Model Tuning in fall 2014 answered by 23 modelers. We argue that tuning or constructing models to match observed warming to some extent is practically unavoidable, and as such, in many cases might as well be done explicitly. For modeling groups that have the capability to tune both their aerosol forcing and climate sensitivity there is now a unique

  16. QSAR models of human data can enrich or replace LLNA testing for human skin sensitization

    Science.gov (United States)

    Alves, Vinicius M.; Capuzzi, Stephen J.; Muratov, Eugene; Braga, Rodolpho C.; Thornton, Thomas; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

    2016-01-01

    Skin sensitization is a major environmental and occupational health hazard. Although many chemicals have been evaluated in humans, there have been no efforts to model these data to date. We have compiled, curated, analyzed, and compared the available human and LLNA data. Using these data, we have developed reliable computational models and applied them for virtual screening of chemical libraries to identify putative skin sensitizers. The overall concordance between murine LLNA and human skin sensitization responses for a set of 135 unique chemicals was low (R = 28-43%), although several chemical classes had high concordance. We have succeeded to develop predictive QSAR models of all available human data with the external correct classification rate of 71%. A consensus model integrating concordant QSAR predictions and LLNA results afforded a higher CCR of 82% but at the expense of the reduced external dataset coverage (52%). We used the developed QSAR models for virtual screening of CosIng database and identified 1061 putative skin sensitizers; for seventeen of these compounds, we found published evidence of their skin sensitization effects. Models reported herein provide more accurate alternative to LLNA testing for human skin sensitization assessment across diverse chemical data. In addition, they can also be used to guide the structural optimization of toxic compounds to reduce their skin sensitization potential. PMID:28630595

  17. Modeled and observed ozone sensitivity to mobile-source emissions in Mexico City

    Directory of Open Access Journals (Sweden)

    M. Zavala

    2009-01-01

    Full Text Available The emission characteristics of mobile sources in the Mexico City Metropolitan Area (MCMA have changed significantly over the past few decades in response to emission control policies, advancements in vehicle technologies and improvements in fuel quality, among others. Along with these changes, concurrent non-linear changes in photochemical levels and criteria pollutants have been observed, providing a unique opportunity to understand the effects of perturbations of mobile emission levels on the photochemistry in the region using observational and modeling approaches. The observed historical trends of ozone (O3, carbon monoxide (CO and nitrogen oxides (NOx suggest that ozone production in the MCMA has changed from a low to a high VOC-sensitive regime over a period of 20 years. Comparison of the historical emission trends of CO, NOx and hydrocarbons derived from mobile-source emission studies in the MCMA from 1991 to 2006 with the trends of the concentrations of CO, NOx, and the CO/NOx ratio during peak traffic hours also indicates that fuel-based fleet average emission factors have significantly decreased for CO and VOCs during this period whereas NOx emission factors do not show any strong trend, effectively reducing the ambient VOC/NOx ratio.

    This study presents the results of model analyses on the sensitivity of the observed ozone levels to the estimated historical changes in its precursors. The model sensitivity analyses used a well-validated base case simulation of a high pollution episode in the MCMA with the mathematical Decoupled Direct Method (DDM and the standard Brute Force Method (BFM in the 3-D CAMx chemical transport model. The model reproduces adequately the observed historical trends and current photochemical levels. Comparison of the BFM and the DDM sensitivity techniques indicates that the model yields ozone values that increase linearly with

  18. Cavitation effects in LMFBR containment loading - a sensitivity study

    International Nuclear Information System (INIS)

    Jones, A.V.

    1981-01-01

    The motivation for and design of a sensitivity study into the effects of bulk cavitation of the coolant upon predicted roof loadings and vessel wall loadings and deformations are presented. The study is designed to cover simple and sophisticated models of cavitation in various geometries and with two types of energy source to represent both an explosion charge and the lower pressure expansion behavior expected in a real core disruptive accident. Effects of change of scale (from reactor to model), of coolant tensile strength, of reactor aspect ratio and design (presence or absence of an internal tank) and of reactor structural resistance (rigid or deforming outer tank) are all examined in order to provide a quantitative answer to the question 'how and to what extent does dynamic cavitation affect the containment loading process.'. (orig.)

  19. The sensitivity of biological finite element models to the resolution of surface geometry: a case study of crocodilian crania

    Directory of Open Access Journals (Sweden)

    Matthew R. McCurry

    2015-06-01

    Full Text Available The reliability of finite element analysis (FEA in biomechanical investigations depends upon understanding the influence of model assumptions. In producing finite element models, surface mesh resolution is influenced by the resolution of input geometry, and influences the resolution of the ensuing solid mesh used for numerical analysis. Despite a large number of studies incorporating sensitivity studies of the effects of solid mesh resolution there has not yet been any investigation into the effect of surface mesh resolution upon results in a comparative context. Here we use a dataset of crocodile crania to examine the effects of surface resolution on FEA results in a comparative context. Seven high-resolution surface meshes were each down-sampled to varying degrees while keeping the resulting number of solid elements constant. These models were then subjected to bite and shake load cases using finite element analysis. The results show that incremental decreases in surface resolution can result in fluctuations in strain magnitudes, but that it is possible to obtain stable results using lower resolution surface in a comparative FEA study. As surface mesh resolution links input geometry with the resulting solid mesh, the implication of these results is that low resolution input geometry and solid meshes may provide valid results in a comparative context.

  20. A shorter and more specific oral sensitization-based experimental model of food allergy in mice.

    Science.gov (United States)

    Bailón, Elvira; Cueto-Sola, Margarita; Utrilla, Pilar; Rodríguez-Ruiz, Judith; Garrido-Mesa, Natividad; Zarzuelo, Antonio; Xaus, Jordi; Gálvez, Julio; Comalada, Mònica

    2012-07-31

    Cow's milk protein allergy (CMPA) is one of the most prevalent human food-borne allergies, particularly in children. Experimental animal models have become critical tools with which to perform research on new therapeutic approaches and on the molecular mechanisms involved. However, oral food allergen sensitization in mice requires several weeks and is usually associated with unspecific immune responses. To overcome these inconveniences, we have developed a new food allergy model that takes only two weeks while retaining the main characters of allergic response to food antigens. The new model is characterized by oral sensitization of weaned Balb/c mice with 5 doses of purified cow's milk protein (CMP) plus cholera toxin (CT) for only two weeks and posterior challenge with an intraperitoneal administration of the allergen at the end of the sensitization period. In parallel, we studied a conventional protocol that lasts for seven weeks, and also the non-specific effects exerted by CT in both protocols. The shorter protocol achieves a similar clinical score as the original food allergy model without macroscopically affecting gut morphology or physiology. Moreover, the shorter protocol caused an increased IL-4 production and a more selective antigen-specific IgG1 response. Finally, the extended CT administration during the sensitization period of the conventional protocol is responsible for the exacerbated immune response observed in that model. Therefore, the new model presented here allows a reduction not only in experimental time but also in the number of animals required per experiment while maintaining the features of conventional allergy models. We propose that the new protocol reported will contribute to advancing allergy research. Copyright © 2012 Elsevier B.V. All rights reserved.

  1. Models for patients' recruitment in clinical trials and sensitivity analysis.

    Science.gov (United States)

    Mijoule, Guillaume; Savy, Stéphanie; Savy, Nicolas

    2012-07-20

    Taking a decision on the feasibility and estimating the duration of patients' recruitment in a clinical trial are very important but very hard questions to answer, mainly because of the huge variability of the system. The more elaborated works on this topic are those of Anisimov and co-authors, where they investigate modelling of the enrolment period by using Gamma-Poisson processes, which allows to develop statistical tools that can help the manager of the clinical trial to answer these questions and thus help him to plan the trial. The main idea is to consider an ongoing study at an intermediate time, denoted t(1). Data collected on [0,t(1)] allow to calibrate the parameters of the model, which are then used to make predictions on what will happen after t(1). This method allows us to estimate the probability of ending the trial on time and give possible corrective actions to the trial manager especially regarding how many centres have to be open to finish on time. In this paper, we investigate a Pareto-Poisson model, which we compare with the Gamma-Poisson one. We will discuss the accuracy of the estimation of the parameters and compare the models on a set of real case data. We make the comparison on various criteria : the expected recruitment duration, the quality of fitting to the data and its sensitivity to parameter errors. We discuss the influence of the centres opening dates on the estimation of the duration. This is a very important question to deal with in the setting of our data set. In fact, these dates are not known. For this discussion, we consider a uniformly distributed approach. Finally, we study the sensitivity of the expected duration of the trial with respect to the parameters of the model : we calculate to what extent an error on the estimation of the parameters generates an error in the prediction of the duration.

  2. Maintenance Personnel Performance Simulation (MAPPS) model: description of model content, structure, and sensitivity testing. Volume 2

    International Nuclear Information System (INIS)

    Siegel, A.I.; Bartter, W.D.; Wolf, J.J.; Knee, H.E.

    1984-12-01

    This volume of NUREG/CR-3626 presents details of the content, structure, and sensitivity testing of the Maintenance Personnel Performance Simulation (MAPPS) model that was described in summary in volume one of this report. The MAPPS model is a generalized stochastic computer simulation model developed to simulate the performance of maintenance personnel in nuclear power plants. The MAPPS model considers workplace, maintenance technician, motivation, human factors, and task oriented variables to yield predictive information about the effects of these variables on successful maintenance task performance. All major model variables are discussed in detail and their implementation and interactive effects are outlined. The model was examined for disqualifying defects from a number of viewpoints, including sensitivity testing. This examination led to the identification of some minor recalibration efforts which were carried out. These positive results indicate that MAPPS is ready for initial and controlled applications which are in conformity with its purposes

  3. Understanding the Day Cent model: Calibration, sensitivity, and identifiability through inverse modeling

    Science.gov (United States)

    Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.

    2015-01-01

    The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

  4. Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

    Science.gov (United States)

    Rakovec, O.; Hill, M. C.; Clark, M. P.; Weerts, A. H.; Teuling, A. J.; Uijlenhoet, R.

    2014-01-01

    This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based "local" methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative "bucket-style" hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.

  5. Sensitivity of surface temperature to radiative forcing by contrail cirrus in a radiative-mixing model

    Directory of Open Access Journals (Sweden)

    U. Schumann

    2017-11-01

    Full Text Available Earth's surface temperature sensitivity to radiative forcing (RF by contrail cirrus and the related RF efficacy relative to CO2 are investigated in a one-dimensional idealized model of the atmosphere. The model includes energy transport by shortwave (SW and longwave (LW radiation and by mixing in an otherwise fixed reference atmosphere (no other feedbacks. Mixing includes convective adjustment and turbulent diffusion, where the latter is related to the vertical component of mixing by large-scale eddies. The conceptual study shows that the surface temperature sensitivity to given contrail RF depends strongly on the timescales of energy transport by mixing and radiation. The timescales are derived for steady layered heating (ghost forcing and for a transient contrail cirrus case. The radiative timescales are shortest at the surface and shorter in the troposphere than in the mid-stratosphere. Without mixing, a large part of the energy induced into the upper troposphere by radiation due to contrails or similar disturbances gets lost to space before it can contribute to surface warming. Because of the different radiative forcing at the surface and at top of atmosphere (TOA and different radiative heating rate profiles in the troposphere, the local surface temperature sensitivity to stratosphere-adjusted RF is larger for SW than for LW contrail forcing. Without mixing, the surface energy budget is more important for surface warming than the TOA budget. Hence, surface warming by contrails is smaller than suggested by the net RF at TOA. For zero mixing, cooling by contrails cannot be excluded. This may in part explain low efficacy values for contrails found in previous global circulation model studies. Possible implications of this study are discussed. Since the results of this study are model dependent, they should be tested with a comprehensive climate model in the future.

  6. Sensitivity in risk analyses with uncertain numbers.

    Energy Technology Data Exchange (ETDEWEB)

    Tucker, W. Troy; Ferson, Scott

    2006-06-01

    Sensitivity analysis is a study of how changes in the inputs to a model influence the results of the model. Many techniques have recently been proposed for use when the model is probabilistic. This report considers the related problem of sensitivity analysis when the model includes uncertain numbers that can involve both aleatory and epistemic uncertainty and the method of calculation is Dempster-Shafer evidence theory or probability bounds analysis. Some traditional methods for sensitivity analysis generalize directly for use with uncertain numbers, but, in some respects, sensitivity analysis for these analyses differs from traditional deterministic or probabilistic sensitivity analyses. A case study of a dike reliability assessment illustrates several methods of sensitivity analysis, including traditional probabilistic assessment, local derivatives, and a ''pinching'' strategy that hypothetically reduces the epistemic uncertainty or aleatory uncertainty, or both, in an input variable to estimate the reduction of uncertainty in the outputs. The prospects for applying the methods to black box models are also considered.

  7. Sensitivity of subject-specific models to Hill muscle-tendon model parameters in simulations of gait

    NARCIS (Netherlands)

    Carbone, V.; Krogt, M.M. van der; Koopman, H.F.J.M.; Verdonschot, N.J.

    2016-01-01

    Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle-tendon (MT) model parameters for each of

  8. Sensitivity of subject-specific models to Hill muscle-tendon model parameters in simulations of gait

    NARCIS (Netherlands)

    Carbone, Vincenzo; van der Krogt, Marjolein; Koopman, Hubertus F.J.M.; Verdonschot, Nicolaas Jacobus Joseph

    2016-01-01

    Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle–tendon (MT) model parameters for each of

  9. Global sensitivity analysis of a model related to memory formation in synapses: Model reduction based on epistemic parameter uncertainties and related issues.

    Science.gov (United States)

    Kulasiri, Don; Liang, Jingyi; He, Yao; Samarasinghe, Sandhya

    2017-04-21

    We investigate the epistemic uncertainties of parameters of a mathematical model that describes the dynamics of CaMKII-NMDAR complex related to memory formation in synapses using global sensitivity analysis (GSA). The model, which was published in this journal, is nonlinear and complex with Ca 2+ patterns with different level of frequencies as inputs. We explore the effects of parameter on the key outputs of the model to discover the most sensitive ones using GSA and partial ranking correlation coefficient (PRCC) and to understand why they are sensitive and others are not based on the biology of the problem. We also extend the model to add presynaptic neurotransmitter vesicles release to have action potentials as inputs of different frequencies. We perform GSA on this extended model to show that the parameter sensitivities are different for the extended model as shown by PRCC landscapes. Based on the results of GSA and PRCC, we reduce the original model to a less complex model taking the most important biological processes into account. We validate the reduced model against the outputs of the original model. We show that the parameter sensitivities are dependent on the inputs and GSA would make us understand the sensitivities and the importance of the parameters. A thorough phenomenological understanding of the relationships involved is essential to interpret the results of GSA and hence for the possible model reduction. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. How can sensitivity analysis improve the robustness of mathematical models utilized by the re/insurance industry?

    Science.gov (United States)

    Noacco, V.; Wagener, T.; Pianosi, F.; Philp, T.

    2017-12-01

    Insurance companies provide insurance against a wide range of threats, such as natural catastrophes, nuclear incidents and terrorism. To quantify risk and support investment decisions, mathematical models are used, for example to set the premiums charged to clients that protect from financial loss, should deleterious events occur. While these models are essential tools for adequately assessing the risk attached to an insurer's portfolio, their development is costly and their value for decision-making may be limited by an incomplete understanding of uncertainty and sensitivity. Aside from the business need to understand risk and uncertainty, the insurance sector also faces regulation which requires them to test their models in such a way that uncertainties are appropriately captured and that plans are in place to assess the risks and their mitigation. The building and testing of models constitutes a high cost for insurance companies, and it is a time intensive activity. This study uses an established global sensitivity analysis toolbox (SAFE) to more efficiently capture the uncertainties and sensitivities embedded in models used by a leading re/insurance firm, with structured approaches to validate these models and test the impact of assumptions on the model predictions. It is hoped that this in turn will lead to better-informed and more robust business decisions.

  11. A model for hormonal control of the menstrual cycle: structural consistency but sensitivity with regard to data.

    Science.gov (United States)

    Selgrade, J F; Harris, L A; Pasteur, R D

    2009-10-21

    This study presents a 13-dimensional system of delayed differential equations which predicts serum concentrations of five hormones important for regulation of the menstrual cycle. Parameters for the system are fit to two different data sets for normally cycling women. For these best fit parameter sets, model simulations agree well with the two different data sets but one model also has an abnormal stable periodic solution, which may represent polycystic ovarian syndrome. This abnormal cycle occurs for the model in which the normal cycle has estradiol levels at the high end of the normal range. Differences in model behavior are explained by studying hysteresis curves in bifurcation diagrams with respect to sensitive model parameters. For instance, one sensitive parameter is indicative of the estradiol concentration that promotes pituitary synthesis of a large amount of luteinizing hormone, which is required for ovulation. Also, it is observed that models with greater early follicular growth rates may have a greater risk of cycling abnormally.

  12. Extending the Global Sensitivity Analysis of the SimSphere model in the Context of its Future Exploitation by the Scientific Community

    Directory of Open Access Journals (Sweden)

    George P. Petropoulos

    2015-05-01

    Full Text Available In today’s changing climate, the development of robust, accurate and globally applicable models is imperative for a wider understanding of Earth’s terrestrial biosphere. Moreover, an understanding of the representation, sensitivity and coherence of such models are vital for the operationalisation of any physically based model. A Global Sensitivity Analysis (GSA was conducted on the SimSphere land biosphere model in which a meta-modelling method adopting Bayesian theory was implemented. Initially, effects of assuming uniform probability distribution functions (PDFs for the model inputs, when examining sensitivity of key quantities simulated by SimSphere at different output times, were examined. The development of topographic model input parameters (e.g., slope, aspect, and elevation were derived within a Geographic Information System (GIS before implementation within the model. The effect of time of the simulation on the sensitivity of previously examined outputs was also analysed. Results showed that simulated outputs were significantly influenced by changes in topographic input parameters, fractional vegetation cover, vegetation height and surface moisture availability in agreement with previous studies. Time of model output simulation had a significant influence on the absolute values of the output variance decomposition, but it did not seem to change the relative importance of each input parameter. Sensitivity Analysis (SA results of the newly modelled outputs allowed identification of the most responsive model inputs and interactions. Our study presents an important step forward in SimSphere verification given the increasing interest in its use both as an independent modelling and educational tool. Furthermore, this study is very timely given on-going efforts towards the development of operational products based on the synergy of SimSphere with Earth Observation (EO data. In this context, results also provide additional support for the

  13. Modeling of a Low-Background Spectroscopic Position-Sensitive Neutron Detector

    Energy Technology Data Exchange (ETDEWEB)

    Postovarova, Daria; Evsenin, Alexey; Gorshkov, Igor; Kuznetsov, Andrey; Osetrov, Oleg; Vakhtin, Dmitry; Yurmanov, Pavel [V.G. Khlopin Radium Institute, 194021, 28, 2nd Murinsky pr., Saint-Petersburg (Russian Federation)

    2011-12-13

    A new low-background spectroscopic direction-sensitive neutron detector that would allow one to reduce the neutron background component in passive and active neutron detection techniques is proposed. The detector is based on thermal neutron detectors surrounded by a fast neutron scintillation detector, which serves at the same time as a neutron moderator. Direction sensitivity is achieved by coincidence/anticoincidence analysis between different parts of the scintillator. Results of mathematical modeling of several detector configurations are presented.

  14. Modeling of a Low-Background Spectroscopic Position-Sensitive Neutron Detector

    International Nuclear Information System (INIS)

    Postovarova, Daria; Evsenin, Alexey; Gorshkov, Igor; Kuznetsov, Andrey; Osetrov, Oleg; Vakhtin, Dmitry; Yurmanov, Pavel

    2011-01-01

    A new low-background spectroscopic direction-sensitive neutron detector that would allow one to reduce the neutron background component in passive and active neutron detection techniques is proposed. The detector is based on thermal neutron detectors surrounded by a fast neutron scintillation detector, which serves at the same time as a neutron moderator. Direction sensitivity is achieved by coincidence/anticoincidence analysis between different parts of the scintillator. Results of mathematical modeling of several detector configurations are presented.

  15. Parameter Sensitivity and Laboratory Benchmarking of a Biogeochemical Process Model for Enhanced Anaerobic Dechlorination

    Science.gov (United States)

    Kouznetsova, I.; Gerhard, J. I.; Mao, X.; Barry, D. A.; Robinson, C.; Brovelli, A.; Harkness, M.; Fisher, A.; Mack, E. E.; Payne, J. A.; Dworatzek, S.; Roberts, J.

    2008-12-01

    A detailed model to simulate trichloroethene (TCE) dechlorination in anaerobic groundwater systems has been developed and implemented through PHAST, a robust and flexible geochemical modeling platform. The approach is comprehensive but retains flexibility such that models of varying complexity can be used to simulate TCE biodegradation in the vicinity of nonaqueous phase liquid (NAPL) source zones. The complete model considers a full suite of biological (e.g., dechlorination, fermentation, sulfate and iron reduction, electron donor competition, toxic inhibition, pH inhibition), physical (e.g., flow and mass transfer) and geochemical processes (e.g., pH modulation, gas formation, mineral interactions). Example simulations with the model demonstrated that the feedback between biological, physical, and geochemical processes is critical. Successful simulation of a thirty-two-month column experiment with site soil, complex groundwater chemistry, and exhibiting both anaerobic dechlorination and endogenous respiration, provided confidence in the modeling approach. A comprehensive suite of batch simulations was then conducted to estimate the sensitivity of predicted TCE degradation to the 36 model input parameters. A local sensitivity analysis was first employed to rank the importance of parameters, revealing that 5 parameters consistently dominated model predictions across a range of performance metrics. A global sensitivity analysis was then performed to evaluate the influence of a variety of full parameter data sets available in the literature. The modeling study was performed as part of the SABRE (Source Area BioREmediation) project, a public/private consortium whose charter is to determine if enhanced anaerobic bioremediation can result in effective and quantifiable treatment of chlorinated solvent DNAPL source areas. The modelling conducted has provided valuable insight into the complex interactions between processes in the evolving biogeochemical systems

  16. Application of Uncertainty and Sensitivity Analysis to a Kinetic Model for Enzymatic Biodiesel Production

    DEFF Research Database (Denmark)

    Price, Jason Anthony; Nordblad, Mathias; Woodley, John

    2014-01-01

    This paper demonstrates the added benefits of using uncertainty and sensitivity analysis in the kinetics of enzymatic biodiesel production. For this study, a kinetic model by Fedosov and co-workers is used. For the uncertainty analysis the Monte Carlo procedure was used to statistically quantify...

  17. Local Sensitivity and Diagnostic Tests

    NARCIS (Netherlands)

    Magnus, J.R.; Vasnev, A.L.

    2004-01-01

    In this paper we confront sensitivity analysis with diagnostic testing.Every model is misspecified, but a model is useful if the parameters of interest (the focus) are not sensitive to small perturbations in the underlying assumptions. The study of the e ect of these violations on the focus is

  18. Gamma ray induced sensitization in CaSO4:Dy and competing trap model

    International Nuclear Information System (INIS)

    Nagpal, J.S.; Kher, R.K.; Gangadharan, P.

    1979-01-01

    Gamma ray induced sensitization in CaSO 4 :Dy has been compared (by measurement of TL glow curves) for different temperatures during irradiation (25 0 , 120 0 and 250 0 C). Enhanced sensitization at elevated temperatures seems to support the competing trap model for supralinearity and sensitization in CaSO 4 :Dy. (author)

  19. Ex-vessel corium coolability sensitivity study with the CORQUENCH code

    International Nuclear Information System (INIS)

    Robb, Kevin; Corradini, Michael

    2009-01-01

    An unresolved safety issue for light water reactor beyond design basis accidents is the coolability and stabilization of ex-vessel core melt debris by top flooding. Several experimental programs, including the OECD MACE, MCCI-1, and the current MCCI-2 program, have investigated core-concrete interactions and debris cooling of ex-vessel core melts. As part of the OECD programs, the CORQUENCH computer model was developed based on phenomena identified from the experiments. Predictions by CORQUENCH have previously been compared against experiments and have also been extrapolated to reactor scale. The current study applied statistical techniques to investigate the importance of initial system parameters and cooling phenomena in CORQUENCH 3.01 on the accident progression of ex-vessel core melts. The purpose of this sensitivity study is to identify parameters that are of major importance, any code peculiarities over the range of inputs, and where modeling improvements may produce the most gain in prediction accuracy. The sensitivity studies were carried out over a range of input conditions, in 1-D and 2-D geometries, and for two concrete compositions. In terms of initial system parameters, the melt height had the most importance on concrete ablation and melt coolability. With respect to cooling phenomena, the amount of melt entrainment through the crust had the most importance on concrete ablation and melt coolability. (author)

  20. Sensitivity analysis of a radionuclide transfer model describing contaminated vegetation in Fukushima prefecture, using Morris and Sobol' - Application of sensitivity analysis on a radionuclides transfer model in the environment describing weeds contamination in Fukushima Prefecture, using Morris method and Sobol' indices indices

    Energy Technology Data Exchange (ETDEWEB)

    Nicoulaud-Gouin, V.; Metivier, J.M.; Gonze, M.A. [Institut de Radioprotection et de Surete Nucleaire-PRP-ENV/SERIS/LM2E (France); Garcia-Sanchez, L. [Institut de Radioprotection et de Surete Nucleaire-PRPENV/SERIS/L2BT (France)

    2014-07-01

    The increasing spatial and temporal complexity of models demands methods capable of ranking the influence of their large numbers of parameters. This question specifically arises in assessment studies on the consequences of the Fukushima accident. Sensitivity analysis aims at measuring the influence of input variability on the output response. Generally, two main approaches are distinguished (Saltelli, 2001, Iooss, 2011): - Screening approach, less expensive in computation time and allowing to identify non influential parameters; - Measures of importance, introducing finer quantitative indices. In this category, there are regression-based methods, assuming a linear or monotonic response (Pearson coefficient, Spearman coefficient), and variance-based methods, without assumptions on the model but requiring an increasingly prohibitive number of evaluations when the number of parameters increases. These approaches are available in various statistical programs (notably R) but are still poorly integrated in modelling platforms of radioecological risk assessment. This work aimed at illustrating the benefits of sensitivity analysis in the course of radioecological risk assessments This study used two complementary state-of-art global sensitivity analysis methods: - The screening method of Morris (Morris, 1991; Campolongo et al., 2007) based on limited model evaluations with a one-at-a-time (OAT) design; - The variance-based Sobol' sensitivity analysis (Saltelli, 2002) based a large number of model evaluations in the parameter space with a quasi-random sampling (Owen, 2003). Sensitivity analyses were applied on a dynamic Soil-Plant Deposition Model (Gonze et al., submitted to this conference) predicting foliar concentration in weeds after atmospheric radionuclide fallout. The Soil-Plant Deposition Model considers two foliage pools and a root pool, and describes foliar biomass growth with a Verhulst model. The developed semi-analytic formulation of foliar concentration

  1. Parameter Sensitivity Study for Typical Expander-Based Transcritical CO2 Refrigeration Cycles

    Directory of Open Access Journals (Sweden)

    Bo Zhang

    2018-05-01

    Full Text Available A sensitivity study was conducted for three typical expander-based transcritical CO2 cycles with the developed simulation model, and the sensitivities of the maximum coefficient of performance (COP to the key operating parameters, including the inlet pressure of gas cooler, the temperatures at evaporator inlet and gas cooler outlet, the inter-stage pressure and the isentropic efficiency of expander, were obtained. The results showed that the sensitivity to the gas cooler inlet pressure differs greatly before and after the optimal gas cooler inlet pressure. The sensitivity to the intercooler outlet temperature in the two-stage cycles increases sharply to near zero and then keeps almost constant at intercooler outlet temperature of higher than 45 °C. However, the sensitivity stabilizes near zero when the evaporator inlet temperature is very low of −26.1 °C. In two-stage compression with an intercooler and an expander assisting in driving the first-stage compressor (TEADFC cycle, an abrupt change in the sensitivity of maximum COP to the inter-stage pressure was observed, but disappeared after intercooler outlet temperature exceeds 50 °C. The sensitivity of maximum COP to the expander isentropic efficiency increases almost linearly with the expander isentropic efficiency.

  2. Hydrograph sensitivity to estimates of map impervious cover: a WinHSPF BASINS case study

    Science.gov (United States)

    Endreny, Theodore A.; Somerlot, Christopher; Hassett, James M.

    2003-04-01

    The BASINS geographic information system hydrologic toolkit was designed to compute total maximum daily loads, which are often derived by combining water quantity estimates with pollutant concentration estimates. In this paper the BASINS toolkit PLOAD and WinHSPF sub-models are briefly described, and then a 0·45 km2 headwater watershed in the New York Croton River area is used for a case study illustrating a full WinHSPF implementation. The goal of the Croton study was to determine the sensitivity of WinHSPF hydrographs to changes in land cover map inputs. This scenario occurs when scaling the WinHSPF model from the smaller 0·45 km2 watershed to the larger 1000 km2 management basin of the entire Croton area. Methods used to test model sensitivity include first calibrating the WinHSPF hydrograph using research-monitored precipitation and discharge data together with high spatial resolution and accuracy land cover data of impervious and pervious areas, and then swapping three separate land cover files, known as GIRAS, MRLC, and DOQQ data, into the calibrated model. Research results indicated that the WinHSPF land cover swapping had peak flow sensitivity in December 2001 hydrographs between 35% underestimation and 20% overestimation, and that errors in land-cover-derived runoff ratios for storm totals and peak flows tracked with the land cover data estimates of impervious area.

  3. Sensitivity study of optimal CO2 emission paths using a simplified structural integrated assessment model (SIAM)

    International Nuclear Information System (INIS)

    Hasselmann, K.; Hasselmann, S.; Giering, R.; Ocana, V.; Storch, H. von

    1997-01-01

    A structurally highly simplified, globally integrated coupled climate-economic costs model SIAM (Structural Integrated Assessment Model) is used to compute optimal paths of global CO 2 emissions that minimize the net sum of climate damage and mitigation costs. It studies the sensitivity of the computed optimal emission paths. The climate module is represented by a linearized impulse-response model calibrated against a coupled ocean-atmosphere general circulation climate model and a three-dimensional global carbon-cycle model. The cost terms are presented by expressions designed with respect to input assumptions. These include the discount rates for mitigation and damage costs, the inertia of the socio-economic system, and the dependence of climate damages on the changes in temperature and the rate of change of temperature. Different assumptions regarding these parameters are believed to cause the marked divergences of existing cost-benefit analyses. The long memory of the climate system implies that very long time horizons of several hundred years need to be considered to optimize CO 2 emissions on time scales relevant for a policy of sustainable development. Cost-benefit analyses over shorter time scales of a century or two can lead to dangerous underestimates of the long term climate impact of increasing greenhouse-gas emissions. To avert a major long term global warming, CO 2 emissions need to be reduced ultimately to very low levels. This may be done slowly but should not be interpreted as providing a time cushion for inaction: the transition becomes more costly the longer the necessary mitigation policies are delayed. However, the long time horizon provides adequate flexibility for later adjustments. Short term energy conservation alone is insufficient and can be viewed only as a useful measure in support of the necessary long term transition to carbon-free energy technologies. 46 refs., 9 figs., 2 tabs

  4. Sensitivity Analysis of an Agent-Based Model of Culture's Consequences for Trade

    NARCIS (Netherlands)

    Burgers, S.L.G.E.; Jonker, C.M.; Hofstede, G.J.; Verwaart, D.

    2010-01-01

    This paper describes the analysis of an agent-based model’s sensitivity to changes in parameters that describe the agents’ cultural background, relational parameters, and parameters of the decision functions. As agent-based models may be very sensitive to small changes in parameter values, it is of

  5. Diagnosis and Quantification of Climatic Sensitivity of Carbon Fluxes in Ensemble Global Ecosystem Models

    Science.gov (United States)

    Wang, W.; Hashimoto, H.; Milesi, C.; Nemani, R. R.; Myneni, R.

    2011-12-01

    Terrestrial ecosystem models are primary scientific tools to extrapolate our understanding of ecosystem functioning from point observations to global scales as well as from the past climatic conditions into the future. However, no model is nearly perfect and there are often considerable structural uncertainties existing between different models. Ensemble model experiments thus become a mainstream approach in evaluating the current status of global carbon cycle and predicting its future changes. A key task in such applications is to quantify the sensitivity of the simulated carbon fluxes to climate variations and changes. Here we develop a systematic framework to address this question solely by analyzing the inputs and the outputs from the models. The principle of our approach is to assume the long-term (~30 years) average of the inputs/outputs as a quasi-equlibrium of the climate-vegetation system while treat the anomalies of carbon fluxes as responses to climatic disturbances. In this way, the corresponding relationships can be largely linearized and analyzed using conventional time-series techniques. This method is used to characterize three major aspects of the vegetation models that are mostly important to global carbon cycle, namely the primary production, the biomass dynamics, and the ecosystem respiration. We apply this analytical framework to quantify the climatic sensitivity of an ensemble of models including CASA, Biome-BGC, LPJ as well as several other DGVMs from previous studies, all driven by the CRU-NCEP climate dataset. The detailed analysis results are reported in this study.

  6. Parameter sensitivity and uncertainty of the forest carbon flux model FORUG : a Monte Carlo analysis

    Energy Technology Data Exchange (ETDEWEB)

    Verbeeck, H.; Samson, R.; Lemeur, R. [Ghent Univ., Ghent (Belgium). Laboratory of Plant Ecology; Verdonck, F. [Ghent Univ., Ghent (Belgium). Dept. of Applied Mathematics, Biometrics and Process Control

    2006-06-15

    The FORUG model is a multi-layer process-based model that simulates carbon dioxide (CO{sub 2}) and water exchange between forest stands and the atmosphere. The main model outputs are net ecosystem exchange (NEE), total ecosystem respiration (TER), gross primary production (GPP) and evapotranspiration. This study used a sensitivity analysis to identify the parameters contributing to NEE uncertainty in the FORUG model. The aim was to determine if it is necessary to estimate the uncertainty of all parameters of a model to determine overall output uncertainty. Data used in the study were the meteorological and flux data of beech trees in Hesse. The Monte Carlo method was used to rank sensitivity and uncertainty parameters in combination with a multiple linear regression. Simulations were run in which parameters were assigned probability distributions and the effect of variance in the parameters on the output distribution was assessed. The uncertainty of the output for NEE was estimated. Based on the arbitrary uncertainty of 10 key parameters, a standard deviation of 0.88 Mg C per year per NEE was found, which was equal to 24 per cent of the mean value of NEE. The sensitivity analysis showed that the overall output uncertainty of the FORUG model could be determined by accounting for only a few key parameters, which were identified as corresponding to critical parameters in the literature. It was concluded that the 10 most important parameters determined more than 90 per cent of the output uncertainty. High ranking parameters included soil respiration; photosynthesis; and crown architecture. It was concluded that the Monte Carlo technique is a useful tool for ranking the uncertainty of parameters of process-based forest flux models. 48 refs., 2 tabs., 2 figs.

  7. Application of Weather Research and Forecasting Model with Chemistry (WRF/Chem) over northern China: Sensitivity study, comparative evaluation, and policy implications

    Science.gov (United States)

    Wang, Litao; Zhang, Yang; Wang, Kai; Zheng, Bo; Zhang, Qiang; Wei, Wei

    2016-01-01

    An extremely severe and persistent haze event occurred over the middle and eastern China in January 2013, with the record-breaking high concentrations of fine particulate matter (PM2.5). In this study, an online-coupled meteorology-air quality model, the Weather Research and Forecasting Model with Chemistry (WRF/Chem), is applied to simulate this pollution episode over East Asia and northern China at 36- and 12-km grid resolutions. A number of simulations are conducted to examine the sensitivities of the model predictions to various physical schemes. The results show that all simulations give similar predictions for temperature, wind speed, wind direction, and humidity, but large variations exist in the prediction for precipitation. The concentrations of PM2.5, particulate matter with aerodynamic diameter of 10 μm or less (PM10), sulfur dioxide (SO2), and nitrogen dioxide (NO2) are overpredicted partially due to the lack of wet scavenging by the chemistry-aerosol option with the 1999 version of the Statewide Air Pollution Research Center (SAPRC-99) mechanism with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) and the Volatility Basis Set (VBS) for secondary organic aerosol formation. The optimal set of configurations with the best performance is the simulation with the Gorddard shortwave and RRTM longwave radiation schemes, the Purdue Lin microphysics scheme, the Kain-Fritsch cumulus scheme, and a nudging coefficient of 1 × 10-5 for water vapor mixing ratio. The emission sensitivity simulations show that the PM2.5 concentrations are most sensitive to nitrogen oxide (NOx) and SO2 emissions in northern China, but to NOx and ammonia (NH3) emissions in southern China. 30% NOx emission reductions may result in an increase in PM2.5 concentrations in northern China because of the NH3-rich and volatile organic compound (VOC) limited conditions over this area. VOC emission reductions will lead to a decrease in PM2.5 concentrations in eastern China

  8. Neutron and gamma sensitivities of self-powered detectors: Monte Carlo modelling

    Energy Technology Data Exchange (ETDEWEB)

    Vermeeren, Ludo [SCK-CEN, Nuclear Research Centre, Boeretang 200, B-2400 Mol, (Belgium)

    2015-07-01

    This paper deals with the development of a detailed Monte Carlo approach for the calculation of the absolute neutron sensitivity of SPNDs, which makes use of the MCNP code. We will explain the calculation approach, including the activation and beta emission steps, the gamma-electron interactions, the charge deposition in the various detector parts and the effect of the space charge field in the insulator. The model can also be applied for the calculation of the gamma sensitivity of self-powered detectors and for the radiation-induced currents in signal cables. The model yields detailed information on the various contributions to the sensor currents, with distinct response times. Results for the neutron sensitivity of various types of SPNDs are in excellent agreement with experimental data obtained at the BR2 research reactor. For typical neutron to gamma flux ratios, the calculated gamma induced SPND currents are significantly lower than the neutron induced currents. The gamma sensitivity depends very strongly upon the immediate detector surroundings and on the gamma spectrum. Our calculation method opens the way to a reliable on-line determination of the absolute in-pile thermal neutron flux. (authors)

  9. Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system.

    Science.gov (United States)

    Lumen, Annie; McNally, Kevin; George, Nysia; Fisher, Jeffrey W; Loizou, George D

    2015-01-01

    A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local sensitivity analysis.

  10. Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system

    Directory of Open Access Journals (Sweden)

    Annie eLumen

    2015-05-01

    Full Text Available A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local

  11. Towards a Formal Model of Privacy-Sensitive Dynamic Coalitions

    Directory of Open Access Journals (Sweden)

    Sebastian Bab

    2012-04-01

    Full Text Available The concept of dynamic coalitions (also virtual organizations describes the temporary interconnection of autonomous agents, who share information or resources in order to achieve a common goal. Through modern technologies these coalitions may form across company, organization and system borders. Therefor questions of access control and security are of vital significance for the architectures supporting these coalitions. In this paper, we present our first steps to reach a formal framework for modeling and verifying the design of privacy-sensitive dynamic coalition infrastructures and their processes. In order to do so we extend existing dynamic coalition modeling approaches with an access-control-concept, which manages access to information through policies. Furthermore we regard the processes underlying these coalitions and present first works in formalizing these processes. As a result of the present paper we illustrate the usefulness of the Abstract State Machine (ASM method for this task. We demonstrate a formal treatment of privacy-sensitive dynamic coalitions by two example ASMs which model certain access control situations. A logical consideration of these ASMs can lead to a better understanding and a verification of the ASMs according to the aspired specification.

  12. Application of the pertubation theory to a two channels model for sensitivity calculations in PWR cores

    International Nuclear Information System (INIS)

    Oliveira, A.C.J.G. de; Andrade Lima, F.R. de

    1989-01-01

    The present work is an application of the perturbation theory (Matricial formalism) to a simplified two channels model, for sensitivity calculations in PWR cores. Expressions for some sensitivity coefficients of thermohydraulic interest were developed from the proposed model. The code CASNUR.FOR was written in FORTRAN to evaluate these sensitivity coefficients. The comparison between results obtained from the matrical formalism of pertubation theory with those obtained directly from the two channels model, makes evident the efficiency and potentiality of this perturbation method for nuclear reactor cores sensitivity calculations. (author) [pt

  13. Early identification of technical issues: a sensitivity study to check LISTRA1A internal consistency and structure

    International Nuclear Information System (INIS)

    Harvey, T.F.; Maninger, R.C.; Rabsatt, S.

    1979-01-01

    This report describes a sensitivity study using LISTRA1A, a model for use in the development of a long-range, time-dependent plan for licensing nuclear waste repositories. The objectives of the model are: (1) to provide information concerning the impact of various licensing strategies on the ability to dispose of nuclear waste effectively; and (2) to provide long-range budget forecasts for differing strategies of the Nuclear Regulatory Commission (NRC) and the Department of Energy (DOE). The model is designed to analyze the interaction between NRC regulatory policy and DOE technical programs. A sensitivity study is reported for a single parameter in a hypothetical review process

  14. Climate forcings and climate sensitivities diagnosed from atmospheric global circulation models

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Bruce T. [Boston University, Department of Geography and Environment, Boston, MA (United States); Knight, Jeff R.; Ringer, Mark A. [Met Office Hadley Centre, Exeter (United Kingdom); Deser, Clara; Phillips, Adam S. [National Center for Atmospheric Research, Boulder, CO (United States); Yoon, Jin-Ho [University of Maryland, Cooperative Institute for Climate and Satellites, Earth System Science Interdisciplinary Center, College Park, MD (United States); Cherchi, Annalisa [Centro Euro-Mediterraneo per i Cambiamenti Climatici, and Istituto Nazionale di Geofisica e Vulcanologia, Bologna (Italy)

    2010-12-15

    Understanding the historical and future response of the global climate system to anthropogenic emissions of radiatively active atmospheric constituents has become a timely and compelling concern. At present, however, there are uncertainties in: the total radiative forcing associated with changes in the chemical composition of the atmosphere; the effective forcing applied to the climate system resulting from a (temporary) reduction via ocean-heat uptake; and the strength of the climate feedbacks that subsequently modify this forcing. Here a set of analyses derived from atmospheric general circulation model simulations are used to estimate the effective and total radiative forcing of the observed climate system due to anthropogenic emissions over the last 50 years of the twentieth century. They are also used to estimate the sensitivity of the observed climate system to these emissions, as well as the expected change in global surface temperatures once the climate system returns to radiative equilibrium. Results indicate that estimates of the effective radiative forcing and total radiative forcing associated with historical anthropogenic emissions differ across models. In addition estimates of the historical sensitivity of the climate to these emissions differ across models. However, results suggest that the variations in climate sensitivity and total climate forcing are not independent, and that the two vary inversely with respect to one another. As such, expected equilibrium temperature changes, which are given by the product of the total radiative forcing and the climate sensitivity, are relatively constant between models, particularly in comparison to results in which the total radiative forcing is assumed constant. Implications of these results for projected future climate forcings and subsequent responses are also discussed. (orig.)

  15. A Toolkit to Study Sensitivity of the Geant4 Predictions to the Variations of the Physics Model Parameters

    Energy Technology Data Exchange (ETDEWEB)

    Fields, Laura [Fermilab; Genser, Krzysztof [Fermilab; Hatcher, Robert [Fermilab; Kelsey, Michael [SLAC; Perdue, Gabriel [Fermilab; Wenzel, Hans [Fermilab; Wright, Dennis H. [SLAC; Yarba, Julia [Fermilab

    2017-08-21

    Geant4 is the leading detector simulation toolkit used in high energy physics to design detectors and to optimize calibration and reconstruction software. It employs a set of carefully validated physics models to simulate interactions of particles with matter across a wide range of interaction energies. These models, especially the hadronic ones, rely largely on directly measured cross-sections and phenomenological predictions with physically motivated parameters estimated by theoretical calculation or measurement. Because these models are tuned to cover a very wide range of possible simulation tasks, they may not always be optimized for a given process or a given material. This raises several critical questions, e.g. how sensitive Geant4 predictions are to the variations of the model parameters, or what uncertainties are associated with a particular tune of a Geant4 physics model, or a group of models, or how to consistently derive guidance for Geant4 model development and improvement from a wide range of available experimental data. We have designed and implemented a comprehensive, modular, user-friendly software toolkit to study and address such questions. It allows one to easily modify parameters of one or several Geant4 physics models involved in the simulation, and to perform collective analysis of multiple variants of the resulting physics observables of interest and comparison against a variety of corresponding experimental data. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. flexible run-time configurable workflow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented and illustrated with results obtained with Geant4 key hadronic models.

  16. Polynomic nonlinear dynamical systems - A residual sensitivity method for model reduction

    Science.gov (United States)

    Yurkovich, S.; Bugajski, D.; Sain, M.

    1985-01-01

    The motivation for using polynomic combinations of system states and inputs to model nonlinear dynamics systems is founded upon the classical theories of analysis and function representation. A feature of such representations is the need to make available all possible monomials in these variables, up to the degree specified, so as to provide for the description of widely varying functions within a broad class. For a particular application, however, certain monomials may be quite superfluous. This paper examines the possibility of removing monomials from the model in accordance with the level of sensitivity displayed by the residuals to their absence. Critical in these studies is the effect of system input excitation, and the effect of discarding monomial terms, upon the model parameter set. Therefore, model reduction is approached iteratively, with inputs redesigned at each iteration to ensure sufficient excitation of remaining monomials for parameter approximation. Examples are reported to illustrate the performance of such model reduction approaches.

  17. Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

    Science.gov (United States)

    Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende

    2014-01-01

    Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

  18. The effect of alternative seismotectonic models on PSHA results - a sensitivity study for two sites in Israel

    Science.gov (United States)

    Avital, Matan; Kamai, Ronnie; Davis, Michael; Dor, Ory

    2018-02-01

    We present a full probabilistic seismic hazard analysis (PSHA) sensitivity analysis for two sites in southern Israel - one in the near field of a major fault system and one farther away. The PSHA analysis is conducted for alternative source representations, using alternative model parameters for the main seismic sources, such as slip rate and Mmax, among others. The analysis also considers the effect of the ground motion prediction equation (GMPE) on the hazard results. In this way, the two types of epistemic uncertainty - modelling uncertainty and parametric uncertainty - are treated and addressed. We quantify the uncertainty propagation by testing its influence on the final calculated hazard, such that the controlling knowledge gaps are identified and can be treated in future studies. We find that current practice in Israel, as represented by the current version of the building code, grossly underestimates the hazard, by approximately 40 % in short return periods (e.g. 10 % in 50 years) and by as much as 150 % in long return periods (e.g. 10E-5). The analysis shows that this underestimation is most probably due to a combination of factors, including source definitions as well as the GMPE used for analysis.

  19. Aspartame sensitivity? A double blind randomised crossover study.

    Directory of Open Access Journals (Sweden)

    Thozhukat Sathyapalan

    Full Text Available Aspartame is a commonly used intense artificial sweetener, being approximately 200 times sweeter than sucrose. There have been concerns over aspartame since approval in the 1980s including a large anecdotal database reporting severe symptoms. The objective of this study was to compare the acute symptom effects of aspartame to a control preparation.This was a double-blind randomized cross over study conducted in a clinical research unit in United Kingdom. Forty-eight individual who has self reported sensitivity to aspartame were compared to 48 age and gender matched aspartame non-sensitive individuals. They were given aspartame (100mg-containing or control snack bars randomly at least 7 days apart. The main outcome measures were acute effects of aspartame measured using repeated ratings of 14 symptoms, biochemistry and metabonomics.Aspartame sensitive and non-sensitive participants differed psychologically at baseline in handling feelings and perceived stress. Sensitive participants had higher triglycerides (2.05 ± 1.44 vs. 1.26 ± 0.84mmol/L; p value 0.008 and lower HDL-C (1.16 ± 0.34 vs. 1.35 ± 0.54 mmol/L; p value 0.04, reflected in 1H NMR serum analysis that showed differences in the baseline lipid content between the two groups. Urine metabonomic studies showed no significant differences. None of the rated symptoms differed between aspartame and control bars, or between sensitive and control participants. However, aspartame sensitive participants rated more symptoms particularly in the first test session, whether this was placebo or control. Aspartame and control bars affected GLP-1, GIP, tyrosine and phenylalanine levels equally in both aspartame sensitive and non-sensitive subjects.Using a comprehensive battery of psychological tests, biochemistry and state of the art metabonomics there was no evidence of any acute adverse responses to aspartame. This independent study gives reassurance to both regulatory bodies and the public that

  20. Aspartame sensitivity? A double blind randomised crossover study.

    Science.gov (United States)

    Sathyapalan, Thozhukat; Thatcher, Natalie J; Hammersley, Richard; Rigby, Alan S; Courts, Fraser L; Pechlivanis, Alexandros; Gooderham, Nigel J; Holmes, Elaine; le Roux, Carel W; Atkin, Stephen L

    2015-01-01

    Aspartame is a commonly used intense artificial sweetener, being approximately 200 times sweeter than sucrose. There have been concerns over aspartame since approval in the 1980s including a large anecdotal database reporting severe symptoms. The objective of this study was to compare the acute symptom effects of aspartame to a control preparation. This was a double-blind randomized cross over study conducted in a clinical research unit in United Kingdom. Forty-eight individual who has self reported sensitivity to aspartame were compared to 48 age and gender matched aspartame non-sensitive individuals. They were given aspartame (100mg)-containing or control snack bars randomly at least 7 days apart. The main outcome measures were acute effects of aspartame measured using repeated ratings of 14 symptoms, biochemistry and metabonomics. Aspartame sensitive and non-sensitive participants differed psychologically at baseline in handling feelings and perceived stress. Sensitive participants had higher triglycerides (2.05 ± 1.44 vs. 1.26 ± 0.84mmol/L; p value 0.008) and lower HDL-C (1.16 ± 0.34 vs. 1.35 ± 0.54 mmol/L; p value 0.04), reflected in 1H NMR serum analysis that showed differences in the baseline lipid content between the two groups. Urine metabonomic studies showed no significant differences. None of the rated symptoms differed between aspartame and control bars, or between sensitive and control participants. However, aspartame sensitive participants rated more symptoms particularly in the first test session, whether this was placebo or control. Aspartame and control bars affected GLP-1, GIP, tyrosine and phenylalanine levels equally in both aspartame sensitive and non-sensitive subjects. Using a comprehensive battery of psychological tests, biochemistry and state of the art metabonomics there was no evidence of any acute adverse responses to aspartame. This independent study gives reassurance to both regulatory bodies and the public that acute ingestion of

  1. Chimera states in a Hodgkin-Huxley model of thermally sensitive neurons

    Science.gov (United States)

    Glaze, Tera A.; Lewis, Scott; Bahar, Sonya

    2016-08-01

    Chimera states occur when identically coupled groups of nonlinear oscillators exhibit radically different dynamics, with one group exhibiting synchronized oscillations and the other desynchronized behavior. This dynamical phenomenon has recently been studied in computational models and demonstrated experimentally in mechanical, optical, and chemical systems. The theoretical basis of these states is currently under active investigation. Chimera behavior is of particular relevance in the context of neural synchronization, given the phenomenon of unihemispheric sleep and the recent observation of asymmetric sleep in human patients with sleep apnea. The similarity of neural chimera states to neural "bump" states, which have been suggested as a model for working memory and visual orientation tuning in the cortex, adds to their interest as objects of study. Chimera states have been demonstrated in the FitzHugh-Nagumo model of excitable cells and in the Hindmarsh-Rose neural model. Here, we demonstrate chimera states and chimera-like behaviors in a Hodgkin-Huxley-type model of thermally sensitive neurons both in a system with Abrams-Strogatz (mean field) coupling and in a system with Kuramoto (distance-dependent) coupling. We map the regions of parameter space for which chimera behavior occurs in each of the two coupling schemes.

  2. Evaluation of Uncertainty and Sensitivity in Environmental Modeling at a Radioactive Waste Management Site

    Science.gov (United States)

    Stockton, T. B.; Black, P. K.; Catlett, K. M.; Tauxe, J. D.

    2002-05-01

    Environmental modeling is an essential component in the evaluation of regulatory compliance of radioactive waste management sites (RWMSs) at the Nevada Test Site in southern Nevada, USA. For those sites that are currently operating, further goals are to support integrated decision analysis for the development of acceptance criteria for future wastes, as well as site maintenance, closure, and monitoring. At these RWMSs, the principal pathways for release of contamination to the environment are upward towards the ground surface rather than downwards towards the deep water table. Biotic processes, such as burrow excavation and plant uptake and turnover, dominate this upward transport. A combined multi-pathway contaminant transport and risk assessment model was constructed using the GoldSim modeling platform. This platform facilitates probabilistic analysis of environmental systems, and is especially well suited for assessments involving radionuclide decay chains. The model employs probabilistic definitions of key parameters governing contaminant transport, with the goals of quantifying cumulative uncertainty in the estimation of performance measures and providing information necessary to perform sensitivity analyses. This modeling differs from previous radiological performance assessments (PAs) in that the modeling parameters are intended to be representative of the current knowledge, and the uncertainty in that knowledge, of parameter values rather than reflective of a conservative assessment approach. While a conservative PA may be sufficient to demonstrate regulatory compliance, a parametrically honest PA can also be used for more general site decision-making. In particular, a parametrically honest probabilistic modeling approach allows both uncertainty and sensitivity analyses to be explicitly coupled to the decision framework using a single set of model realizations. For example, sensitivity analysis provides a guide for analyzing the value of collecting more

  3. On sensitivity of gamma families to the model of nuclear interaction

    International Nuclear Information System (INIS)

    Krys, A.; Tomaszewski, A.; Wrotniak, J.A.

    1980-01-01

    A variety of 5 different models of nuclear interaction has been used in a Monte Carlo simulation of nuclear and electromagnetic showers in the atmosphere. The gamma families obtained from this simulation were processed in a way, analogous to one employed in analysis of Pamir experimental results. The sensitivity of observed pattern to the nuclear interaction model assumptions was investigated. Such sensitivity, though not a strong one, was found. In case of longitudinal (or energetical) family characteristics, the changes in nuclear interaction should be really large, if they were to be reflected in the experimental data -with all methodical error possibilities. The transverse characteristics of gamma families are more sensitive to the assumed transverse momentum distribution, but they feel the longitudinal features of nuclear interaction as well. Additionally, there was tested the dependence of observed family pattern on some methodical effects (resolving power of X-ray film, radial cut-off and energy underestimation.) (author)

  4. Sensitivity analysis of model output - a step towards robust safety indicators?

    International Nuclear Information System (INIS)

    Broed, R.; Pereira, A.; Moberg, L.

    2004-01-01

    The protection of the environment from ionising radiation challenges the radioecological community with the issue of harmonising disparate safety indicators. These indicators should preferably cover the whole spectrum of model predictions on chemo-toxic and radiation impact of contaminants. In question is not only the protection of man and biota but also of abiotic systems. In many cases modelling will constitute the basis for an evaluation of potential impact. It is recognised that uncertainty and sensitivity analysis of model output will play an important role in the 'construction' of safety indicators that are robust, reliable and easy to explain to all groups of stakeholders including the general public. However, environmental models of transport of radionuclides have some extreme characteristics. They are, a) complex, b) non-linear, c) include a huge number of input parameters, d) input parameters are associated with large or very large uncertainties, e) parameters are often correlated to each other, f) uncertainties other than parameter-driven may be present in the modelling system, g) space variability and time-dependence of parameters are present, h) model predictions may cover geological time scales. Consequently, uncertainty and sensitivity analysis are non-trivial tasks, challenging the decision-maker when it comes to the interpretation of safety indicators or the application of regulatory criteria. In this work we use the IAEA model ISAM, to make a set of Monte Carlo calculations. The ISAM model includes several nuclides and decay chains, many compartments and variable parameters covering the range of nuclide migration pathways from the near field to the biosphere. The goal of our calculations is to make a global sensitivity analysis. After extracting the non-influential parameters, the M.C. calculations are repeated with those parameters frozen. Reducing the number of parameters to a few ones will simplify the interpretation of the results and the use

  5. Sensitivity of a numerical wave model on wind re-analysis datasets

    Science.gov (United States)

    Lavidas, George; Venugopal, Vengatesan; Friedrich, Daniel

    2017-03-01

    Wind is the dominant process for wave generation. Detailed evaluation of metocean conditions strengthens our understanding of issues concerning potential offshore applications. However, the scarcity of buoys and high cost of monitoring systems pose a barrier to properly defining offshore conditions. Through use of numerical wave models, metocean conditions can be hindcasted and forecasted providing reliable characterisations. This study reports the sensitivity of wind inputs on a numerical wave model for the Scottish region. Two re-analysis wind datasets with different spatio-temporal characteristics are used, the ERA-Interim Re-Analysis and the CFSR-NCEP Re-Analysis dataset. Different wind products alter results, affecting the accuracy obtained. The scope of this study is to assess different available wind databases and provide information concerning the most appropriate wind dataset for the specific region, based on temporal, spatial and geographic terms for wave modelling and offshore applications. Both wind input datasets delivered results from the numerical wave model with good correlation. Wave results by the 1-h dataset have higher peaks and lower biases, in expense of a high scatter index. On the other hand, the 6-h dataset has lower scatter but higher biases. The study shows how wind dataset affects the numerical wave modelling performance, and that depending on location and study needs, different wind inputs should be considered.

  6. Testing the Nanoparticle-Allostatic Cross Adaptation-Sensitization Model for Homeopathic Remedy Effects

    Science.gov (United States)

    Bell, Iris R.; Koithan, Mary; Brooks, Audrey J.

    2012-01-01

    Key concepts of the Nanoparticle-Allostatic Cross-Adaptation-Sensitization (NPCAS) Model for the action of homeopathic remedies in living systems include source nanoparticles as low level environmental stressors, heterotypic hormesis, cross-adaptation, allostasis (stress response network), time-dependent sensitization with endogenous amplification and bidirectional change, and self-organizing complex adaptive systems. The model accommodates the requirement for measurable physical agents in the remedy (source nanoparticles and/or source adsorbed to silica nanoparticles). Hormetic adaptive responses in the organism, triggered by nanoparticles; bipolar, metaplastic change, dependent on the history of the organism. Clinical matching of the patient’s symptom picture, including modalities, to the symptom pattern that the source material can cause (cross-adaptation and cross-sensitization). Evidence for nanoparticle-related quantum macro-entanglement in homeopathic pathogenetic trials. This paper examines research implications of the model, discussing the following hypotheses: Variability in nanoparticle size, morphology, and aggregation affects remedy properties and reproducibility of findings. Homeopathic remedies modulate adaptive allostatic responses, with multiple dynamic short- and long-term effects. Simillimum remedy nanoparticles, as novel mild stressors corresponding to the organism’s dysfunction initiate time-dependent cross-sensitization, reversing the direction of dysfunctional reactivity to environmental stressors. The NPCAS model suggests a way forward for systematic research on homeopathy. The central proposition is that homeopathic treatment is a form of nanomedicine acting by modulation of endogenous adaptation and metaplastic amplification processes in the organism to enhance long-term systemic resilience and health. PMID:23290882

  7. Seismic analysis of steam generator and parameter sensitivity studies

    International Nuclear Information System (INIS)

    Qian Hao; Xu Dinggen; Yang Ren'an; Liang Xingyun

    2013-01-01

    Background: The steam generator (SG) serves as the primary means for removing the heat generated within the reactor core and is part of the reactor coolant system (RCS) pressure boundary. Purpose: Seismic analysis in required for SG, whose seismic category is Cat. I. Methods: The analysis model of SG is created with moisture separator assembly and tube bundle assembly herein. The seismic analysis is performed with RCS pipe and Reactor Pressure Vessel (RPV). Results: The seismic stress results of SG are obtained. In addition, parameter sensitivities of seismic analysis results are studied, such as the effect of another SG, support, anti-vibration bars (AVBs), and so on. Our results show that seismic results are sensitive to support and AVBs setting. Conclusions: The guidance and comments on these parameters are summarized for equipment design and analysis, which should be focused on in future new type NPP SG's research and design. (authors)

  8. Skin care products can aggravate epidermal function: studies in a murine model suggest a pathogenic role in sensitive skin.

    Science.gov (United States)

    Li, Zhengxiao; Hu, Lizhi; Elias, Peter M; Man, Mao-Qiang

    2018-02-01

    Sensitive skin is defined as a spectrum of unpleasant sensations in response to a variety of stimuli. However, only some skin care products provoke cutaneous symptoms in individuals with sensitive skin. Hence, it would be useful to identify products that could provoke cutaneous symptoms in individuals with sensitive skin. To assess whether vehicles, as well as certain branded skin care products, can alter epidermal function following topical applications to normal mouse skin. Following topical applications of individual vehicle or skin care product to C57BL/6J mice twice daily for 4 days, transepidermal water loss (TEWL) rates, stratum corneum (SC) hydration and skin surface pH were measured on treated versus untreated mouse skin with an MPA5 device and pH 900 pH meter. Our results show that all tested products induced abnormalities in epidermal functions of varying severity, including elevations in TEWL and skin surface pH, and reduced SC hydration. Our results suggest that mice can serve as a predictive model that could be used to evaluate the potential safety of skin care products in humans with sensitive skin. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  9. Modeling of Yb3+-sensitized Er3+-doped silica waveguide amplifiers

    DEFF Research Database (Denmark)

    Lester, Christian; Bjarklev, Anders Overgaard; Rasmussen, Thomas

    1995-01-01

    A model for Yb3+-sensitized Er3+-doped silica waveguide amplifiers is described and numerically investigated in the small-signal regime. The amplified spontaneous emission in the ytterbium-band and the quenching process between excited erbium ions are included in the model. For pump wavelengths...

  10. Sensitivity analysis in oxidation ditch modelling: the effect of variations in stoichiometric, kinetic and operating parameters on the performance indices

    NARCIS (Netherlands)

    Abusam, A.A.A.; Keesman, K.J.; Straten, van G.; Spanjers, H.; Meinema, K.

    2001-01-01

    This paper demonstrates the application of the factorial sensitivity analysis methodology in studying the influence of variations in stoichiometric, kinetic and operating parameters on the performance indices of an oxidation ditch simulation model (benchmark). Factorial sensitivity analysis

  11. Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection.

    Science.gov (United States)

    Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

    2015-01-01

    Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.

  12. Study plan for the sensitivity analysis of the Terrain-Responsive Atmospheric Code (TRAC)

    International Nuclear Information System (INIS)

    Restrepo, L.F.; Deitesfeld, C.A.

    1987-01-01

    Rocky Flats Plant, Golden, Colorado is presently developing a computer code to model the dispersion of potential or actual releases of radioactive or toxic materials to the environment, along with the public consequences from these releases. The model, the Terrain-Responsive Atmospheric Code (TRAC), considers several complex features which could affect the overall dispersion and consequences. To help validate TRAC, a sensitivity analysis is being planned to determine how sensitive the model's solutions are to input variables. This report contains a brief description of the code, along with a list of tasks and resources needed to complete the sensitivity analysis

  13. Seismic sensitivity study of a generic CANDU nuclear power plant: Soil-structure interaction

    International Nuclear Information System (INIS)

    Lee, L.S.S.; Duff, C.G.

    1983-01-01

    The seismic sensitivity and capability study for a generic CANDU Plant is part of an overall development program of design standardization. The purpose of this paper is to investigate the sensitivities of structural responses and floor response spectra (FRS) to variations of structural and soil parameters. In the seismic design standardization, a wide range of soil conditions is considered and the envelopes of the resulting site spectra (soil-structure interaction effect) are then used for the design of the generic plant. The nuclear island structures considered herein have different relative stiffness and one of them has two layout/structure schemes: one is relatively flexible and the other is moderately stiff. In the preliminary phase of the seismic sensitivity study presented hereby, the soil-structure interaction seismic analysis is based on the half-space modelling (soil-spring lumped-mass) method and the response spectrum method for the seismic responses. Distinct patterns and sensitivity of the site spectrum analysis for structure schemes of different relative stiffness and for different structural elevations are observed and discussed. (orig.)

  14. How can we reduce phosphorus export from lowland polders? Implications from a sensitivity analysis of a coupled model.

    Science.gov (United States)

    Huang, Jiacong; Gao, Junfeng; Yan, Renhua

    2016-08-15

    Phosphorus (P) export from lowland polders has caused severe water pollution. Numerical models are an important resource that help water managers control P export. This study coupled three models, i.e., Phosphorus Dynamic model for Polders (PDP), Integrated Catchments model of Phosphorus dynamics (INCA-P) and Universal Soil Loss Equation (USLE), to describe the P dynamics in polders. Based on the coupled models and a dataset collected from Polder Jian in China, sensitivity analysis were carried out to analyze the cause-effect relationships between environmental factors and P export from Polder Jian. The sensitivity analysis results showed that P export from Polder Jian were strongly affected by air temperature, precipitation and fertilization. Proper fertilization management should be a strategic priority for reducing P export from Polder Jian. This study demonstrated the success of model coupling, and its application in investigating potential strategies to support pollution control in polder systems. Copyright © 2016. Published by Elsevier B.V.

  15. Is Freedom Contagious? A Self-Regulatory Model of Reactance and Sensitivity to Deviant Peers.

    Science.gov (United States)

    Leander, N Pontus; vanDellen, Michelle R; Rachl-Willberger, Judith; Shah, James Y; Fitzsimons, Gavan J; Chartrand, Tanya L

    2016-12-01

    Psychological reactance is typically assumed to motivate resistance to controlling peer influences and societal prohibitions. However, some peer influences encourage behaviors prohibited by society. We consider whether reactant individuals are sensitive to such opportunities to enhance their autonomy. We specifically propose a self-regulatory perspective on reactance, wherein freedom/autonomy is the superordinate goal, and thus highly reactant individuals will be sensitive to peer influences that could enhance their behavioral freedoms. In two studies, we find that reactant individuals can be cooperative in response to autonomy-supportive peer influences. Participants read a scenario in which a peer's intentions to engage in substance use were manipulated to imply freedom of choice or not. Results indicated that highly reactant participants were sensitive to deviant peers whose own behavior towards alcohol (Study 1, N = 160) or marijuana (Study 2, N = 124) appeared to be motivated by autonomy and thus afforded free choice. Altogether, the results support a self-regulatory model of reactance, wherein deviant peer influence can be a means to pursue autonomy.

  16. Sensitivity Analysis on Fire Modeling of Main Control Board Fire Using Fire Dynamics Simulator

    International Nuclear Information System (INIS)

    Kang, Dae Il; Lim, Ho Gon

    2015-01-01

    In this study, sensitivity analyses for an MCB fire were performed to identify the effects on the MCR forced abandonment time according to the changes of height and number for fire initiation places. Hanul Unit 3 NPP was selected as a reference plant for this study. In this study, sensitivity analyses for an MCB fire were performed to identify the effects on the MCR forced abandonment time according to the changes of height and number of fire initiation places. A main control board (MCB) fire can cause a forced main control room (MCR) abandonment of the operators as well as the function failures or spurious operations of the control and instrumentation-related components. If the MCR cannot be habitable, a safe shutdown from outside the MCR can be achieved and maintained at an alternate shutdown panel independent from the MCR. When the fire modeling for an electrical cabinet such as an MCB was performed, its many input parameters can affect the fire simulation results. This study results showed that the decrease in the height of fire ignition place and the use of single fire ignition place in fire modeling for the propagating fire shortened MCR abandonment time

  17. Sensitivity Analysis on Fire Modeling of Main Control Board Fire Using Fire Dynamics Simulator

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Dae Il; Lim, Ho Gon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-10-15

    In this study, sensitivity analyses for an MCB fire were performed to identify the effects on the MCR forced abandonment time according to the changes of height and number for fire initiation places. Hanul Unit 3 NPP was selected as a reference plant for this study. In this study, sensitivity analyses for an MCB fire were performed to identify the effects on the MCR forced abandonment time according to the changes of height and number of fire initiation places. A main control board (MCB) fire can cause a forced main control room (MCR) abandonment of the operators as well as the function failures or spurious operations of the control and instrumentation-related components. If the MCR cannot be habitable, a safe shutdown from outside the MCR can be achieved and maintained at an alternate shutdown panel independent from the MCR. When the fire modeling for an electrical cabinet such as an MCB was performed, its many input parameters can affect the fire simulation results. This study results showed that the decrease in the height of fire ignition place and the use of single fire ignition place in fire modeling for the propagating fire shortened MCR abandonment time.

  18. Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

    Science.gov (United States)

    Battisti, R.; Sentelhas, P. C.; Boote, K. J.

    2017-12-01

    Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

  19. Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

    Science.gov (United States)

    Battisti, R.; Sentelhas, P. C.; Boote, K. J.

    2018-05-01

    Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

  20. Visualization of nonlinear kernel models in neuroimaging by sensitivity maps

    DEFF Research Database (Denmark)

    Rasmussen, Peter Mondrup; Hansen, Lars Kai; Madsen, Kristoffer Hougaard

    There is significant current interest in decoding mental states from neuroimages. In this context kernel methods, e.g., support vector machines (SVM) are frequently adopted to learn statistical relations between patterns of brain activation and experimental conditions. In this paper we focus...... on visualization of such nonlinear kernel models. Specifically, we investigate the sensitivity map as a technique for generation of global summary maps of kernel classification methods. We illustrate the performance of the sensitivity map on functional magnetic resonance (fMRI) data based on visual stimuli. We...

  1. Identification of the most sensitive parameters in the activated sludge model implemented in BioWin software.

    Science.gov (United States)

    Liwarska-Bizukojc, Ewa; Biernacki, Rafal

    2010-10-01

    In order to simulate biological wastewater treatment processes, data concerning wastewater and sludge composition, process kinetics and stoichiometry are required. Selection of the most sensitive parameters is an important step of model calibration. The aim of this work is to verify the predictability of the activated sludge model, which is implemented in BioWin software, and select its most influential kinetic and stoichiometric parameters with the help of sensitivity analysis approach. Two different measures of sensitivity are applied: the normalised sensitivity coefficient (S(i,j)) and the mean square sensitivity measure (delta(j)(msqr)). It occurs that 17 kinetic and stoichiometric parameters of the BioWin activated sludge (AS) model can be regarded as influential on the basis of S(i,j) calculations. Half of the influential parameters are associated with growth and decay of phosphorus accumulating organisms (PAOs). The identification of the set of the most sensitive parameters should support the users of this model and initiate the elaboration of determination procedures for the parameters, for which it has not been done yet. Copyright 2010 Elsevier Ltd. All rights reserved.

  2. Commensurate comparisons of models with energy budget observations reveal consistent climate sensitivities

    Science.gov (United States)

    Armour, K.

    2017-12-01

    Global energy budget observations have been widely used to constrain the effective, or instantaneous climate sensitivity (ICS), producing median estimates around 2°C (Otto et al. 2013; Lewis & Curry 2015). A key question is whether the comprehensive climate models used to project future warming are consistent with these energy budget estimates of ICS. Yet, performing such comparisons has proven challenging. Within models, values of ICS robustly vary over time, as surface temperature patterns evolve with transient warming, and are generally smaller than the values of equilibrium climate sensitivity (ECS). Naively comparing values of ECS in CMIP5 models (median of about 3.4°C) to observation-based values of ICS has led to the suggestion that models are overly sensitive. This apparent discrepancy can partially be resolved by (i) comparing observation-based values of ICS to model values of ICS relevant for historical warming (Armour 2017; Proistosescu & Huybers 2017); (ii) taking into account the "efficacies" of non-CO2 radiative forcing agents (Marvel et al. 2015); and (iii) accounting for the sparseness of historical temperature observations and differences in sea-surface temperature and near-surface air temperature over the oceans (Richardson et al. 2016). Another potential source of discrepancy is a mismatch between observed and simulated surface temperature patterns over recent decades, due to either natural variability or model deficiencies in simulating historical warming patterns. The nature of the mismatch is such that simulated patterns can lead to more positive radiative feedbacks (higher ICS) relative to those engendered by observed patterns. The magnitude of this effect has not yet been addressed. Here we outline an approach to perform fully commensurate comparisons of climate models with global energy budget observations that take all of the above effects into account. We find that when apples-to-apples comparisons are made, values of ICS in models are

  3. Good Modeling Practice for PAT Applications: Propagation of Input Uncertainty and Sensitivity Analysis

    DEFF Research Database (Denmark)

    Sin, Gürkan; Gernaey, Krist; Eliasson Lantz, Anna

    2009-01-01

    The uncertainty and sensitivity analysis are evaluated for their usefulness as part of the model-building within Process Analytical Technology applications. A mechanistic model describing a batch cultivation of Streptomyces coelicolor for antibiotic production was used as case study. The input...... compared to the large uncertainty observed in the antibiotic and off-gas CO2 predictions. The output uncertainty was observed to be lower during the exponential growth phase, while higher in the stationary and death phases - meaning the model describes some periods better than others. To understand which...... promising for helping to build reliable mechanistic models and to interpret the model outputs properly. These tools make part of good modeling practice, which can contribute to successful PAT applications for increased process understanding, operation and control purposes. © 2009 American Institute...

  4. Inferring climate sensitivity from volcanic events

    Energy Technology Data Exchange (ETDEWEB)

    Boer, G.J. [Environment Canada, University of Victoria, Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); Stowasser, M.; Hamilton, K. [University of Hawaii, International Pacific Research Centre, Honolulu, HI (United States)

    2007-04-15

    The possibility of estimating the equilibrium climate sensitivity of the earth-system from observations following explosive volcanic eruptions is assessed in the context of a perfect model study. Two modern climate models (the CCCma CGCM3 and the NCAR CCSM2) with different equilibrium climate sensitivities are employed in the investigation. The models are perturbed with the same transient volcano-like forcing and the responses analysed to infer climate sensitivities. For volcano-like forcing the global mean surface temperature responses of the two models are very similar, despite their differing equilibrium climate sensitivities, indicating that climate sensitivity cannot be inferred from the temperature record alone even if the forcing is known. Equilibrium climate sensitivities can be reasonably determined only if both the forcing and the change in heat storage in the system are known very accurately. The geographic patterns of clear-sky atmosphere/surface and cloud feedbacks are similar for both the transient volcano-like and near-equilibrium constant forcing simulations showing that, to a considerable extent, the same feedback processes are invoked, and determine the climate sensitivity, in both cases. (orig.)

  5. A sensitivity analysis of the WIPP disposal room model: Phase 1

    Energy Technology Data Exchange (ETDEWEB)

    Labreche, D.A.; Beikmann, M.A. [RE/SPEC, Inc., Albuquerque, NM (United States); Osnes, J.D. [RE/SPEC, Inc., Rapid City, SD (United States); Butcher, B.M. [Sandia National Labs., Albuquerque, NM (United States)

    1995-07-01

    The WIPP Disposal Room Model (DRM) is a numerical model with three major components constitutive models of TRU waste, crushed salt backfill, and intact halite -- and several secondary components, including air gap elements, slidelines, and assumptions on symmetry and geometry. A sensitivity analysis of the Disposal Room Model was initiated on two of the three major components (waste and backfill models) and on several secondary components as a group. The immediate goal of this component sensitivity analysis (Phase I) was to sort (rank) model parameters in terms of their relative importance to model response so that a Monte Carlo analysis on a reduced set of DRM parameters could be performed under Phase II. The goal of the Phase II analysis will be to develop a probabilistic definition of a disposal room porosity surface (porosity, gas volume, time) that could be used in WIPP Performance Assessment analyses. This report documents a literature survey which quantifies the relative importance of the secondary room components to room closure, a differential analysis of the creep consolidation model and definition of a follow-up Monte Carlo analysis of the model, and an analysis and refitting of the waste component data on which a volumetric plasticity model of TRU drum waste is based. A summary, evaluation of progress, and recommendations for future work conclude the report.

  6. Global sensitivity analysis of GEOS-Chem modeled ozone and hydrogen oxides during the INTEX campaigns

    Directory of Open Access Journals (Sweden)

    K. E. Christian

    2018-02-01

    Full Text Available Making sense of modeled atmospheric composition requires not only comparison to in situ measurements but also knowing and quantifying the sensitivity of the model to its input factors. Using a global sensitivity method involving the simultaneous perturbation of many chemical transport model input factors, we find the model uncertainty for ozone (O3, hydroxyl radical (OH, and hydroperoxyl radical (HO2 mixing ratios, and apportion this uncertainty to specific model inputs for the DC-8 flight tracks corresponding to the NASA Intercontinental Chemical Transport Experiment (INTEX campaigns of 2004 and 2006. In general, when uncertainties in modeled and measured quantities are accounted for, we find agreement between modeled and measured oxidant mixing ratios with the exception of ozone during the Houston flights of the INTEX-B campaign and HO2 for the flights over the northernmost Pacific Ocean during INTEX-B. For ozone and OH, modeled mixing ratios were most sensitive to a bevy of emissions, notably lightning NOx, various surface NOx sources, and isoprene. HO2 mixing ratios were most sensitive to CO and isoprene emissions as well as the aerosol uptake of HO2. With ozone and OH being generally overpredicted by the model, we find better agreement between modeled and measured vertical profiles when reducing NOx emissions from surface as well as lightning sources.

  7. Application of uncertainty and sensitivity analysis to the air quality SHERPA modelling tool

    Science.gov (United States)

    Pisoni, E.; Albrecht, D.; Mara, T. A.; Rosati, R.; Tarantola, S.; Thunis, P.

    2018-06-01

    Air quality has significantly improved in Europe over the past few decades. Nonetheless we still find high concentrations in measurements mainly in specific regions or cities. This dimensional shift, from EU-wide to hot-spot exceedances, calls for a novel approach to regional air quality management (to complement EU-wide existing policies). The SHERPA (Screening for High Emission Reduction Potentials on Air quality) modelling tool was developed in this context. It provides an additional tool to be used in support to regional/local decision makers responsible for the design of air quality plans. It is therefore important to evaluate the quality of the SHERPA model, and its behavior in the face of various kinds of uncertainty. Uncertainty and sensitivity analysis techniques can be used for this purpose. They both reveal the links between assumptions and forecasts, help in-model simplification and may highlight unexpected relationships between inputs and outputs. Thus, a policy steered SHERPA module - predicting air quality improvement linked to emission reduction scenarios - was evaluated by means of (1) uncertainty analysis (UA) to quantify uncertainty in the model output, and (2) by sensitivity analysis (SA) to identify the most influential input sources of this uncertainty. The results of this study provide relevant information about the key variables driving the SHERPA output uncertainty, and advise policy-makers and modellers where to place their efforts for an improved decision-making process.

  8. Sensitivity of wetland methane emissions to model assumptions: application and model testing against site observations

    Directory of Open Access Journals (Sweden)

    L. Meng

    2012-07-01

    Full Text Available Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources are still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011 into the Community Land Model 4.0 (CLM4CN in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model, because there are large differences between simulated fractional inundation and satellite observations, and thus we do not use CLM4-simulated hydrology to predict inundated areas. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid-cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH4 yr−1 (including the soil sink and rice paddy emissions in the year 2000 were 42 Tg CH4 yr−1. Tropical wetlands contributed 201 Tg CH4 yr−1, or 78% of the global wetland flux. Northern latitude (>50 N systems contributed 12 Tg CH4 yr−1. However, sensitivity studies show a large range (150–346 Tg CH4 yr−1 in predicted global methane emissions (excluding emissions from rice paddies. The large range is

  9. Sensitivity study on the parameters of the regional hydrology model for the Nevada nuclear waste storage investigations

    International Nuclear Information System (INIS)

    Iman, R.L.; Davenport, J.M.; Waddell, R.K.; Stephens, H.P.; Leap, D.I.

    1979-01-01

    Statistical methodology has been applied to the investigation of the regional hydrologic systems of a large area encompassing the Nevada Test Site (NTS) as a part of the overall evaluation of the NTS for deep geologic disposal of nuclear waste. Statistical techniques including Latin hypercube sampling were used to perform a sensitivity analysis on a two-dimensional finite-element code of 16 geohydrologic zones used to model the regional ground-water flow system. The Latin hypercube sample has been modified to include correlations between corresponding variables from zone to zone. From the results of sensitivity analysis it was found that: (1) the ranking of the relative importance of input variables between locations within the same geohydrologic zone were similar, but not identical; and (2) inclusion of a correlation structure for input variables had a significant effect on the ranking of their relative importance. The significance of these results is discussed with respect to the hydrology of the region

  10. Comparison of global sensitivity analysis methods – Application to fuel behavior modeling

    Energy Technology Data Exchange (ETDEWEB)

    Ikonen, Timo, E-mail: timo.ikonen@vtt.fi

    2016-02-15

    Highlights: • Several global sensitivity analysis methods are compared. • The methods’ applicability to nuclear fuel performance simulations is assessed. • The implications of large input uncertainties and complex models are discussed. • Alternative strategies to perform sensitivity analyses are proposed. - Abstract: Fuel performance codes have two characteristics that make their sensitivity analysis challenging: large uncertainties in input parameters and complex, non-linear and non-additive structure of the models. The complex structure of the code leads to interactions between inputs that show as cross terms in the sensitivity analysis. Due to the large uncertainties of the inputs these interactions are significant, sometimes even dominating the sensitivity analysis. For the same reason, standard linearization techniques do not usually perform well in the analysis of fuel performance codes. More sophisticated methods are typically needed in the analysis. To this end, we compare the performance of several sensitivity analysis methods in the analysis of a steady state FRAPCON simulation. The comparison of importance rankings obtained with the various methods shows that even the simplest methods can be sufficient for the analysis of fuel maximum temperature. However, the analysis of the gap conductance requires more powerful methods that take into account the interactions of the inputs. In some cases, moment-independent methods are needed. We also investigate the computational cost of the various methods and present recommendations as to which methods to use in the analysis.

  11. Selecting Sensitive Parameter Subsets in Dynamical Models With Application to Biomechanical System Identification.

    Science.gov (United States)

    Ramadan, Ahmed; Boss, Connor; Choi, Jongeun; Peter Reeves, N; Cholewicki, Jacek; Popovich, John M; Radcliffe, Clark J

    2018-07-01

    Estimating many parameters of biomechanical systems with limited data may achieve good fit but may also increase 95% confidence intervals in parameter estimates. This results in poor identifiability in the estimation problem. Therefore, we propose a novel method to select sensitive biomechanical model parameters that should be estimated, while fixing the remaining parameters to values obtained from preliminary estimation. Our method relies on identifying the parameters to which the measurement output is most sensitive. The proposed method is based on the Fisher information matrix (FIM). It was compared against the nonlinear least absolute shrinkage and selection operator (LASSO) method to guide modelers on the pros and cons of our FIM method. We present an application identifying a biomechanical parametric model of a head position-tracking task for ten human subjects. Using measured data, our method (1) reduced model complexity by only requiring five out of twelve parameters to be estimated, (2) significantly reduced parameter 95% confidence intervals by up to 89% of the original confidence interval, (3) maintained goodness of fit measured by variance accounted for (VAF) at 82%, (4) reduced computation time, where our FIM method was 164 times faster than the LASSO method, and (5) selected similar sensitive parameters to the LASSO method, where three out of five selected sensitive parameters were shared by FIM and LASSO methods.

  12. A sensitivity study on modeling black carbon in snow and its radiative forcing over the Arctic and Northern China

    International Nuclear Information System (INIS)

    Qian, Yun; Wang, Hailong; Rasch, Philip J; Zhang, Rudong; Flanner, Mark G

    2014-01-01

    Black carbon in snow (BCS) simulated in the Community Atmosphere Model (CAM5) is evaluated against measurements over Northern China and the Arctic, and its sensitivity to atmospheric deposition and two parameters that affect post-depositional enrichment is explored. Improvements in atmospheric BC transport and deposition significantly reduce the biases (by a factor of two) in the estimation of BCS concentration over both Northern China and the Arctic. Further sensitivity simulations using the improved CAM5 indicate that the melt-water scavenging efficiency (MSE) parameter plays an important role in regulating BC concentrations in the Arctic through the post-depositional enrichment, which not only drastically changes the amplitude but also shifts the seasonal cycle of the BCS concentration and its radiative forcing in the Arctic. The impact of the snow aging scaling factor (SAF) on BCS shows more complex latitudinal and seasonal dependence, and overall impact of SAF is much smaller than that of MSE. The improvements of BC transport and deposition in CAM5 have a stronger influence on BCS than perturbations of the two snow model parameters in Northern China. (letters)

  13. An analysis of sensitivity and uncertainty associated with the use of the HSPF model for EIA applications

    Energy Technology Data Exchange (ETDEWEB)

    Biftu, G.F.; Beersing, A.; Wu, S.; Ade, F. [Golder Associates, Calgary, AB (Canada)

    2005-07-01

    An outline of a new approach to assessing the sensitivity and uncertainty associated with surface water modelling results using Hydrological Simulation Program-Fortran (HSPF) was presented, as well as the results of a sensitivity and uncertainty analysis. The HSPF model is often used to characterize the hydrological processes in watersheds within the oil sands region. Typical applications of HSPF included calibration of the model parameters using data from gauged watersheds, as well as validation of calibrated models with data sets. Additionally, simulations are often conducted to make flow predictions to support the environmental impact assessment (EIA) process. However, a key aspect of the modelling components of the EIA process is the sensitivity and uncertainty of the modelling results as compared to model parameters. Many of the variations in the HSPF model's outputs are caused by a small number of model parameters and outputs. A sensitivity analysis was performed to identify and focus on key parameters and assumptions that have the most influence on the model's outputs. Analysis entailed varying each parameter in turn, within a range, and examining the resulting relative changes in the model outputs. This analysis consisted of the selection of probability distributions to characterize the uncertainty in the model's key sensitive parameters, as well as the use of Monte Carlo and HSPF simulation to determine the uncertainty in model outputs. tabs, figs.

  14. Subsurface stormflow modeling with sensitivity analysis using a Latin-hypercube sampling technique

    International Nuclear Information System (INIS)

    Gwo, J.P.; Toran, L.E.; Morris, M.D.; Wilson, G.V.

    1994-09-01

    Subsurface stormflow, because of its dynamic and nonlinear features, has been a very challenging process in both field experiments and modeling studies. The disposal of wastes in subsurface stormflow and vadose zones at Oak Ridge National Laboratory, however, demands more effort to characterize these flow zones and to study their dynamic flow processes. Field data and modeling studies for these flow zones are relatively scarce, and the effect of engineering designs on the flow processes is poorly understood. On the basis of a risk assessment framework and a conceptual model for the Oak Ridge Reservation area, numerical models of a proposed waste disposal site were built, and a Latin-hypercube simulation technique was used to study the uncertainty of model parameters. Four scenarios, with three engineering designs, were simulated, and the effectiveness of the engineering designs was evaluated. Sensitivity analysis of model parameters suggested that hydraulic conductivity was the most influential parameter. However, local heterogeneities may alter flow patterns and result in complex recharge and discharge patterns. Hydraulic conductivity, therefore, may not be used as the only reference for subsurface flow monitoring and engineering operations. Neither of the two engineering designs, capping and French drains, was found to be effective in hydrologically isolating downslope waste trenches. However, pressure head contours indicated that combinations of both designs may prove more effective than either one alone

  15. Significance of uncertainties derived from settling tank model structure and parameters on predicting WWTP performance - A global sensitivity analysis study

    DEFF Research Database (Denmark)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen

    2011-01-01

    Uncertainty derived from one of the process models – such as one-dimensional secondary settling tank (SST) models – can impact the output of the other process models, e.g., biokinetic (ASM1), as well as the integrated wastewater treatment plant (WWTP) models. The model structure and parameter...... and from the last aerobic bioreactor upstream to the SST (Garrett/hydraulic method). For model structure uncertainty, two one-dimensional secondary settling tank (1-D SST) models are assessed, including a first-order model (the widely used Takács-model), in which the feasibility of using measured...... uncertainty of settler models can therefore propagate, and add to the uncertainties in prediction of any plant performance criteria. Here we present an assessment of the relative significance of secondary settling model performance in WWTP simulations. We perform a global sensitivity analysis (GSA) based...

  16. The Influence of Climate Change on Atmospheric Deposition of Mercury in the Arctic—A Model Sensitivity Study

    Science.gov (United States)

    Hansen, Kaj M.; Christensen, Jesper H.; Brandt, Jørgen

    2015-01-01

    Mercury (Hg) is a global pollutant with adverse health effects on humans and wildlife. It is of special concern in the Arctic due to accumulation in the food web and exposure of the Arctic population through a rich marine diet. Climate change may alter the exposure of the Arctic population to Hg. We have investigated the effect of climate change on the atmospheric Hg transport to and deposition within the Arctic by making a sensitivity study of how the atmospheric chemistry-transport model Danish Eulerian Hemispheric Model (DEHM) reacts to climate change forcing. The total deposition of Hg to the Arctic is 18% lower in the 2090s compared to the 1990s under the applied Special Report on Emissions Scenarios (SRES-A1B) climate scenario. Asia is the major anthropogenic source area (25% of the deposition to the Arctic) followed by Europe (6%) and North America (5%), with the rest arising from the background concentration, and this is independent of the climate. DEHM predicts between a 6% increase (Status Quo scenario) and a 37% decrease (zero anthropogenic emissions scenario) in Hg deposition to the Arctic depending on the applied emission scenario, while the combined effect of future climate and emission changes results in up to 47% lower Hg deposition. PMID:26378551

  17. Relative sensitivity analysis of the predictive properties of sloppy models.

    Science.gov (United States)

    Myasnikova, Ekaterina; Spirov, Alexander

    2018-01-25

    Commonly among the model parameters characterizing complex biological systems are those that do not significantly influence the quality of the fit to experimental data, so-called "sloppy" parameters. The sloppiness can be mathematically expressed through saturating response functions (Hill's, sigmoid) thereby embodying biological mechanisms responsible for the system robustness to external perturbations. However, if a sloppy model is used for the prediction of the system behavior at the altered input (e.g. knock out mutations, natural expression variability), it may demonstrate the poor predictive power due to the ambiguity in the parameter estimates. We introduce a method of the predictive power evaluation under the parameter estimation uncertainty, Relative Sensitivity Analysis. The prediction problem is addressed in the context of gene circuit models describing the dynamics of segmentation gene expression in Drosophila embryo. Gene regulation in these models is introduced by a saturating sigmoid function of the concentrations of the regulatory gene products. We show how our approach can be applied to characterize the essential difference between the sensitivity properties of robust and non-robust solutions and select among the existing solutions those providing the correct system behavior at any reasonable input. In general, the method allows to uncover the sources of incorrect predictions and proposes the way to overcome the estimation uncertainties.

  18. Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil.

    Science.gov (United States)

    Battisti, R; Sentelhas, P C; Boote, K J

    2018-05-01

    Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha -1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .

  19. Sensitivity analysis and calibration of a dynamic physically based slope stability model

    Science.gov (United States)

    Zieher, Thomas; Rutzinger, Martin; Schneider-Muntau, Barbara; Perzl, Frank; Leidinger, David; Formayer, Herbert; Geitner, Clemens

    2017-06-01

    Physically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of parameter values, (ii) shortcomings of the selected model, (iii) uncertainties of laboratory tests and field measurements or (iv) parameters that cannot be derived experimentally or measured in the field (e.g. calibration constants). While systematic parameter calibration is a common task in hydrological modelling, this is rarely done using physically based slope stability models. In the present study a dynamic, physically based, coupled hydrological-geomechanical slope stability model is calibrated based on a limited number of laboratory tests and a detailed multitemporal shallow landslide inventory covering two landslide-triggering rainfall events in the Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified based on a local one-at-a-time sensitivity analysis. These parameters (hydraulic conductivity, specific storage, angle of internal friction for effective stress, cohesion for effective stress) are systematically sampled and calibrated for a landslide-triggering rainfall event in August 2005. The identified model ensemble, including 25 behavioural model runs with the highest portion of correctly predicted landslides and non-landslides, is then validated with another landslide-triggering rainfall event in May 1999. The identified model ensemble correctly predicts the location and the supposed triggering timing of 73.0 % of the observed landslides triggered in August 2005 and 91.5 % of the observed landslides triggered in May 1999. Results of the model ensemble driven with raised precipitation input reveal a slight increase in areas potentially affected by slope failure. At the same time, the peak run-off increases more markedly, suggesting that

  20. Structure sensitivity in adsorption

    DEFF Research Database (Denmark)

    Hammer, Bjørk; Nielsen, Ole Holm; Nørskov, Jens Kehlet

    1997-01-01

    The structure sensitivity of CO adsorption on different flat, stepped, kinked and reconstructed Pt surfaces is studied using large-scale density-functional calculations. We find an extremely strong structure sensitivity in the adsorption energy with variations up to 1 eV (or 100%) from one...... structure to the next. We propose a model to explain this behavior, and use it to discuss more generally the origin of structure sensitivity in heterogeneous catalysis....

  1. Using sparse polynomial chaos expansions for the global sensitivity analysis of groundwater lifetime expectancy in a multi-layered hydrogeological model

    International Nuclear Information System (INIS)

    Deman, G.; Konakli, K.; Sudret, B.; Kerrou, J.; Perrochet, P.; Benabderrahmane, H.

    2016-01-01

    The study makes use of polynomial chaos expansions to compute Sobol' indices within the frame of a global sensitivity analysis of hydro-dispersive parameters in a simplified vertical cross-section of a segment of the subsurface of the Paris Basin. Applying conservative ranges, the uncertainty in 78 input variables is propagated upon the mean lifetime expectancy of water molecules departing from a specific location within a highly confining layer situated in the middle of the model domain. Lifetime expectancy is a hydrogeological performance measure pertinent to safety analysis with respect to subsurface contaminants, such as radionuclides. The sensitivity analysis indicates that the variability in the mean lifetime expectancy can be sufficiently explained by the uncertainty in the petrofacies, i.e. the sets of porosity and hydraulic conductivity, of only a few layers of the model. The obtained results provide guidance regarding the uncertainty modeling in future investigations employing detailed numerical models of the subsurface of the Paris Basin. Moreover, the study demonstrates the high efficiency of sparse polynomial chaos expansions in computing Sobol' indices for high-dimensional models. - Highlights: • Global sensitivity analysis of a 2D 15-layer groundwater flow model is conducted. • A high-dimensional random input comprising 78 parameters is considered. • The variability in the mean lifetime expectancy for the central layer is examined. • Sparse polynomial chaos expansions are used to compute Sobol' sensitivity indices. • The petrofacies of a few layers can sufficiently explain the response variance.

  2. Quantification of remodeling parameter sensitivity - assessed by a computer simulation model

    DEFF Research Database (Denmark)

    Thomsen, J.S.; Mosekilde, Li.; Mosekilde, Erik

    1996-01-01

    We have used a computer simulation model to evaluate the effect of several bone remodeling parameters on vertebral cancellus bone. The menopause was chosen as the base case scenario, and the sensitivity of the model to the following parameters was investigated: activation frequency, formation bal....... However, the formation balance was responsible for the greater part of total mass loss....

  3. Sensitivity to plant modelling uncertainties in optimal feedback control of sound radiation from a panel

    DEFF Research Database (Denmark)

    Mørkholt, Jakob

    1997-01-01

    Optimal feedback control of broadband sound radiation from a rectangular baffled panel has been investigated through computer simulations. Special emphasis has been put on the sensitivity of the optimal feedback control to uncertainties in the modelling of the system under control.A model...... in terms of a set of radiation filters modelling the radiation dynamics.Linear quadratic feedback control applied to the panel in order to minimise the radiated sound power has then been simulated. The sensitivity of the model based controller to modelling uncertainties when using feedback from actual...

  4. Sensitivity of Rooftop PV Projections in the SunShot Vision Study to Market Assumptions

    Energy Technology Data Exchange (ETDEWEB)

    Drury, E.; Denholm, P.; Margolis, R.

    2013-01-01

    The SunShot Vision Study explored the potential growth of solar markets if solar prices decreased by about 75% from 2010 to 2020. The SolarDS model was used to simulate rooftop PV demand for this study, based on several PV market assumptions--future electricity rates, customer access to financing, and others--in addition to the SunShot PV price projections. This paper finds that modeled PV demand is highly sensitive to several non-price market assumptions, particularly PV financing parameters.

  5. A model to estimate insulin sensitivity in dairy cows

    Directory of Open Access Journals (Sweden)

    Holtenius Kjell

    2007-10-01

    Full Text Available Abstract Impairment of the insulin regulation of energy metabolism is considered to be an etiologic key component for metabolic disturbances. Methods for studies of insulin sensitivity thus are highly topical. There are clear indications that reduced insulin sensitivity contributes to the metabolic disturbances that occurs especially among obese lactating cows. Direct measurements of insulin sensitivity are laborious and not suitable for epidemiological studies. We have therefore adopted an indirect method originally developed for humans to estimate insulin sensitivity in dairy cows. The method, "Revised Quantitative Insulin Sensitivity Check Index" (RQUICKI is based on plasma concentrations of glucose, insulin and free fatty acids (FFA and it generates good and linear correlations with different estimates of insulin sensitivity in human populations. We hypothesized that the RQUICKI method could be used as an index of insulin function in lactating dairy cows. We calculated RQUICKI in 237 apparently healthy dairy cows from 20 commercial herds. All cows included were in their first 15 weeks of lactation. RQUICKI was not affected by the homeorhetic adaptations in energy metabolism that occurred during the first 15 weeks of lactation. In a cohort of 24 experimental cows fed in order to obtain different body condition at parturition RQUICKI was lower in early lactation in cows with a high body condition score suggesting disturbed insulin function in obese cows. The results indicate that RQUICKI might be used to identify lactating cows with disturbed insulin function.

  6. Identification of Mission Sensitivities with Mission Modeling from the One System Organization at Hanford - 13292

    Energy Technology Data Exchange (ETDEWEB)

    Belsher, Jeremy D.; Pierson, Kayla L. [Washington River Protection Solutions, LLC, Richland, WA 99352 (United States); Gimpel, Rod F. [One System - Waste Treatment Project, Richland, WA 99352 (United States)

    2013-07-01

    The Hanford site in southeast Washington contains approximately 207 million liters of radioactive and hazardous waste stored in 177 underground tanks. The U.S. Department of Energy's Office of River Protection is currently managing the Hanford waste treatment mission, which includes the storage, retrieval, treatment and disposal of the tank waste. Two recent studies, employing the modeling tools managed by the One System organization, have highlighted waste cleanup mission sensitivities. The Hanford Tank Waste Operations Simulator Sensitivity Study evaluated the impact that varying 21 different parameters had on the Hanford Tank Waste Operations Simulator model. It concluded that inaccuracies in the predicted phase partitioning of a few key components can result in significant changes in the waste treatment duration and in the amount of immobilized high-level waste that is produced. In addition, reducing the efficiency with which tank waste is retrieved and staged can increase mission duration. The 2012 WTP Tank Utilization Assessment concluded that flowsheet models need to include the latest low-activity waste glass algorithms or the waste treatment mission duration and the amount of low activity waste that is produced could be significantly underestimated. (authors)

  7. Sensitive analysis and modifications to reflood-related constitutive models of RELAP5

    International Nuclear Information System (INIS)

    Li Dong; Liu Xiaojing; Yang Yanhua

    2014-01-01

    Previous system code calculation reveals that the cladding temperature is underestimated and quench front appears too early during reflood process. To find out the parameters shows important effect on the results, sensitive analysis is performed on parameters of constitutive physical models. Based on the phenomenological and theoretical analysis, four parameters are selected: wall to vapor film boiling heat transfer coefficient, wall to liquid film boiling heat transfer coefficient, dry wall interfacial friction coefficient and minimum droplet diameter. In order to improve the reflood simulation ability of RELAP5 code, the film boiling heat transfer model and dry wall interfacial friction model which are corresponding models of those influential parameters are studied. Modifications have been made and installed into RELAP5 code. Six tests of FEBA are simulated by RELAP5 to study the predictability of reflood-related physical models. A dispersed flow film boiling heat transfer (DFFB) model is applied when void fraction is above 0.9. And a factor is multiplied to the post-CHF drag coefficient to fit the experiment better. Finally, the six FEBA tests are calculated again so as to assess the modifications. Better results are obtained which prove the advantage of the modified models. (author)

  8. Sensitivity of the model error parameter specification in weak-constraint four-dimensional variational data assimilation

    Science.gov (United States)

    Shaw, Jeremy A.; Daescu, Dacian N.

    2017-08-01

    This article presents the mathematical framework to evaluate the sensitivity of a forecast error aspect to the input parameters of a weak-constraint four-dimensional variational data assimilation system (w4D-Var DAS), extending the established theory from strong-constraint 4D-Var. Emphasis is placed on the derivation of the equations for evaluating the forecast sensitivity to parameters in the DAS representation of the model error statistics, including bias, standard deviation, and correlation structure. A novel adjoint-based procedure for adaptive tuning of the specified model error covariance matrix is introduced. Results from numerical convergence tests establish the validity of the model error sensitivity equations. Preliminary experiments providing a proof-of-concept are performed using the Lorenz multi-scale model to illustrate the theoretical concepts and potential benefits for practical applications.

  9. Sensitivity analysis for the coupling of a subglacial hydrology model with a 3D ice-sheet model.

    Science.gov (United States)

    Bertagna, L.; Perego, M.; Gunzburger, M.; Hoffman, M. J.; Price, S. F.

    2017-12-01

    When studying the movement of ice sheets, one of the most important factors that influence the velocity of the ice is the amount of friction against the bedrock. Usually, this is modeled by a friction coefficient that may depend on the bed geometry and other quantities, such as the temperature and/or water pressure at the ice-bedrock interface. These quantities are often assumed to be known (either by indirect measurements or by means of parameter estimation) and constant in time. Here, we present a 3D computational model for the simulation of the ice dynamics which incorporates a 2D model proposed by Hewitt (2011) for the subglacial water pressure. The hydrology model is fully coupled with the Blatter-Pattyn model for the ice sheet flow, as the subglacial water pressure appears in the expression for the ice friction coefficient, and the ice velocity appears as a source term in the hydrology model. We will present results on real geometries, and perform a sensitivity analysis with respect to the hydrology model parameters.

  10. Increase of carbon cycle feedback with climate sensitivity: results from a coupled climate and carbon cycle model

    International Nuclear Information System (INIS)

    Govindasamy, B.; Thompson, S.; Mirin, A.; Wickett, M.; Caldeira, K.; Delire, C.

    2005-01-01

    Coupled climate and carbon cycle modelling studies have shown that the feedback between global warming and the carbon cycle, in particular the terrestrial carbon cycle, could accelerate climate change and result in greater warming. In this paper we investigate the sensitivity of this feedback for year 2100 global warming in the range of 0 to 8 K. Differing climate sensitivities to increased CO 2 content are imposed on the carbon cycle models for the same emissions. Emissions from the SRES A2 scenario are used. We use a fully coupled climate and carbon cycle model, the INtegrated Climate and CArbon model (INCCA), the NCAR/DOE Parallel Climate Model coupled to the IBIS terrestrial biosphere model and a modified OCMIP ocean biogeochemistry model. In our integrated model, for scenarios with year 2100 global warming increasing from 0 to 8 K, land uptake decreases from 47% to 29% of total CO 2 emissions. Due to competing effects, ocean uptake (16%) shows almost no change at all. Atmospheric CO 2 concentration increases are 48% higher in the run with 8 K global climate warming than in the case with no warming. Our results indicate that carbon cycle amplification of climate warming will be greater if there is higher climate sensitivity to increased atmospheric CO 2 content; the carbon cycle feedback factor increases from 1.13 to 1.48 when global warming increases from 3.2 to 8 K

  11. Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study

    International Nuclear Information System (INIS)

    Zhai, Qingqing; Yang, Jun; Zhao, Yu

    2014-01-01

    Variance-based sensitivity analysis has been widely studied and asserted itself among practitioners. Monte Carlo simulation methods are well developed in the calculation of variance-based sensitivity indices but they do not make full use of each model run. Recently, several works mentioned a scatter-plot partitioning method to estimate the variance-based sensitivity indices from given data, where a single bunch of samples is sufficient to estimate all the sensitivity indices. This paper focuses on the space-partition method in the estimation of variance-based sensitivity indices, and its convergence and other performances are investigated. Since the method heavily depends on the partition scheme, the influence of the partition scheme is discussed and the optimal partition scheme is proposed based on the minimized estimator's variance. A decomposition and integration procedure is proposed to improve the estimation quality for higher order sensitivity indices. The proposed space-partition method is compared with the more traditional method and test cases show that it outperforms the traditional one

  12. Contributions to sensitivity analysis and generalized discriminant analysis

    International Nuclear Information System (INIS)

    Jacques, J.

    2005-12-01

    Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)

  13. Sensitivity analysis and power for instrumental variable studies.

    Science.gov (United States)

    Wang, Xuran; Jiang, Yang; Zhang, Nancy R; Small, Dylan S

    2018-03-31

    In observational studies to estimate treatment effects, unmeasured confounding is often a concern. The instrumental variable (IV) method can control for unmeasured confounding when there is a valid IV. To be a valid IV, a variable needs to be independent of unmeasured confounders and only affect the outcome through affecting the treatment. When applying the IV method, there is often concern that a putative IV is invalid to some degree. We present an approach to sensitivity analysis for the IV method which examines the sensitivity of inferences to violations of IV validity. Specifically, we consider sensitivity when the magnitude of association between the putative IV and the unmeasured confounders and the direct effect of the IV on the outcome are limited in magnitude by a sensitivity parameter. Our approach is based on extending the Anderson-Rubin test and is valid regardless of the strength of the instrument. A power formula for this sensitivity analysis is presented. We illustrate its usage via examples about Mendelian randomization studies and its implications via a comparison of using rare versus common genetic variants as instruments. © 2018, The International Biometric Society.

  14. Emulation and Sobol' sensitivity analysis of an atmospheric dispersion model applied to the Fukushima nuclear accident

    Science.gov (United States)

    Girard, Sylvain; Mallet, Vivien; Korsakissok, Irène; Mathieu, Anne

    2016-04-01

    Simulations of the atmospheric dispersion of radionuclides involve large uncertainties originating from the limited knowledge of meteorological input data, composition, amount and timing of emissions, and some model parameters. The estimation of these uncertainties is an essential complement to modeling for decision making in case of an accidental release. We have studied the relative influence of a set of uncertain inputs on several outputs from the Eulerian model Polyphemus/Polair3D on the Fukushima case. We chose to use the variance-based sensitivity analysis method of Sobol'. This method requires a large number of model evaluations which was not achievable directly due to the high computational cost of Polyphemus/Polair3D. To circumvent this issue, we built a mathematical approximation of the model using Gaussian process emulation. We observed that aggregated outputs are mainly driven by the amount of emitted radionuclides, while local outputs are mostly sensitive to wind perturbations. The release height is notably influential, but only in the vicinity of the source. Finally, averaging either spatially or temporally tends to cancel out interactions between uncertain inputs.

  15. Sensitivity of physics parameters for establishment of a burned CANDU full-core model for decommissioning waste characterization

    International Nuclear Information System (INIS)

    Cho, Dong-Keun; Sun, Gwang-Min; Choi, Jongwon; Hwang, Dong-Hyun; Hwang, Tae-Won; Yang, Ho-Yeon; Park, Dong-Hwan

    2011-01-01

    The sensitivity of parameters related with reactor physics on the source terms of decommissioning wastes from a CANDU reactor was investigated in order to find a viable, simplified burned core model of a Monte Carlo simulation for decommissioning waste characterization. First, a sensitivity study was performed for the level of nuclide consideration in an irradiated fuel and implicit geometry modeling, the effects of side structural components of the core, and structural supporters for reactive devices. The overall effects for computation memory, calculation time, and accuracy were then investigated with a full-core model. From the results, it was revealed that the level of nuclide consideration and geometry homogenization are not important factors when the ratio of macroscopic neutron absorption cross section (MNAC) relative to a total value exceeded 0.95. The most important factor affecting the neutron flux of the pressure tube was shown to be the structural supporters for reactivity devices, showing an 10% difference. Finally, it was concluded that a bundle-average homogeneous model considering a MNAC of 0.95, which is the simplest model in this study, could be a viable approximate model, with about 25% lower computation memory, 40% faster simulation time, and reasonable engineering accuracy compared with a model with an explicit geometry employing an MNAC of 0.99. (author)

  16. Sensitivity analysis on a dose-calculation model for the terrestrial food-chain pathway

    International Nuclear Information System (INIS)

    Abdel-Aal, M.M.

    1994-01-01

    Parameter uncertainty and sensitivity were applied to the U.S. Regulatory Commission's (NRC) Regulatory Guide 1.109 (1977) models for calculating the ingestion dose via a terrestrial food-chain pathway in order to assess the transport of chronically released, low-level effluents from light-water reactors. In the analysis, we used the generation of latin hypercube samples (LHS) and employed a constrained sampling scheme. The generation of these samples is based on information supplied to the LHS program for variables or parameters. The actually sampled values are used to form vectors of variables that are commonly used as inputs to computer models for the purpose of sensitivity and uncertainty analysis. Regulatory models consider the concentrations of radionuclides that are deposited on plant tissues or lead to root uptake of nuclides initially deposited on soil. We also consider concentrations in milk and beef as a consequence of grazing on contaminated pasture or ingestion of contaminated feed by dairy and beef cattle. The radionuclides Sr-90 and Cs-137 were selected for evaluation. The most sensitive input parameters for the model were the ground-dispersion parameter, release rates of radionuclides, and soil-to-plant transfer coefficients of radionuclides. (Author)

  17. Cyanidin-Based Novel Organic Sensitizer for Efficient Dye-Sensitized Solar Cells: DFT/TDDFT Study

    Directory of Open Access Journals (Sweden)

    Kalpana Galappaththi

    2017-01-01

    Full Text Available Cyanidin is widely considered as a potential natural sensitizer in dye-sensitized solar cells due to its promising electron-donating and electron-accepting abilities and cheap availability. We consider modifications of cyanidin structure in order to obtain broader UV-Vis absorption and hence to achieve better performance in DSSC. The modified molecule consists of cyanidin and the benzothiadiazolylbenzoic acid group, where the benzothiadiazolylbenzoic acid group is attached to the cyanidin molecule by replacing one hydroxyl group. The resulting structure was then computationally simulated by using the Spartan’10 software package. The molecular geometries, electronic structures, absorption spectra, and electron injections of the newly designed organic sensitizer were investigated in this work through density functional theory (DFT and time-dependent density functional theory (TDDFT calculations using the Gaussian’09W software package. Furthermore, TDDFT computational calculations were performed on cyanadin and benzothiadiazolylbenzoic acid separately, as reference. The computational studies on the new sensitizer have shown a reduced HOMO-LUMO gap; bathochromic and hyperchromic shifts of absorption spectra range up to near-infrared region revealing its enhanced ability to sensitize DSSCs.

  18. Isoprene emissions modelling for West Africa: MEGAN model evaluation and sensitivity analysis

    Directory of Open Access Journals (Sweden)

    J. Ferreira

    2010-09-01

    Full Text Available Isoprene emissions are the largest source of reactive carbon to the atmosphere, with the tropics being a major source region. These natural emissions are expected to change with changing climate and human impact on land use. As part of the African Monsoon Multidisciplinary Analyses (AMMA project the Model of Emissions of Gases and Aerosols from Nature (MEGAN has been used to estimate the spatial and temporal distribution of isoprene emissions over the West African region. During the AMMA field campaign, carried out in July and August 2006, isoprene mixing ratios were measured on board the FAAM BAe-146 aircraft. These data have been used to make a qualitative evaluation of the model performance.

    MEGAN was firstly applied to a large area covering much of West Africa from the Gulf of Guinea in the south to the desert in the north and was able to capture the large scale spatial distribution of isoprene emissions as inferred from the observed isoprene mixing ratios. In particular the model captures the transition from the forested area in the south to the bare soils in the north, but some discrepancies have been identified over the bare soil, mainly due to the emission factors used. Sensitivity analyses were performed to assess the model response to changes in driving parameters, namely Leaf Area Index (LAI, Emission Factors (EF, temperature and solar radiation.

    A high resolution simulation was made of a limited area south of Niamey, Niger, where the higher concentrations of isoprene were observed. This is used to evaluate the model's ability to simulate smaller scale spatial features and to examine the influence of the driving parameters on an hourly basis through a case study of a flight on 17 August 2006.

    This study highlights the complex interactions between land surface processes and the meteorological dynamics and chemical composition of the PBL. This has implications for quantifying the impact of biogenic emissions

  19. On the sensitivity of mesoscale models to surface-layer parameterization constants

    Science.gov (United States)

    Garratt, J. R.; Pielke, R. A.

    1989-09-01

    The Colorado State University standard mesoscale model is used to evaluate the sensitivity of one-dimensional (1D) and two-dimensional (2D) fields to differences in surface-layer parameterization “constants”. Such differences reflect the range in the published values of the von Karman constant, Monin-Obukhov stability functions and the temperature roughness length at the surface. The sensitivity of 1D boundary-layer structure, and 2D sea-breeze intensity, is generally less than that found in published comparisons related to turbulence closure schemes generally.

  20. Simulating smoke transport from wildland fires with a regional-scale air quality model: sensitivity to spatiotemporal allocation of fire emissions.

    Science.gov (United States)

    Garcia-Menendez, Fernando; Hu, Yongtao; Odman, Mehmet T

    2014-09-15

    Air quality forecasts generated with chemical transport models can provide valuable information about the potential impacts of fires on pollutant levels. However, significant uncertainties are associated with fire-related emission estimates as well as their distribution on gridded modeling domains. In this study, we explore the sensitivity of fine particulate matter concentrations predicted by a regional-scale air quality model to the spatial and temporal allocation of fire emissions. The assessment was completed by simulating a fire-related smoke episode in which air quality throughout the Atlanta metropolitan area was affected on February 28, 2007. Sensitivity analyses were carried out to evaluate the significance of emission distribution among the model's vertical layers, along the horizontal plane, and into hourly inputs. Predicted PM2.5 concentrations were highly sensitive to emission injection altitude relative to planetary boundary layer height. Simulations were also responsive to the horizontal allocation of fire emissions and their distribution into single or multiple grid cells. Additionally, modeled concentrations were greatly sensitive to the temporal distribution of fire-related emissions. The analyses demonstrate that, in addition to adequate estimates of emitted mass, successfully modeling the impacts of fires on air quality depends on an accurate spatiotemporal allocation of emissions. Copyright © 2014 Elsevier B.V. All rights reserved.

  1. HCIT Contrast Performance Sensitivity Studies: Simulation Versus Experiment

    Science.gov (United States)

    Sidick, Erkin; Shaklan, Stuart; Krist, John; Cady, Eric J.; Kern, Brian; Balasubramanian, Kunjithapatham

    2013-01-01

    Using NASA's High Contrast Imaging Testbed (HCIT) at the Jet Propulsion Laboratory, we have experimentally investigated the sensitivity of dark hole contrast in a Lyot coronagraph for the following factors: 1) Lateral and longitudinal translation of an occulting mask; 2) An opaque spot on the occulting mask; 3) Sizes of the controlled dark hole area. Also, we compared the measured results with simulations obtained using both MACOS (Modeling and Analysis for Controlled Optical Systems) and PROPER optical analysis programs with full three-dimensional near-field diffraction analysis to model HCIT's optical train and coronagraph.

  2. Comprehensive mechanisms for combustion chemistry: Experiment, modeling, and sensitivity analysis

    Energy Technology Data Exchange (ETDEWEB)

    Dryer, F.L.; Yetter, R.A. [Princeton Univ., NJ (United States)

    1993-12-01

    This research program is an integrated experimental/numerical effort to study pyrolysis and oxidation reactions and mechanisms for small-molecule hydrocarbon structures under conditions representative of combustion environments. The experimental aspects of the work are conducted in large diameter flow reactors, at pressures from one to twenty atmospheres, temperatures from 550 K to 1200 K, and with observed reaction times from 10{sup {minus}2} to 5 seconds. Gas sampling of stable reactant, intermediate, and product species concentrations provides not only substantial definition of the phenomenology of reaction mechanisms, but a significantly constrained set of kinetic information with negligible diffusive coupling. Analytical techniques used for detecting hydrocarbons and carbon oxides include gas chromatography (GC), and gas infrared (NDIR) and FTIR methods are utilized for continuous on-line sample detection of light absorption measurements of OH have also been performed in an atmospheric pressure flow reactor (APFR), and a variable pressure flow (VPFR) reactor is presently being instrumented to perform optical measurements of radicals and highly reactive molecular intermediates. The numerical aspects of the work utilize zero and one-dimensional pre-mixed, detailed kinetic studies, including path, elemental gradient sensitivity, and feature sensitivity analyses. The program emphasizes the use of hierarchical mechanistic construction to understand and develop detailed kinetic mechanisms. Numerical studies are utilized for guiding experimental parameter selections, for interpreting observations, for extending the predictive range of mechanism constructs, and to study the effects of diffusive transport coupling on reaction behavior in flames. Modeling using well defined and validated mechanisms for the CO/H{sub 2}/oxidant systems.

  3. Sensitivity analysis of alkaline plume modelling: influence of mineralogy

    International Nuclear Information System (INIS)

    Gaboreau, S.; Claret, F.; Marty, N.; Burnol, A.; Tournassat, C.; Gaucher, E.C.; Munier, I.; Michau, N.; Cochepin, B.

    2010-01-01

    Document available in extended abstract form only. In the context of a disposal facility for radioactive waste in clayey geological formation, an important modelling effort has been carried out in order to predict the time evolution of interacting cement based (concrete or cement) and clay (argillites and bentonite) materials. The high number of modelling input parameters associated with non negligible uncertainties makes often difficult the interpretation of modelling results. As a consequence, it is necessary to carry out sensitivity analysis on main modelling parameters. In a recent study, Marty et al. (2009) could demonstrate that numerical mesh refinement and consideration of dissolution/precipitation kinetics have a marked effect on (i) the time necessary to numerically clog the initial porosity and (ii) on the final mineral assemblage at the interface. On the contrary, these input parameters have little effect on the extension of the alkaline pH plume. In the present study, we propose to investigate the effects of the considered initial mineralogy on the principal simulation outputs: (1) the extension of the high pH plume, (2) the time to clog the porosity and (3) the alteration front in the clay barrier (extension and nature of mineralogy changes). This was done through sensitivity analysis on both concrete composition and clay mineralogical assemblies since in most published studies, authors considered either only one composition per materials or simplified mineralogy in order to facilitate or to reduce their calculation times. 1D Cartesian reactive transport models were run in order to point out the importance of (1) the crystallinity of concrete phases, (2) the type of clayey materials and (3) the choice of secondary phases that are allowed to precipitate during calculations. Two concrete materials with either nanocrystalline or crystalline phases were simulated in contact with two clayey materials (smectite MX80 or Callovo- Oxfordian argillites). Both

  4. Sensitivity studies on the approaches for addressing multiple initiating events in fire events PSA

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Dae Il; Lim, Ho Gon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    A single fire event within a fire compartment or a fire scenario can cause multiple initiating events (IEs). As an example, a fire in a turbine building fire area can cause a loss of the main feed-water (LOMF) and loss of off-site power (LOOP) IEs. Previous domestic fire events PSA had considered only the most severe initiating event among multiple initiating events. NUREG/CR-6850 and ANS/ASME PRA Standard require that multiple IEs are to be addressed in fire events PSA. In this paper, sensitivity studies on the approaches for addressing multiple IEs in fire events PSA for Hanul Unit 3 were performed and their results were presented. In this paper, sensitivity studies on the approaches for addressing multiple IEs in fire events PSA are performed and their results were presented. From the sensitivity analysis results, we can find that the incorporations of multiple IEs into fire events PSA model result in the core damage frequency (CDF) increase and may lead to the generation of the duplicate cutsets. Multiple IEs also can occur at internal flooding event or other external events such as seismic event. They should be considered in the constructions of PSA models in order to realistically estimate risk due to flooding or seismic events.

  5. On sensitivity value of pair-matched observational studies

    OpenAIRE

    Zhao, Qingyuan

    2017-01-01

    An observational study may be biased for estimating causal effects by failing to control for unmeasured confounders. This paper proposes a new quantity called the "sensitivity value", which is defined as the minimum strength of unmeasured confounders needed to change the qualitative conclusions of a naive analysis assuming no unmeasured confounder. We establish the asymptotic normality of the sensitivity value in pair-matched observational studies. The theoretical results are then used to app...

  6. Reward and Punishment Sensitivity in Children with ADHD: Validating the Sensitivity to Punishment and Sensitivity to Reward Questionnaire for Children (SPSRQ-C)

    OpenAIRE

    Luman, Marjolein; van Meel, Catharina S.; Oosterlaan, Jaap; Geurts, Hilde M.

    2011-01-01

    This study validates the Sensitivity to Punishment and Sensitivity to Reward Questionnaire for children (SPSRQ-C), using a Dutch sample of 1234 children between 6-13 years old. Factor analysis determined that a 4-factor and a 5-factor solution were best fitting, explaining 41% and 50% of the variance respectively. The 4-factor model was highly similar to the original SPSRQ factors found in adults (Punishment Sensitivity, Reward Responsivity, Impulsivity/ Fun-Seeking, and Drive). The 5-factor ...

  7. Sensitivity of a subject-specific musculoskeletal model to the uncertainties on the joint axes location.

    Science.gov (United States)

    Martelli, Saulo; Valente, Giordano; Viceconti, Marco; Taddei, Fulvia

    2015-01-01

    Subject-specific musculoskeletal models have become key tools in the clinical decision-making process. However, the sensitivity of the calculated solution to the unavoidable errors committed while deriving the model parameters from the available information is not fully understood. The aim of this study was to calculate the sensitivity of all the kinematics and kinetics variables to the inter-examiner uncertainty in the identification of the lower limb joint models. The study was based on the computer tomography of the entire lower-limb from a single donor and the motion capture from a body-matched volunteer. The hip, the knee and the ankle joint models were defined following the International Society of Biomechanics recommendations. Using a software interface, five expert anatomists identified on the donor's images the necessary bony locations five times with a three-day time interval. A detailed subject-specific musculoskeletal model was taken from an earlier study, and re-formulated to define the joint axes by inputting the necessary bony locations. Gait simulations were run using OpenSim within a Monte Carlo stochastic scheme, where the locations of the bony landmarks were varied randomly according to the estimated distributions. Trends for the joint angles, moments, and the muscle and joint forces did not substantially change after parameter perturbations. The highest variations were as follows: (a) 11° calculated for the hip rotation angle, (b) 1% BW × H calculated for the knee moment and (c) 0.33 BW calculated for the ankle plantarflexor muscles and the ankle joint forces. In conclusion, the identification of the joint axes from clinical images is a robust procedure for human movement modelling and simulation.

  8. Constraining Transient Climate Sensitivity Using Coupled Climate Model Simulations of Volcanic Eruptions

    KAUST Repository

    Merlis, Timothy M.; Held, Isaac M.; Stenchikov, Georgiy L.; Zeng, Fanrong; Horowitz, Larry W.

    2014-01-01

    Coupled climate model simulations of volcanic eruptions and abrupt changes in CO2 concentration are compared in multiple realizations of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1). The change in global-mean surface temperature (GMST) is analyzed to determine whether a fast component of the climate sensitivity of relevance to the transient climate response (TCR; defined with the 1%yr-1 CO2-increase scenario) can be estimated from shorter-time-scale climate changes. The fast component of the climate sensitivity estimated from the response of the climate model to volcanic forcing is similar to that of the simulations forced by abrupt CO2 changes but is 5%-15% smaller than the TCR. In addition, the partition between the top-of-atmosphere radiative restoring and ocean heat uptake is similar across radiative forcing agents. The possible asymmetry between warming and cooling climate perturbations, which may affect the utility of volcanic eruptions for estimating the TCR, is assessed by comparing simulations of abrupt CO2 doubling to abrupt CO2 halving. There is slightly less (~5%) GMST change in 0.5 × CO2 simulations than in 2 × CO2 simulations on the short (~10 yr) time scales relevant to the fast component of the volcanic signal. However, inferring the TCR from volcanic eruptions is more sensitive to uncertainties from internal climate variability and the estimation procedure. The response of the GMST to volcanic eruptions is similar in GFDL CM2.1 and GFDL Climate Model, version 3 (CM3), even though the latter has a higher TCR associated with a multidecadal time scale in its response. This is consistent with the expectation that the fast component of the climate sensitivity inferred from volcanic eruptions is a lower bound for the TCR.

  9. Constraining Transient Climate Sensitivity Using Coupled Climate Model Simulations of Volcanic Eruptions

    KAUST Repository

    Merlis, Timothy M.

    2014-10-01

    Coupled climate model simulations of volcanic eruptions and abrupt changes in CO2 concentration are compared in multiple realizations of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1). The change in global-mean surface temperature (GMST) is analyzed to determine whether a fast component of the climate sensitivity of relevance to the transient climate response (TCR; defined with the 1%yr-1 CO2-increase scenario) can be estimated from shorter-time-scale climate changes. The fast component of the climate sensitivity estimated from the response of the climate model to volcanic forcing is similar to that of the simulations forced by abrupt CO2 changes but is 5%-15% smaller than the TCR. In addition, the partition between the top-of-atmosphere radiative restoring and ocean heat uptake is similar across radiative forcing agents. The possible asymmetry between warming and cooling climate perturbations, which may affect the utility of volcanic eruptions for estimating the TCR, is assessed by comparing simulations of abrupt CO2 doubling to abrupt CO2 halving. There is slightly less (~5%) GMST change in 0.5 × CO2 simulations than in 2 × CO2 simulations on the short (~10 yr) time scales relevant to the fast component of the volcanic signal. However, inferring the TCR from volcanic eruptions is more sensitive to uncertainties from internal climate variability and the estimation procedure. The response of the GMST to volcanic eruptions is similar in GFDL CM2.1 and GFDL Climate Model, version 3 (CM3), even though the latter has a higher TCR associated with a multidecadal time scale in its response. This is consistent with the expectation that the fast component of the climate sensitivity inferred from volcanic eruptions is a lower bound for the TCR.

  10. Sensitivity analysis for thermo-hydraulics model of a Westinghouse type PWR. Verification of the simulation results

    Energy Technology Data Exchange (ETDEWEB)

    Farahani, Aref Zarnooshe [Islamic Azad Univ., Tehran (Iran, Islamic Republic of). Dept. of Nuclear Engineering, Science and Research Branch; Yousefpour, Faramarz [Nuclear Science and Technology Research Institute, Tehran (Iran, Islamic Republic of); Hoseyni, Seyed Mohsen [Islamic Azad Univ., Tehran (Iran, Islamic Republic of). Dept. of Basic Sciences; Islamic Azad Univ., Tehran (Iran, Islamic Republic of). Young Researchers and Elite Club

    2017-07-15

    Development of a steady-state model is the first step in nuclear safety analysis. The developed model should be qualitatively analyzed first, then a sensitivity analysis is required on the number of nodes for models of different systems to ensure the reliability of the obtained results. This contribution aims to show through sensitivity analysis, the independence of modeling results to the number of nodes in a qualified MELCOR model for a Westinghouse type pressurized power plant. For this purpose, and to minimize user error, the nuclear analysis software, SNAP, is employed. Different sensitivity cases were developed by modification of the existing model and refinement of the nodes for the simulated systems including steam generators, reactor coolant system and also reactor core and its connecting flow paths. By comparing the obtained results to those of the original model no significant difference is observed which is indicative of the model independence to the finer nodes.

  11. Demonstration uncertainty/sensitivity analysis using the health and economic consequence model CRAC2

    International Nuclear Information System (INIS)

    Alpert, D.J.; Iman, R.L.; Johnson, J.D.; Helton, J.C.

    1984-12-01

    The techniques for performing uncertainty/sensitivity analyses compiled as part of the MELCOR program appear to be well suited for use with a health and economic consequence model. Two replicate samples of size 50 gave essentially identical results, indicating that for this case, a Latin hypercube sample of size 50 seems adequate to represent the distribution of results. Though the intent of this study was a demonstration of uncertainty/sensitivity analysis techniques, a number of insights relevant to health and economic consequence modeling can be gleaned: uncertainties in early deaths are significantly greater than uncertainties in latent cancer deaths; though the magnitude of the source term is the largest source of variation in estimated distributions of early deaths, a number of additional parameters are also important; even with the release fractions for a full SST1, one quarter of the CRAC2 runs gave no early deaths; and comparison of the estimates of mean early deaths for a full SST1 release in this study with those of recent point estimates for similar conditions indicates that the recent estimates may be significant overestimations of early deaths. Estimates of latent cancer deaths, however, are roughly comparable. An analysis of the type described here can provide insights in a number of areas. First, the variability in the results gives an indication of the potential uncertainty associated with the calculations. Second, the sensitivity of the results to assumptions about the input variables can be determined. Research efforts can then be concentrated on reducing the uncertainty in the variables which are the largest contributors to uncertainty in results

  12. Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, T. (Yale Univ., New Haven, CT (United States))

    1994-06-01

    A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover, soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations. 46 refs., 10 figs., 6 tabs.

  13. Two-Dimensional Modeling of Heat and Moisture Dynamics in Swedish Roads: Model Set up and Parameter Sensitivity

    Science.gov (United States)

    Rasul, H.; Wu, M.; Olofsson, B.

    2017-12-01

    Modelling moisture and heat changes in road layers is very important to understand road hydrology and for better construction and maintenance of roads in a sustainable manner. In cold regions due to the freezing/thawing process in the partially saturated material of roads, the modeling task will become more complicated than simple model of flow through porous media without freezing/thawing pores considerations. This study is presenting a 2-D model simulation for a section of highway with considering freezing/thawing and vapor changes. Partial deferential equations (PDEs) are used in formulation of the model. Parameters are optimized from modelling results based on the measured data from test station on E18 highway near Stockholm. Impacts of phase change considerations in the modelling are assessed by comparing the modeled soil moisture with TDR-measured data. The results show that the model can be used for prediction of water and ice content in different layers of the road and at different seasons. Parameter sensitivities are analyzed by implementing a calibration strategy. In addition, the phase change consideration is evaluated in the modeling process, by comparing the PDE model with another model without considerations of freezing/thawing in roads. The PDE model shows high potential in understanding the moisture dynamics in the road system.

  14. Bayesian Sensitivity Analysis of a Cardiac Cell Model Using a Gaussian Process Emulator

    Science.gov (United States)

    Chang, Eugene T Y; Strong, Mark; Clayton, Richard H

    2015-01-01

    Models of electrical activity in cardiac cells have become important research tools as they can provide a quantitative description of detailed and integrative physiology. However, cardiac cell models have many parameters, and how uncertainties in these parameters affect the model output is difficult to assess without undertaking large numbers of model runs. In this study we show that a surrogate statistical model of a cardiac cell model (the Luo-Rudy 1991 model) can be built using Gaussian process (GP) emulators. Using this approach we examined how eight outputs describing the action potential shape and action potential duration restitution depend on six inputs, which we selected to be the maximum conductances in the Luo-Rudy 1991 model. We found that the GP emulators could be fitted to a small number of model runs, and behaved as would be expected based on the underlying physiology that the model represents. We have shown that an emulator approach is a powerful tool for uncertainty and sensitivity analysis in cardiac cell models. PMID:26114610

  15. Use of FFTBM by signal mirroring for sensitivity study

    International Nuclear Information System (INIS)

    Prošek, Andrej; Leskovar, Matjaž

    2015-01-01

    Highlights: • The fast Fourier transform based tool was applied for a sensitivity analysis. • The calculations of the BEMUSE programme LOFT L2-5 test were used in the study. • The most influential input parameters were identified and their influence quantified. • It was shown that FFTBM-SM is best suited for conducting quick sensitivity analyses. - Abstract: The state of the art best estimate safety analyses for nuclear reactors use best estimate thermal–hydraulic computer codes with an evaluation of the uncertainties to compare the results of calculations with acceptance criteria. The uncertainty quantification is typically accompanied by a sensitivity analysis, in which the influence of the individual contributors to the uncertainty is determined. The objective of the performed study is to demonstrate that the fast Fourier transform based method by signal mirroring (FFTBM-SM) can be very efficiently used for the sensitivity analysis when one parameter is varied at a time. The sensitivity study was conducted for the LOFT L2-5 test, which simulates the large break loss of coolant accident. The LOFT L2-5 test was analysed in the frame of the Organisation for Economic Co-operation and Development (OECD) Best Estimate Methods – Uncertainty and Sensitivity Evaluation (BEMUSE) programme, where each of the 14 participants performed a reference calculation and up to 15 sensitivity runs of the test. The results show that with the FFTBM-SM the analyst can get the time dependent picture of the input parameter influence on the results. The results suggest that FFTBM-SM is especially appropriate for a sensitivity analysis in which several calculations need to be compared

  16. Sensitivity analysis of the noise-induced oscillatory multistability in Higgins model of glycolysis

    Science.gov (United States)

    Ryashko, Lev

    2018-03-01

    A phenomenon of the noise-induced oscillatory multistability in glycolysis is studied. As a basic deterministic skeleton, we consider the two-dimensional Higgins model. The noise-induced generation of mixed-mode stochastic oscillations is studied in various parametric zones. Probabilistic mechanisms of the stochastic excitability of equilibria and noise-induced splitting of randomly forced cycles are analysed by the stochastic sensitivity function technique. A parametric zone of supersensitive Canard-type cycles is localized and studied in detail. It is shown that the generation of mixed-mode stochastic oscillations is accompanied by the noise-induced transitions from order to chaos.

  17. Sleep fragmentation exacerbates mechanical hypersensitivity and alters subsequent sleep-wake behavior in a mouse model of musculoskeletal sensitization.

    Science.gov (United States)

    Sutton, Blair C; Opp, Mark R

    2014-03-01

    Sleep deprivation, or sleep disruption, enhances pain in human subjects. Chronic musculoskeletal pain is prevalent in our society, and constitutes a tremendous public health burden. Although preclinical models of neuropathic and inflammatory pain demonstrate effects on sleep, few studies focus on musculoskeletal pain. We reported elsewhere in this issue of SLEEP that musculoskeletal sensitization alters sleep of mice. In this study we hypothesize that sleep fragmentation during the development of musculoskeletal sensitization will exacerbate subsequent pain responses and alter sleep-wake behavior of mice. This is a preclinical study using C57BL/6J mice to determine the effect on behavioral outcomes of sleep fragmentation combined with musculoskeletal sensitization. Musculoskeletal sensitization, a model of chronic muscle pain, was induced using two unilateral injections of acidified saline (pH 4.0) into the gastrocnemius muscle, spaced 5 days apart. Musculoskeletal sensitization manifests as mechanical hypersensitivity determined by von Frey filament testing at the hindpaws. Sleep fragmentation took place during the consecutive 12-h light periods of the 5 days between intramuscular injections. Electroencephalogram (EEG) and body temperature were recorded from some mice at baseline and for 3 weeks after musculoskeletal sensitization. Mechanical hypersensitivity was determined at preinjection baseline and on days 1, 3, 7, 14, and 21 after sensitization. Two additional experiments were conducted to determine the independent effects of sleep fragmentation or musculoskeletal sensitization on mechanical hypersensitivity. Five days of sleep fragmentation alone did not induce mechanical hypersensitivity, whereas sleep fragmentation combined with musculoskeletal sensitization resulted in prolonged and exacerbated mechanical hypersensitivity. Sleep fragmentation combined with musculoskeletal sensitization had an effect on subsequent sleep of mice as demonstrated by increased

  18. Finnish Secondary School Students' Interreligious Sensitivity

    Science.gov (United States)

    Holm, Kristiina; Nokelainen, Petri; Tirri, Kirsi

    2014-01-01

    The aim of this study was to assess the self-evaluations of Finnish secondary school students' (N?=?549) interreligious sensitivity. The data were collected from 12-16-year-old young people with a 15-item Interreligious Sensitivity Scale Questionnaire (IRRSSQ). The IRRSSQ is based on Abu-Nimer's Developmental Model of Interreligious Sensitivity,…

  19. Anxiety sensitivity and suicide risk among firefighters: A test of the depression-distress amplification model.

    Science.gov (United States)

    Stanley, Ian H; Smith, Lia J; Boffa, Joseph W; Tran, Jana K; Schmidt, N Brad; Joiner, Thomas E; Vujanovic, Anka A

    2018-04-07

    Firefighters represent an occupational group at increased suicide risk. How suicidality develops among firefighters is poorly understood. The depression-distress amplification model posits that the effects of depression symptoms on suicide risk will be intensified in the context of anxiety sensitivity (AS) cognitive concerns. The current study tested this model among firefighters. Overall, 831 firefighters participated (mean [SD] age = 38.37 y [8.53 y]; 94.5% male; 75.2% White). The Center for Epidemiologic Studies Depression Scale (CES-D), Anxiety Sensitivity Index-3 (ASI-3), and Suicidal Behaviors Questionnaire-Revised (SBQ-R) were utilized to assess for depression symptoms, AS concerns (cognitive, physical, social), and suicide risk, respectively. Linear regression interaction models were tested. The effects of elevated depression symptoms on increased suicide risk were augmented when AS cognitive concerns were also elevated. Unexpectedly, depression symptoms also interacted with AS social concerns; however, consistent with expectations, depression symptoms did not interact with AS physical concerns in the prediction of suicide risk. In the context of elevated depression symptoms, suicide risk is potentiated among firefighters reporting elevated AS cognitive and AS social concerns. Findings support and extend the depression-distress amplification model of suicide risk within a sample of firefighters. Interventions that successfully impact AS concerns may, in turn, mitigate suicide risk among this at-risk population. Copyright © 2018 Elsevier Inc. All rights reserved.

  20. Modeling and sensitivity analysis on the transport of aluminum oxide nanoparticles in saturated sand: effects of ionic strength, flow rate, and nanoparticle concentration.

    Science.gov (United States)

    Rahman, Tanzina; Millwater, Harry; Shipley, Heather J

    2014-11-15

    Aluminum oxide nanoparticles have been widely used in various consumer products and there are growing concerns regarding their exposure in the environment. This study deals with the modeling, sensitivity analysis and uncertainty quantification of one-dimensional transport of nano-sized (~82 nm) aluminum oxide particles in saturated sand. The transport of aluminum oxide nanoparticles was modeled using a two-kinetic-site model with a blocking function. The modeling was done at different ionic strengths, flow rates, and nanoparticle concentrations. The two sites representing fast and slow attachments along with a blocking term yielded good agreement with the experimental results from the column studies of aluminum oxide nanoparticles. The same model was used to simulate breakthrough curves under different conditions using experimental data and calculated 95% confidence bounds of the generated breakthroughs. The sensitivity analysis results showed that slow attachment was the most sensitive parameter for high influent concentrations (e.g. 150 mg/L Al2O3) and the maximum solid phase retention capacity (related to blocking function) was the most sensitive parameter for low concentrations (e.g. 50 mg/L Al2O3). Copyright © 2014 Elsevier B.V. All rights reserved.

  1. An Investigation on the Sensitivity of the Parameters of Urban Flood Model

    Science.gov (United States)

    M, A. B.; Lohani, B.; Jain, A.

    2015-12-01

    Global climatic change has triggered weather patterns which lead to heavy and sudden rainfall in different parts of world. The impact of heavy rainfall is severe especially on urban areas in the form of urban flooding. In order to understand the effect of heavy rainfall induced flooding, it is necessary to model the entire flooding scenario more accurately, which is now becoming possible with the availability of high resolution airborne LiDAR data and other real time observations. However, there is not much understanding on the optimal use of these data and on the effect of other parameters on the performance of the flood model. This study aims at developing understanding on these issues. In view of the above discussion, the aim of this study is to (i) understand that how the use of high resolution LiDAR data improves the performance of urban flood model, and (ii) understand the sensitivity of various hydrological parameters on urban flood modelling. In this study, modelling of flooding in urban areas due to heavy rainfall is carried out considering Indian Institute of Technology (IIT) Kanpur, India as the study site. The existing model MIKE FLOOD, which is accepted by Federal Emergency Management Agency (FEMA), is used along with the high resolution airborne LiDAR data. Once the model is setup it is made to run by changing the parameters such as resolution of Digital Surface Model (DSM), manning's roughness, initial losses, catchment description, concentration time, runoff reduction factor. In order to realize this, the results obtained from the model are compared with the field observations. The parametric study carried out in this work demonstrates that the selection of catchment description plays a very important role in urban flood modelling. Results also show the significant impact of resolution of DSM, initial losses and concentration time on urban flood model. This study will help in understanding the effect of various parameters that should be part of a

  2. Sensitivity analysis of Smith's AMRV model

    International Nuclear Information System (INIS)

    Ho, Chih-Hsiang

    1995-01-01

    Multiple-expert hazard/risk assessments have considerable precedent, particularly in the Yucca Mountain site characterization studies. In this paper, we present a Bayesian approach to statistical modeling in volcanic hazard assessment for the Yucca Mountain site. Specifically, we show that the expert opinion on the site disruption parameter p is elicited on the prior distribution, π (p), based on geological information that is available. Moreover, π (p) can combine all available geological information motivated by conflicting but realistic arguments (e.g., simulation, cluster analysis, structural control, etc.). The incorporated uncertainties about the probability of repository disruption p, win eventually be averaged out by taking the expectation over π (p). We use the following priors in the analysis: priors chosen for mathematical convenience: Beta (r, s) for (r, s) = (2, 2), (3, 3), (5, 5), (2, 1), (2, 8), (8, 2), and (1, 1); and three priors motivated by expert knowledge. Sensitivity analysis is performed for each prior distribution. Estimated values of hazard based on the priors chosen for mathematical simplicity are uniformly higher than those obtained based on the priors motivated by expert knowledge. And, the model using the prior, Beta (8,2), yields the highest hazard (= 2.97 X 10 -2 ). The minimum hazard is produced by the open-quotes three-expert priorclose quotes (i.e., values of p are equally likely at 10 -3 10 -2 , and 10 -1 ). The estimate of the hazard is 1.39 x which is only about one order of magnitude smaller than the maximum value. The term, open-quotes hazardclose quotes, is defined as the probability of at least one disruption of a repository at the Yucca Mountain site by basaltic volcanism for the next 10,000 years

  3. MOESHA: A genetic algorithm for automatic calibration and estimation of parameter uncertainty and sensitivity of hydrologic models

    Science.gov (United States)

    Characterization of uncertainty and sensitivity of model parameters is an essential and often overlooked facet of hydrological modeling. This paper introduces an algorithm called MOESHA that combines input parameter sensitivity analyses with a genetic algorithm calibration routin...

  4. Electromyographic Study of Differential Sensitivity to Succinylcholine of the Diaphragm, Laryngeal and Somatic Muscles: A Swine Model

    Directory of Open Access Journals (Sweden)

    I-Cheng Lu

    2010-12-01

    Full Text Available Neuromuscular blocking agents (NMBAs might diminish the electromyography signal of the vocalis muscles during intraoperative neuromonitoring of the recurrent laryngeal nerve. The aim of this study was to compare differential sensitivity of different muscles to succinylcholine in a swine model, and to realize the influence of NMBAs on neuromonitoring. Six male Duroc-Landrace piglets were anesthetized with thiamylal and underwent tracheal intubation without the use of an NMBA. The left recurrent laryngeal nerve, the spinal accessory nerve, the right phrenic nerve and the brachial plexus were stimulated. Evoked potentials (electromyography signal of four muscle groups were elicited from needle electrodes before and after intravenous succinylcholine bolus (1.0 mg/kg. Recorded muscles included the vocalis muscles, trapezius muscle, diaphragm and triceps brachii muscles. The onset time and 80% recovery of control response were recorded and analyzed. The testing was repeated after 30 minutes. The onset time of neuromuscular blocking for the vocalis muscles, trapezius muscle, diaphragm and triceps brachii muscle was 36.3 ± 6.3 seconds, 38.8 ± 14.9 seconds, 52.5 ± 9.7 seconds and 45.0 ± 8.2 seconds during the first test; and 49.3 ± 10.8 seconds, 40.0 ± 12.2 seconds, 47.5 ± 11.9 seconds and 41.3 ± 10.1 seconds during the second test. The 80% recovery of the control response for each muscle was 18.3 ± 2.7 minutes, 16.5±6.9 minutes, 8.1±2.5 minutes and 14.8±2.9 minutes during the first test; and 21.5±3.8 minutes, 12.5 ± 4.3 minutes, 10.5 ± 3.1 minutes and 16.4 ± 4.2 minutes during the second test. The sensitivity of the muscles to succinylcholine, ranked in order, was: the vocalis muscles, the triceps brachii muscle, the trapezius muscle and the diaphragm. We demonstrated a useful and reliable animal model to investigate the effects of NMBAs on intraoperative neuromonitoring. Extrapolation of these data to humans should be done with caution.

  5. Parametric sensitivity analysis of an agro-economic model of management of irrigation water

    Science.gov (United States)

    El Ouadi, Ihssan; Ouazar, Driss; El Menyari, Younesse

    2015-04-01

    The current work aims to build an analysis and decision support tool for policy options concerning the optimal allocation of water resources, while allowing a better reflection on the issue of valuation of water by the agricultural sector in particular. Thus, a model disaggregated by farm type was developed for the rural town of Ait Ben Yacoub located in the east Morocco. This model integrates economic, agronomic and hydraulic data and simulates agricultural gross margin across in this area taking into consideration changes in public policy and climatic conditions, taking into account the competition for collective resources. To identify the model input parameters that influence over the results of the model, a parametric sensitivity analysis is performed by the "One-Factor-At-A-Time" approach within the "Screening Designs" method. Preliminary results of this analysis show that among the 10 parameters analyzed, 6 parameters affect significantly the objective function of the model, it is in order of influence: i) Coefficient of crop yield response to water, ii) Average daily gain in weight of livestock, iii) Exchange of livestock reproduction, iv) maximum yield of crops, v) Supply of irrigation water and vi) precipitation. These 6 parameters register sensitivity indexes ranging between 0.22 and 1.28. Those results show high uncertainties on these parameters that can dramatically skew the results of the model or the need to pay particular attention to their estimates. Keywords: water, agriculture, modeling, optimal allocation, parametric sensitivity analysis, Screening Designs, One-Factor-At-A-Time, agricultural policy, climate change.

  6. A computational model that predicts behavioral sensitivity to intracortical microstimulation

    Science.gov (United States)

    Kim, Sungshin; Callier, Thierri; Bensmaia, Sliman J.

    2017-02-01

    Objective. Intracortical microstimulation (ICMS) is a powerful tool to investigate the neural mechanisms of perception and can be used to restore sensation for patients who have lost it. While sensitivity to ICMS has previously been characterized, no systematic framework has been developed to summarize the detectability of individual ICMS pulse trains or the discriminability of pairs of pulse trains. Approach. We develop a simple simulation that describes the responses of a population of neurons to a train of electrical pulses delivered through a microelectrode. We then perform an ideal observer analysis on the simulated population responses to predict the behavioral performance of non-human primates in ICMS detection and discrimination tasks. Main results. Our computational model can predict behavioral performance across a wide range of stimulation conditions with high accuracy (R 2 = 0.97) and generalizes to novel ICMS pulse trains that were not used to fit its parameters. Furthermore, the model provides a theoretical basis for the finding that amplitude discrimination based on ICMS violates Weber’s law. Significance. The model can be used to characterize the sensitivity to ICMS across the range of perceptible and safe stimulation regimes. As such, it will be a useful tool for both neuroscience and neuroprosthetics.

  7. Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models

    Directory of Open Access Journals (Sweden)

    J. D. Herman

    2013-07-01

    Full Text Available The increase in spatially distributed hydrologic modeling warrants a corresponding increase in diagnostic methods capable of analyzing complex models with large numbers of parameters. Sobol' sensitivity analysis has proven to be a valuable tool for diagnostic analyses of hydrologic models. However, for many spatially distributed models, the Sobol' method requires a prohibitive number of model evaluations to reliably decompose output variance across the full set of parameters. We investigate the potential of the method of Morris, a screening-based sensitivity approach, to provide results sufficiently similar to those of the Sobol' method at a greatly reduced computational expense. The methods are benchmarked on the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM over a six-month period in the Blue River watershed, Oklahoma, USA. The Sobol' method required over six million model evaluations to ensure reliable sensitivity indices, corresponding to more than 30 000 computing hours and roughly 180 gigabytes of storage space. We find that the method of Morris is able to correctly screen the most and least sensitive parameters with 300 times fewer model evaluations, requiring only 100 computing hours and 1 gigabyte of storage space. The method of Morris proves to be a promising diagnostic approach for global sensitivity analysis of highly parameterized, spatially distributed hydrologic models.

  8. Categorical QSAR models for skin sensitization based on local lymph node assay measures and both ground and excited state 4D-fingerprint descriptors

    Science.gov (United States)

    Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Santos-Filho, Osvaldo A.; Esposito, Emilio X.; Hopfinger, Anton J.; Tseng, Yufeng J.

    2008-06-01

    In previous studies we have developed categorical QSAR models for predicting skin-sensitization potency based on 4D-fingerprint (4D-FP) descriptors and in vivo murine local lymph node assay (LLNA) measures. Only 4D-FP derived from the ground state (GMAX) structures of the molecules were used to build the QSAR models. In this study we have generated 4D-FP descriptors from the first excited state (EMAX) structures of the molecules. The GMAX, EMAX and the combined ground and excited state 4D-FP descriptors (GEMAX) were employed in building categorical QSAR models. Logistic regression (LR) and partial least square coupled logistic regression (PLS-CLR), found to be effective model building for the LLNA skin-sensitization measures in our previous studies, were used again in this study. This also permitted comparison of the prior ground state models to those involving first excited state 4D-FP descriptors. Three types of categorical QSAR models were constructed for each of the GMAX, EMAX and GEMAX datasets: a binary model (2-state), an ordinal model (3-state) and a binary-binary model (two-2-state). No significant differences exist among the LR 2-state model constructed for each of the three datasets. However, the PLS-CLR 3-state and 2-state models based on the EMAX and GEMAX datasets have higher predictivity than those constructed using only the GMAX dataset. These EMAX and GMAX categorical models are also more significant and predictive than corresponding models built in our previous QSAR studies of LLNA skin-sensitization measures.

  9. Numeric-modeling sensitivity analysis of the performance of wind turbine arrays

    Energy Technology Data Exchange (ETDEWEB)

    Lissaman, P.B.S.; Gyatt, G.W.; Zalay, A.D.

    1982-06-01

    An evaluation of the numerical model created by Lissaman for predicting the performance of wind turbine arrays has been made. Model predictions of the wake parameters have been compared with both full-scale and wind tunnel measurements. Only limited, full-scale data were available, while wind tunnel studies showed difficulties in representing real meteorological conditions. Nevertheless, several modifications and additions have been made to the model using both theoretical and empirical techniques and the new model shows good correlation with experiment. The larger wake growth rate and shorter near wake length predicted by the new model lead to reduced interference effects on downstream turbines and hence greater array efficiencies. The array model has also been re-examined and now incorporates the ability to show the effects of real meteorological conditions such as variations in wind speed and unsteady winds. The resulting computer code has been run to show the sensitivity of array performance to meteorological, machine, and array parameters. Ambient turbulence and windwise spacing are shown to dominate, while hub height ratio is seen to be relatively unimportant. Finally, a detailed analysis of the Goodnoe Hills wind farm in Washington has been made to show how power output can be expected to vary with ambient turbulence, wind speed, and wind direction.

  10. Overview and application of the Model Optimization, Uncertainty, and SEnsitivity Analysis (MOUSE) toolbox

    Science.gov (United States)

    For several decades, optimization and sensitivity/uncertainty analysis of environmental models has been the subject of extensive research. Although much progress has been made and sophisticated methods developed, the growing complexity of environmental models to represent real-world systems makes it...

  11. Structural development and web service based sensitivity analysis of the Biome-BGC MuSo model

    Science.gov (United States)

    Hidy, Dóra; Balogh, János; Churkina, Galina; Haszpra, László; Horváth, Ferenc; Ittzés, Péter; Ittzés, Dóra; Ma, Shaoxiu; Nagy, Zoltán; Pintér, Krisztina; Barcza, Zoltán

    2014-05-01

    -BGC with multi-soil layer). Within the frame of the BioVeL project (http://www.biovel.eu) an open source and domain independent scientific workflow management system (http://www.taverna.org.uk) are used to support 'in silico' experimentation and easy applicability of different models including Biome-BGC MuSo. Workflows can be built upon functionally linked sets of web services like retrieval of meteorological dataset and other parameters; preparation of single run or spatial run model simulation; desk top grid technology based Monte Carlo experiment with parallel processing; model sensitivity analysis, etc. The newly developed, Monte Carlo experiment based sensitivity analysis is described in this study and results are presented about differences in the sensitivity of the original and the developed Biome-BGC model.

  12. Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

    Science.gov (United States)

    Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

    2017-01-01

    Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  13. Sensitivity of numerical dispersion modeling to explosive source parameters

    International Nuclear Information System (INIS)

    Baskett, R.L.; Cederwall, R.T.

    1991-01-01

    The calculation of downwind concentrations from non-traditional sources, such as explosions, provides unique challenges to dispersion models. The US Department of Energy has assigned the Atmospheric Release Advisory Capability (ARAC) at the Lawrence Livermore National Laboratory (LLNL) the task of estimating the impact of accidental radiological releases to the atmosphere anywhere in the world. Our experience includes responses to over 25 incidents in the past 16 years, and about 150 exercises a year. Examples of responses to explosive accidents include the 1980 Titan 2 missile fuel explosion near Damascus, Arkansas and the hydrogen gas explosion in the 1986 Chernobyl nuclear power plant accident. Based on judgment and experience, we frequently estimate the source geometry and the amount of toxic material aerosolized as well as its particle size distribution. To expedite our real-time response, we developed some automated algorithms and default assumptions about several potential sources. It is useful to know how well these algorithms perform against real-world measurements and how sensitive our dispersion model is to the potential range of input values. In this paper we present the algorithms we use to simulate explosive events, compare these methods with limited field data measurements, and analyze their sensitivity to input parameters. 14 refs., 7 figs., 2 tabs

  14. Sensitivity analysis in multiple imputation in effectiveness studies of psychotherapy.

    Science.gov (United States)

    Crameri, Aureliano; von Wyl, Agnes; Koemeda, Margit; Schulthess, Peter; Tschuschke, Volker

    2015-01-01

    The importance of preventing and treating incomplete data in effectiveness studies is nowadays emphasized. However, most of the publications focus on randomized clinical trials (RCT). One flexible technique for statistical inference with missing data is multiple imputation (MI). Since methods such as MI rely on the assumption of missing data being at random (MAR), a sensitivity analysis for testing the robustness against departures from this assumption is required. In this paper we present a sensitivity analysis technique based on posterior predictive checking, which takes into consideration the concept of clinical significance used in the evaluation of intra-individual changes. We demonstrate the possibilities this technique can offer with the example of irregular longitudinal data collected with the Outcome Questionnaire-45 (OQ-45) and the Helping Alliance Questionnaire (HAQ) in a sample of 260 outpatients. The sensitivity analysis can be used to (1) quantify the degree of bias introduced by missing not at random data (MNAR) in a worst reasonable case scenario, (2) compare the performance of different analysis methods for dealing with missing data, or (3) detect the influence of possible violations to the model assumptions (e.g., lack of normality). Moreover, our analysis showed that ratings from the patient's and therapist's version of the HAQ could significantly improve the predictive value of the routine outcome monitoring based on the OQ-45. Since analysis dropouts always occur, repeated measurements with the OQ-45 and the HAQ analyzed with MI are useful to improve the accuracy of outcome estimates in quality assurance assessments and non-randomized effectiveness studies in the field of outpatient psychotherapy.

  15. Uncertainty and sensitivity assessments of an agricultural-hydrological model (RZWQM2) using the GLUE method

    Science.gov (United States)

    Sun, Mei; Zhang, Xiaolin; Huo, Zailin; Feng, Shaoyuan; Huang, Guanhua; Mao, Xiaomin

    2016-03-01

    Quantitatively ascertaining and analyzing the effects of model uncertainty on model reliability is a focal point for agricultural-hydrological models due to more uncertainties of inputs and processes. In this study, the generalized likelihood uncertainty estimation (GLUE) method with Latin hypercube sampling (LHS) was used to evaluate the uncertainty of the RZWQM-DSSAT (RZWQM2) model outputs responses and the sensitivity of 25 parameters related to soil properties, nutrient transport and crop genetics. To avoid the one-sided risk of model prediction caused by using a single calibration criterion, the combined likelihood (CL) function integrated information concerning water, nitrogen, and crop production was introduced in GLUE analysis for the predictions of the following four model output responses: the total amount of water content (T-SWC) and the nitrate nitrogen (T-NIT) within the 1-m soil profile, the seed yields of waxy maize (Y-Maize) and winter wheat (Y-Wheat). In the process of evaluating RZWQM2, measurements and meteorological data were obtained from a field experiment that involved a winter wheat and waxy maize crop rotation system conducted from 2003 to 2004 in southern Beijing. The calibration and validation results indicated that RZWQM2 model can be used to simulate the crop growth and water-nitrogen migration and transformation in wheat-maize crop rotation planting system. The results of uncertainty analysis using of GLUE method showed T-NIT was sensitive to parameters relative to nitrification coefficient, maize growth characteristics on seedling period, wheat vernalization period, and wheat photoperiod. Parameters on soil saturated hydraulic conductivity, nitrogen nitrification and denitrification, and urea hydrolysis played an important role in crop yield component. The prediction errors for RZWQM2 outputs with CL function were relatively lower and uniform compared with other likelihood functions composed of individual calibration criterion. This

  16. Testing a river basin model with sensitivity analysis and autocalibration for an agricultural catchment in SW Finland

    Directory of Open Access Journals (Sweden)

    S. TATTARI

    2008-12-01

    Full Text Available Modeling tools are needed to assess (i the amounts of loading from agricultural sources to water bodies as well as (ii the alternative management options in varying climatic conditions. These days, the implementation of Water Framework Directive (WFD has put totally new requirements also for modeling approaches. The physically based models are commonly not operational and thus the usability of these models is restricted for a few selected catchments. But the rewarding feature of these process-based models is an option to study the effect of protection measures on a catchment scale and, up to a certain point, a possibility to upscale the results. In this study, the parameterization of the SWAT model was developed in terms of discharge dynamics and nutrient loads, and a sensitivity analysis regarding discharge and sediment concentration was made. The SWAT modeling exercise was carried out for a 2nd order catchment (Yläneenjoki, 233 km2 of the Eurajoki river basin in southwestern Finland. The Yläneenjoki catchment has been intensively monitored during the last 14 years. Hence, there was enough background information available for both parameter setup and calibration. In addition to load estimates, SWAT also offers possibility to assess the effects of various agricultural management actions like fertilization, tillage practices, choice of cultivated plants, buffer strips, sedimentation ponds and constructed wetlands (CWs on loading. Moreover, information on local agricultural practices and the implemented and planned protective measures were readily available thanks to aware farmers and active authorities. Here, we studied how CWs can reduce the nutrient load at the outlet of the Yläneenjoki river basin. The results suggested that sensitivity analysis and autocalibration tools incorporated in the model are useful by pointing out the most influential parameters, and that flow dynamics and annual loading values can be modeled with reasonable

  17. An investigation of the sensitivity of a land surface model to climate change using a reduced form model

    Energy Technology Data Exchange (ETDEWEB)

    Lynch, A.H.; McIlwaine, S. [PAOS/CIRES, Univ. of Colorado, Boulder, CO (United States); Beringer, J. [Inst. of Arctic Biology, Univ. of Alaska, Fairbanks (United States); Bonan, G.B. [National Center for Atmospheric Research, Boulder, CO (United States)

    2001-05-01

    In an illustration of a model evaluation methodology, a multivariate reduced form model is developed to evaluate the sensitivity of a land surface model to changes in atmospheric forcing. The reduced form model is constructed in terms of a set of ten integrative response metrics, including the timing of spring snow melt, sensible and latent heat fluxes in summer, and soil temperature. The responses are evaluated as a function of a selected set of six atmospheric forcing perturbations which are varied simultaneously, and hence each may be thought of as a six-dimensional response surface. The sensitivities of the land surface model are interdependent and in some cases illustrate a physically plausible feedback process. The important predictors of land surface response in a changing climate are the atmospheric temperature and downwelling longwave radiation. Scenarios characterized by warming and drying produce a large relative response compared to warm, moist scenarios. The insensitivity of the model to increases in precipitation and atmospheric humidity is expected to change in applications to coupled models, since these parameters are also strongly implicated, through the representation of clouds, in the simulation of both longwave and shortwave radiation. (orig.)

  18. Sensitivity analysis of a discrete fracture network model for performance assessment of Aberg

    International Nuclear Information System (INIS)

    Outters, N.; Shuttle, D.

    2000-12-01

    This report presents a sensitivity analysis of pathway simulations in a DFN model. The DFN model consists of two sets of stochastic fractures at different scales and the canister locations of a hypothetical repository layout. The hydrogeological base case model is defined by constant head boundary conditions on the edges of a 2000 x 2000 x 1000 m 3 block. The pathway analysis carried out by the program PAWorks provides pathway parameters (pathway length, pathway width, transport aperture, reactive surface area, pathway transmissivity), canister statistics (average number of pathways per canister, percentage of canister locations with pathways) and visualisation of pathways. The project provided the following results from the alternative cases: Case 1: Model with a 100 m thick fracture network at the repository scale instead of 50 m in the base case. The model is little sensitive to the increase of the thickness of the local fracture network. Case 2: Model including fracture networks where the mean size and size standard deviation is twice the ones used in the base case. The travel times to the biosphere is slightly shortened by increasing the fracture diameter. Case 3: Two models with alternative hydraulic boundary conditions: two different flux boundary conditions are tested instead of head boundary conditions in the base case. The advective travel time is shortened by changing the boundary conditions in both alternative cases; in some cases it is reduced to less than a year. Case 4: Study of alternative pathway search algorithms: the pathway search is here based on minimum travel time. The pathway search algorithm of PAWorks based on minimum travel time gives much more optimistic results than the base case where the maximum flow rate was used. The mean travel time is about 5000 years. Due to editorial reasons only a subset of all this information is treated in this report

  19. Advanced postbuckling and imperfection sensitivity of the elastic-plastic Shanley-Hutchinson model column

    DEFF Research Database (Denmark)

    Christensen, Claus Dencker; Byskov, Esben

    2008-01-01

    The postbuckling behavior and imperfection sensitivity of the Shanley-Hutchinson plastic model column introduced by Hutchinson in 1973 are examined. The study covers the initial, buckled state and the advanced postbuckling regime of the geometrically perfect realization as well as its sensitivity...... to geometric imperfections. In Section 1, which is concerned with the perfect structure, a new, simple explicit upper bound for all solutions to the problem is found when the tangent modulus at bifurcation vanishes compared to the linear elastic (unloading) modulus. The difference between the upper bound...... and the solution to an actual problem is determined by an asymptotic expansion involving hyperbolic trial functions (instead of polynomials) which fulfill general boundary conditions at bifurcation and infinity. The method provides an accurate estimate of the maximum load even if it occurs in an advanced...

  20. Forecasting hypoxia in the Chesapeake Bay and Gulf of Mexico: model accuracy, precision, and sensitivity to ecosystem change

    International Nuclear Information System (INIS)

    Evans, Mary Anne; Scavia, Donald

    2011-01-01

    Increasing use of ecological models for management and policy requires robust evaluation of model precision, accuracy, and sensitivity to ecosystem change. We conducted such an evaluation of hypoxia models for the northern Gulf of Mexico and Chesapeake Bay using hindcasts of historical data, comparing several approaches to model calibration. For both systems we find that model sensitivity and precision can be optimized and model accuracy maintained within reasonable bounds by calibrating the model to relatively short, recent 3 year datasets. Model accuracy was higher for Chesapeake Bay than for the Gulf of Mexico, potentially indicating the greater importance of unmodeled processes in the latter system. Retrospective analyses demonstrate both directional and variable changes in sensitivity of hypoxia to nutrient loads.

  1. High degree gravitational sensitivity from Mars orbiters for the GMM-1 gravity model

    Science.gov (United States)

    Lerch, F. J.; Smith, D. E.; Chan, J. C.; Patel, G. B.; Chinn, D. S.

    1994-01-01

    Orbital sensitivity of the gravity field for high degree terms (greater than 30) is analyzed on satellites employed in a Goddard Mars Model GMM-1, complete in spherical harmonics through degree and order 50. The model is obtained from S-band Doppler data on Mariner 9 (M9), Viking Orbiter 1 (VO1), and Viking Orbiter 2 (VO2) spacecraft, which were tracked by the NASA Deep Space Network on seven different highly eccentric orbits. The main sensitivity of the high degree terms is obtained from the VO1 and VO2 low orbits (300 km periapsis altitude), where significant spectral sensitivity is seen for all degrees out through degree 50. The velocity perturbations show a dominant effect at periapsis and significant effects out beyond the semi-latus rectum covering over 180 degrees of the orbital groundtrack for the low altitude orbits. Because of the wideband of periapsis motion covering nearly 180 degrees in w and +39 degrees in latitude coverage, the VO1 300 km periapsis altitude orbit with inclination of 39 degrees gave the dominant sensitivity in the GMM-1 solution for the high degree terms. Although the VO2 low periapsis orbit has a smaller band of periapsis mapping coverage, it strongly complements the VO1 orbit sensitivity for the GMM-1 solution with Doppler tracking coverage over a different inclination of 80 degrees.

  2. Model sensitivity studies of the decrease in atmospheric carbon tetrachloride

    Directory of Open Access Journals (Sweden)

    M. P. Chipperfield

    2016-12-01

    Full Text Available Carbon tetrachloride (CCl4 is an ozone-depleting substance, which is controlled by the Montreal Protocol and for which the atmospheric abundance is decreasing. However, the current observed rate of this decrease is known to be slower than expected based on reported CCl4 emissions and its estimated overall atmospheric lifetime. Here we use a three-dimensional (3-D chemical transport model to investigate the impact on its predicted decay of uncertainties in the rates at which CCl4 is removed from the atmosphere by photolysis, by ocean uptake and by degradation in soils. The largest sink is atmospheric photolysis (74 % of total, but a reported 10 % uncertainty in its combined photolysis cross section and quantum yield has only a modest impact on the modelled rate of CCl4 decay. This is partly due to the limiting effect of the rate of transport of CCl4 from the main tropospheric reservoir to the stratosphere, where photolytic loss occurs. The model suggests large interannual variability in the magnitude of this stratospheric photolysis sink caused by variations in transport. The impact of uncertainty in the minor soil sink (9 % of total is also relatively small. In contrast, the model shows that uncertainty in ocean loss (17 % of total has the largest impact on modelled CCl4 decay due to its sizeable contribution to CCl4 loss and large lifetime uncertainty range (147 to 241 years. With an assumed CCl4 emission rate of 39 Gg year−1, the reference simulation with the best estimate of loss processes still underestimates the observed CCl4 (overestimates the decay over the past 2 decades but to a smaller extent than previous studies. Changes to the rate of CCl4 loss processes, in line with known uncertainties, could bring the model into agreement with in situ surface and remote-sensing measurements, as could an increase in emissions to around 47 Gg year−1. Further progress in constraining the CCl4 budget is partly limited by

  3. Geostatistical and adjoint sensitivity techniques applied to a conceptual model of ground-water flow in the Paradox Basin, Utah

    International Nuclear Information System (INIS)

    Metcalfe, D.E.; Campbell, J.E.; RamaRao, B.S.; Harper, W.V.; Battelle Project Management Div., Columbus, OH)

    1985-01-01

    Sensitivity and uncertainty analysis are important components of performance assessment activities for potential high-level radioactive waste repositories. The application of geostatistical and adjoint sensitivity techniques to aid in the calibration of an existing conceptual model of ground-water flow is demonstrated for the Leadville Limestone in Paradox Basin, Utah. The geostatistical method called kriging is used to statistically analyze the measured potentiometric data for the Leadville. This analysis consists of identifying anomalous data and data trends and characterizing the correlation structure between data points. Adjoint sensitivity analysis is then performed to aid in the calibration of a conceptual model of ground-water flow to the Leadville measured potentiometric data. Sensitivity derivatives of the fit between the modeled Leadville potentiometric surface and the measured potentiometric data to model parameters and boundary conditions are calculated by the adjoint method. These sensitivity derivatives are used to determine which model parameter and boundary condition values should be modified to most efficiently improve the fit of modeled to measured potentiometric conditions

  4. Sensitivity of modeled ozone concentrations to uncertainties in biogenic emissions

    International Nuclear Information System (INIS)

    Roselle, S.J.

    1992-06-01

    The study examines the sensitivity of regional ozone (O3) modeling to uncertainties in biogenic emissions estimates. The United States Environmental Protection Agency's (EPA) Regional Oxidant Model (ROM) was used to simulate the photochemistry of the northeastern United States for the period July 2-17, 1988. An operational model evaluation showed that ROM had a tendency to underpredict O3 when observed concentrations were above 70-80 ppb and to overpredict O3 when observed values were below this level. On average, the model underpredicted daily maximum O3 by 14 ppb. Spatial patterns of O3, however, were reproduced favorably by the model. Several simulations were performed to analyze the effects of uncertainties in biogenic emissions on predicted O3 and to study the effectiveness of two strategies of controlling anthropogenic emissions for reducing high O3 concentrations. Biogenic hydrocarbon emissions were adjusted by a factor of 3 to account for the existing range of uncertainty in these emissions. The impact of biogenic emission uncertainties on O3 predictions depended upon the availability of NOx. In some extremely NOx-limited areas, increasing the amount of biogenic emissions decreased O3 concentrations. Two control strategies were compared in the simulations: (1) reduced anthropogenic hydrocarbon emissions, and (2) reduced anthropogenic hydrocarbon and NOx emissions. The simulations showed that hydrocarbon emission controls were more beneficial to the New York City area, but that combined NOx and hydrocarbon controls were more beneficial to other areas of the Northeast. Hydrocarbon controls were more effective as biogenic hydrocarbon emissions were reduced, whereas combined NOx and hydrocarbon controls were more effective as biogenic hydrocarbon emissions were increased

  5. Low Complexity Models to improve Incomplete Sensitivities for Shape Optimization

    Science.gov (United States)

    Stanciu, Mugurel; Mohammadi, Bijan; Moreau, Stéphane

    2003-01-01

    The present global platform for simulation and design of multi-model configurations treat shape optimization problems in aerodynamics. Flow solvers are coupled with optimization algorithms based on CAD-free and CAD-connected frameworks. Newton methods together with incomplete expressions of gradients are used. Such incomplete sensitivities are improved using reduced models based on physical assumptions. The validity and the application of this approach in real-life problems are presented. The numerical examples concern shape optimization for an airfoil, a business jet and a car engine cooling axial fan.

  6. Assessing modeled Greenland surface mass balance in the GISS Model E2 and its sensitivity to surface albedo

    Science.gov (United States)

    Alexander, Patrick; LeGrande, Allegra N.; Koenig, Lora S.; Tedesco, Marco; Moustafa, Samiah E.; Ivanoff, Alvaro; Fischer, Robert P.; Fettweis, Xavier

    2016-04-01

    The surface mass balance (SMB) of the Greenland Ice Sheet (GrIS) plays an important role in global sea level change. Regional Climate Models (RCMs) such as the Modèle Atmosphérique Régionale (MAR) have been employed at high spatial resolution with relatively complex physics to simulate ice sheet SMB. Global climate models (GCMs) incorporate less sophisticated physical schemes and provide outputs at a lower spatial resolution, but have the advantage of modeling the interaction between different components of the earth's oceans, climate, and land surface at a global scale. Improving the ability of GCMs to represent ice sheet SMB is important for making predictions of future changes in global sea level. With the ultimate goal of improving SMB simulated by the Goddard Institute for Space Studies (GISS) Model E2 GCM, we compare simulated GrIS SMB against the outputs of the MAR model and radar-derived estimates of snow accumulation. In order to reproduce present-day climate variability in the Model E2 simulation, winds are constrained to match the reanalysis datasets used to force MAR at the lateral boundaries. We conduct a preliminary assessment of the sensitivity of the simulated Model E2 SMB to surface albedo, a parameter that is known to strongly influence SMB. Model E2 albedo is set to a fixed value of 0.8 over the entire ice sheet in the initial configuration of the model (control case). We adjust this fixed value in an ensemble of simulations over a range of 0.4 to 0.8 (roughly the range of observed summer GrIS albedo values) to examine the sensitivity of ice-sheet-wide SMB to albedo. We prescribe albedo from the Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43A3 v6 to examine the impact of a more realistic spatial and temporal variations in albedo. An age-dependent snow albedo parameterization is applied, and its impact on SMB relative to observations and the RCM is assessed.

  7. Application of the CIPP model in the study of factors that promote intercultural sensitivity

    Directory of Open Access Journals (Sweden)

    Ruiz-Bernardo, Paola

    2012-10-01

    Full Text Available The present study proposes a group of factors (related to self, context and process favouring the development of intercultural sensitivity. A social diagnosis was performed in the Spanish province of Castellón in order to identify these factors by means of a correlational study. A non-probabilistic but representative sample consisting of 995 people from 37 different countries living in this province was used. Data were collected by means of an adaptation of the scale proposed by Chen and Starosta (2000 for the assessment of intercultural sensitivity. Results showed four profiles, and their main characteristics were studied. Variables such as country of origin, gender, academic background, number of languages spoken, or the experience of living in a foreign country revealed to have a positive influence on the development of this attitude. El presente artículo propone un conjunto de los factores (personales, contextuales y de proceso que favorecen el desarrollo de la sensibilidad intercultural. Para identificar dichos factores se ha realizado un diagnóstico social en la provincia de Castellón (España. Este estudio de tipo descriptivo de carácter correlacional se ha concretado con una muestra de 995 personas de 37 nacionalidades diferentes, constituyendo una muestra representativa, caracterizada por ser de tipo fortuito o accidental. Para recoger la información se ha utilizado una adaptación de la escala de sensibilidad intercultural de Chen y Starosta (2000. El análisis de datos ha permitido identificar cuatro perfiles, de los cuales se han estudiado sus principales características y se ha podido concluir que variables tales como la condición de origen, el sexo, la formación, la cantidad de lenguas que habla o el haber vivido en otro país influyen positivamente para el desarrollo de esta actitud.

  8. SENSITIVITY ANALYSIS OF BIOME-BGC MODEL FOR DRY TROPICAL FORESTS OF VINDHYAN HIGHLANDS, INDIA

    OpenAIRE

    M. Kumar; A. S. Raghubanshi

    2012-01-01

    A process-based model BIOME-BGC was run for sensitivity analysis to see the effect of ecophysiological parameters on net primary production (NPP) of dry tropical forest of India. The sensitivity test reveals that the forest NPP was highly sensitive to the following ecophysiological parameters: Canopy light extinction coefficient (k), Canopy average specific leaf area (SLA), New stem C : New leaf C (SC:LC), Maximum stomatal conductance (gs,max), C:N of fine roots (C:Nfr), All-sided to...

  9. Assessing flood risk at the global scale: model setup, results, and sensitivity

    International Nuclear Information System (INIS)

    Ward, Philip J; Jongman, Brenden; Weiland, Frederiek Sperna; Winsemius, Hessel C; Bouwman, Arno; Ligtvoet, Willem; Van Beek, Rens; Bierkens, Marc F P

    2013-01-01

    Globally, economic losses from flooding exceeded $19 billion in 2012, and are rising rapidly. Hence, there is an increasing need for global-scale flood risk assessments, also within the context of integrated global assessments. We have developed and validated a model cascade for producing global flood risk maps, based on numerous flood return-periods. Validation results indicate that the model simulates interannual fluctuations in flood impacts well. The cascade involves: hydrological and hydraulic modelling; extreme value statistics; inundation modelling; flood impact modelling; and estimating annual expected impacts. The initial results estimate global impacts for several indicators, for example annual expected exposed population (169 million); and annual expected exposed GDP ($1383 billion). These results are relatively insensitive to the extreme value distribution employed to estimate low frequency flood volumes. However, they are extremely sensitive to the assumed flood protection standard; developing a database of such standards should be a research priority. Also, results are sensitive to the use of two different climate forcing datasets. The impact model can easily accommodate new, user-defined, impact indicators. We envisage several applications, for example: identifying risk hotspots; calculating macro-scale risk for the insurance industry and large companies; and assessing potential benefits (and costs) of adaptation measures. (letter)

  10. A gaze-contingent display to study contrast sensitivity under natural viewing conditions

    Science.gov (United States)

    Dorr, Michael; Bex, Peter J.

    2011-03-01

    Contrast sensitivity has been extensively studied over the last decades and there are well-established models of early vision that were derived by presenting the visual system with synthetic stimuli such as sine-wave gratings near threshold contrasts. Natural scenes, however, contain a much wider distribution of orientations, spatial frequencies, and both luminance and contrast values. Furthermore, humans typically move their eyes two to three times per second under natural viewing conditions, but most laboratory experiments require subjects to maintain central fixation. We here describe a gaze-contingent display capable of performing real-time contrast modulations of video in retinal coordinates, thus allowing us to study contrast sensitivity when dynamically viewing dynamic scenes. Our system is based on a Laplacian pyramid for each frame that efficiently represents individual frequency bands. Each output pixel is then computed as a locally weighted sum of pyramid levels to introduce local contrast changes as a function of gaze. Our GPU implementation achieves real-time performance with more than 100 fps on high-resolution video (1920 by 1080 pixels) and a synthesis latency of only 1.5ms. Psychophysical data show that contrast sensitivity is greatly decreased in natural videos and under dynamic viewing conditions. Synthetic stimuli therefore only poorly characterize natural vision.

  11. Sensitivity of Reliability Estimates in Partially Damaged RC Structures subject to Earthquakes, using Reduced Hysteretic Models

    DEFF Research Database (Denmark)

    Iwankiewicz, R.; Nielsen, Søren R. K.; Skjærbæk, P. S.

    The subject of the paper is the investigation of the sensitivity of structural reliability estimation by a reduced hysteretic model for a reinforced concrete frame under an earthquake excitation.......The subject of the paper is the investigation of the sensitivity of structural reliability estimation by a reduced hysteretic model for a reinforced concrete frame under an earthquake excitation....

  12. Sensitivity of Earthquake Loss Estimates to Source Modeling Assumptions and Uncertainty

    Science.gov (United States)

    Reasenberg, Paul A.; Shostak, Nan; Terwilliger, Sharon

    2006-01-01

    adopted in the loss calculations. This is a sensitivity study aimed at future regional earthquake source modelers, so that they may be informed of the effects on loss introduced by modeling assumptions and epistemic uncertainty in the WG02 earthquake source model.

  13. Intercultural Sensitivity through Short-Term Study Abroad

    Science.gov (United States)

    Bloom, Melanie; Miranda, Arturo

    2015-01-01

    One of the foremost-cited rationales for study abroad during college is the development of a global perspective and intercultural sensitivity. Although this argument is mentioned frequently in promotional materials for study abroad, it has not yet been backed by research based on the outcomes of students' study abroad experiences. As more…

  14. Automatic CT-based finite element model generation for temperature-based death time estimation: feasibility study and sensitivity analysis.

    Science.gov (United States)

    Schenkl, Sebastian; Muggenthaler, Holger; Hubig, Michael; Erdmann, Bodo; Weiser, Martin; Zachow, Stefan; Heinrich, Andreas; Güttler, Felix Victor; Teichgräber, Ulf; Mall, Gita

    2017-05-01

    Temperature-based death time estimation is based either on simple phenomenological models of corpse cooling or on detailed physical heat transfer models. The latter are much more complex but allow a higher accuracy of death time estimation, as in principle, all relevant cooling mechanisms can be taken into account.Here, a complete workflow for finite element-based cooling simulation is presented. The following steps are demonstrated on a CT phantom: Computer tomography (CT) scan Segmentation of the CT images for thermodynamically relevant features of individual geometries and compilation in a geometric computer-aided design (CAD) model Conversion of the segmentation result into a finite element (FE) simulation model Computation of the model cooling curve (MOD) Calculation of the cooling time (CTE) For the first time in FE-based cooling time estimation, the steps from the CT image over segmentation to FE model generation are performed semi-automatically. The cooling time calculation results are compared to cooling measurements performed on the phantoms under controlled conditions. In this context, the method is validated using a CT phantom. Some of the phantoms' thermodynamic material parameters had to be determined via independent experiments.Moreover, the impact of geometry and material parameter uncertainties on the estimated cooling time is investigated by a sensitivity analysis.

  15. Performance Modeling of Mimosa pudica Extract as a Sensitizer for Solar Energy Conversion

    Directory of Open Access Journals (Sweden)

    M. B. Shitta

    2016-01-01

    Full Text Available An organic material is proposed as a sustainable sensitizer and a replacement for the synthetic sensitizer in a dye-sensitized solar cell technology. Using the liquid extract from the leaf of a plant called Mimosa pudica (M. pudica as a sensitizer, the performance characteristics of the extract of M. pudica are investigated. The photo-anode of each of the solar cell sample is passivated with a self-assembly monolayer (SAM from a set of four materials, including alumina, formic acid, gelatine, and oxidized starch. Three sets of five samples of an M. pudica–based solar cell are produced, with the fifth sample used as the control experiment. Each of the solar cell samples has an active area of 0.3848cm2. A two-dimensional finite volume method (FVM is used to model the transport of ions within the monolayer of the solar cell. The performance of the experimentally fabricated solar cells compares qualitatively with the ones obtained from the literature and the simulated solar cells. The highest efficiency of 3% is obtained from the use of the extract as a sensitizer. It is anticipated that the comparison of the performance characteristics with further research on the concentration of M. pudica extract will enhance the development of a reliable and competitive organic solar cell. It is also recommended that further research should be carried out on the concentration of the extract and electrolyte used in this study for a possible improved performance of the cell.

  16. Acute and chronic sensitivity to copper of a promising ecotoxicological model species, the annual killifish Nothobranchius furzeri.

    Science.gov (United States)

    Philippe, Charlotte; Grégoir, Arnout F; Janssens, Lizanne; Pinceel, Tom; De Boeck, Gudrun; Brendonck, Luc

    2017-10-01

    Nothobranchius furzeri is a promising model for ecotoxicological research due to the species' short life cycle and the production of drought-resistant eggs. Although the species is an emerging vertebrate fish model for several fundamental as well as applied research domains, its potential for ecotoxicological research has not yet been tested. The aim of this study was to characterise the acute and chronic sensitivity of this species to copper as compared to other model organisms. Effects of both acute and chronic copper exposure were tested on survival, life history and physiological traits. We report a 24h-LC 50 of 53.93µg Cu/L, which is situated within the sensitivity range of other model species such as Brook Trout, Fathead Minnow and Rainbow Trout. Moreover, in the full life cycle exposure, we show that an exposure concentration of 10.27µg/L did not cause acute adverse effects (96h), but did cause mortality after prolonged exposure (3-4 weeks). Also chronic, sublethal effects were observed, such as a reduction in growth rate, delayed maturation and postponed reproduction. Based on our results, we define the NOEC at 6.68µg Cu/L, making N. furzeri more sensitive to copper as compared to Brook Trout and Fathead Minnow. We found stimulatory effects on peak fecundity at subinhibitory levels of copper concentrations (hormesis). Finally, we found indications for detoxifying and copper-excreting mechanisms, demonstrating the ability of the fish to cope with this essential metal, even when exposed to stressful amounts. The successful application of current ecotoxicological protocols on N. furzeri and its sensitivity range comparable to that of other model organisms forms the basis to exploit this species in further ecotoxicological practices. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. QSAR models of human data can enrich or replace LLNA testing for human skin sensitization

    OpenAIRE

    Alves, Vinicius M.; Capuzzi, Stephen J.; Muratov, Eugene; Braga, Rodolpho C.; Thornton, Thomas; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

    2016-01-01

    Skin sensitization is a major environmental and occupational health hazard. Although many chemicals have been evaluated in humans, there have been no efforts to model these data to date. We have compiled, curated, analyzed, and compared the available human and LLNA data. Using these data, we have developed reliable computational models and applied them for virtual screening of chemical libraries to identify putative skin sensitizers. The overall concordance between murine LLNA and human skin ...

  18. Sensitivity Analysis of Fatigue Crack Growth Model for API Steels in Gaseous Hydrogen.

    Science.gov (United States)

    Amaro, Robert L; Rustagi, Neha; Drexler, Elizabeth S; Slifka, Andrew J

    2014-01-01

    A model to predict fatigue crack growth of API pipeline steels in high pressure gaseous hydrogen has been developed and is presented elsewhere. The model currently has several parameters that must be calibrated for each pipeline steel of interest. This work provides a sensitivity analysis of the model parameters in order to provide (a) insight to the underlying mathematical and mechanistic aspects of the model, and (b) guidance for model calibration of other API steels.

  19. Development and Sensitivity Analysis of a Fully Kinetic Model of Sequential Reductive Dechlorination in Groundwater

    DEFF Research Database (Denmark)

    Malaguerra, Flavio; Chambon, Julie Claire Claudia; Bjerg, Poul Løgstrup

    2011-01-01

    experiments of complete trichloroethene (TCE) degradation in natural sediments. Global sensitivity analysis was performed using the Morris method and Sobol sensitivity indices to identify the most influential model parameters. Results show that the sulfate concentration and fermentation kinetics are the most...

  20. Sensitivity of the polypropylene to the strain rate: experiments and modeling

    International Nuclear Information System (INIS)

    Abdul-Latif, A.; Aboura, Z.; Mosleh, L.

    2002-01-01

    Full text.The main goal of this work is first to evaluate experimentally the strain rate dependent deformation of the polypropylene under tensile load; and secondly is to propose a model capable to appropriately describe the mechanical behavior of this material and especially its sensitivity to the strain rate. Several experimental tensile tests are performed at different quasi-static strain rates in the range of 10 -5 s -1 to 10 -1 s -1 . In addition to some relaxation tests are also conducted introducing the strain rate jumping state during testing. Within the framework of elastoviscoplasticity, a phenomenological model is developed for describing the non-linear mechanical behavior of the material under uniaxial loading paths. With the small strain assumption, the sensitivity of the polypropylene to the strain rate being of particular interest in this work, is accordingly taken into account. As a matter of fact, since this model is based on internal state variables, we assume thus that the material sensitivity to the strain rate is governed by the kinematic hardening variable notably its modulus and the accumulated viscoplastic strain. As far as the elastic behavior is concerned, it is noticed that such a behavior is slightly influenced by the employed strain rate rage. For this reason, the elastic behavior is classically determined, i.e. without coupling with the strain rate dependent deformation. It is obvious that the inelastic behavior of the used material is thoroughly dictated by the applied strain rate. Hence, the model parameters are well calibrated utilizing several experimental databases for different strain rates (10 -5 s -1 to 10 -1 s -1 ). Actually, among these experimental results, some experiments related to the relaxation phenomenon and strain rate jumping during testing (increasing or decreasing) are also used in order to more perfect the model parameters identification. To validate the calibrated model parameters, simulation tests are achieved