Uncertainty and sensitivity analyses of the complete program system UFOMOD and of selected submodels

International Nuclear Information System (INIS)

Fischer, F.; Ehrhardt, J.; Hasemann, I.

1990-09-01

Uncertainty and sensitivity studies with the program system UFOMOD have been performed since several years on a submodel basis to get a deeper insight into the propagation of parameter uncertainties through the different modules and to quantify their contribution to the confidence bands of the intermediate and final results of an accident consequence assessment. In a series of investigations with the atmospheric dispersion module, the models describing early protective actions, the models calculating short-term organ doses and the health effects model of the near range subsystem NE of UFOMOD, a great deal of experience has been gained with methods and evaluation techniques for uncertainty and sensitivity analyses. Especially the influence on results of different sampling techniques and sample sizes, parameter distributions and correlations could be quantified and the usefulness of sensitivity measures for the interpretation of results could be demonstrated. In each submodel investigation, the (5%, 95%)-confidende bounds of the complementary cumulative frequency distributions (CCFDs) of various consequence types (activity concentrations of I-131 and Cs-137, individual acute organ doses, individual risks of nonstochastic health effects, and the number of early deaths) were calculated. The corresponding sensitivity analyses for each of these endpoints led to a list of parameters contributing significantly to the variation of mean values and 99% - fractiles. The most important parameters were extracted and combined for the final overall analysis. (orig.) [de

Sensitivity analyses of factors influencing CMAQ performance for fine particulate nitrate.

Science.gov (United States)

Shimadera, Hikari; Hayami, Hiroshi; Chatani, Satoru; Morino, Yu; Mori, Yasuaki; Morikawa, Tazuko; Yamaji, Kazuyo; Ohara, Toshimasa

2014-04-01

Improvement of air quality models is required so that they can be utilized to design effective control strategies for fine particulate matter (PM2.5). The Community Multiscale Air Quality modeling system was applied to the Greater Tokyo Area of Japan in winter 2010 and summer 2011. The model results were compared with observed concentrations of PM2.5 sulfate (SO4(2-)), nitrate (NO3(-)) and ammonium, and gaseous nitric acid (HNO3) and ammonia (NH3). The model approximately reproduced PM2.5 SO4(2-) concentration, but clearly overestimated PM2.5 NO3(-) concentration, which was attributed to overestimation of production of ammonium nitrate (NH4NO3). This study conducted sensitivity analyses of factors associated with the model performance for PM2.5 NO3(-) concentration, including temperature and relative humidity, emission of nitrogen oxides, seasonal variation of NH3 emission, HNO3 and NH3 dry deposition velocities, and heterogeneous reaction probability of dinitrogen pentoxide. Change in NH3 emission directly affected NH3 concentration, and substantially affected NH4NO3 concentration. Higher dry deposition velocities of HNO3 and NH3 led to substantial reductions of concentrations of the gaseous species and NH4NO3. Because uncertainties in NH3 emission and dry deposition processes are probably large, these processes may be key factors for improvement of the model performance for PM2.5 NO3(-). The Community Multiscale Air Quality modeling system clearly overestimated the concentration of fine particulate nitrate in the Greater Tokyo Area of Japan, which was attributed to overestimation of production of ammonium nitrate. Sensitivity analyses were conducted for factors associated with the model performance for nitrate. Ammonia emission and dry deposition of nitric acid and ammonia may be key factors for improvement of the model performance.

Sobol method application in dimensional sensitivity analyses of different AFM cantilevers for biological particles

Science.gov (United States)

Korayem, M. H.; Taheri, M.; Ghahnaviyeh, S. D.

2015-08-01

Due to the more delicate nature of biological micro/nanoparticles, it is necessary to compute the critical force of manipulation. The modeling and simulation of reactions and nanomanipulator dynamics in a precise manipulation process require an exact modeling of cantilevers stiffness, especially the stiffness of dagger cantilevers because the previous model is not useful for this investigation. The stiffness values for V-shaped cantilevers can be obtained through several methods. One of them is the PBA method. In another approach, the cantilever is divided into two sections: a triangular head section and two slanted rectangular beams. Then, deformations along different directions are computed and used to obtain the stiffness values in different directions. The stiffness formulations of dagger cantilever are needed for this sensitivity analyses so the formulations have been driven first and then sensitivity analyses has been started. In examining the stiffness of the dagger-shaped cantilever, the micro-beam has been divided into two triangular and rectangular sections and by computing the displacements along different directions and using the existing relations, the stiffness values for dagger cantilever have been obtained. In this paper, after investigating the stiffness of common types of cantilevers, Sobol sensitivity analyses of the effects of various geometric parameters on the stiffness of these types of cantilevers have been carried out. Also, the effects of different cantilevers on the dynamic behavior of nanoparticles have been studied and the dagger-shaped cantilever has been deemed more suitable for the manipulation of biological particles.

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

Modeling Acequia Irrigation Systems Using System Dynamics: Model Development, Evaluation, and Sensitivity Analyses to Investigate Effects of Socio-Economic and Biophysical Feedbacks

Directory of Open Access Journals (Sweden)

Benjamin L. Turner

2016-10-01

Full Text Available Agriculture-based irrigation communities of northern New Mexico have survived for centuries despite the arid environment in which they reside. These irrigation communities are threatened by regional population growth, urbanization, a changing demographic profile, economic development, climate change, and other factors. Within this context, we investigated the extent to which community resource management practices centering on shared resources (e.g., water for agricultural in the floodplains and grazing resources in the uplands and mutualism (i.e., shared responsibility of local residents to maintaining traditional irrigation policies and upholding cultural and spiritual observances embedded within the community structure influence acequia function. We used a system dynamics modeling approach as an interdisciplinary platform to integrate these systems, specifically the relationship between community structure and resource management. In this paper we describe the background and context of acequia communities in northern New Mexico and the challenges they face. We formulate a Dynamic Hypothesis capturing the endogenous feedbacks driving acequia community vitality. Development of the model centered on major stock-and-flow components, including linkages for hydrology, ecology, community, and economics. Calibration metrics were used for model evaluation, including statistical correlation of observed and predicted values and Theil inequality statistics. Results indicated that the model reproduced trends exhibited by the observed system. Sensitivity analyses of socio-cultural processes identified absentee decisions, cumulative income effect on time in agriculture, and land use preference due to time allocation, community demographic effect, effect of employment on participation, and farm size effect as key determinants of system behavior and response. Sensitivity analyses of biophysical parameters revealed that several key parameters (e.g., acres per

Using uncertainty and sensitivity analyses in socioecological agent-based models to improve their analytical performance and policy relevance.

Science.gov (United States)

Ligmann-Zielinska, Arika; Kramer, Daniel B; Spence Cheruvelil, Kendra; Soranno, Patricia A

2014-01-01

Agent-based models (ABMs) have been widely used to study socioecological systems. They are useful for studying such systems because of their ability to incorporate micro-level behaviors among interacting agents, and to understand emergent phenomena due to these interactions. However, ABMs are inherently stochastic and require proper handling of uncertainty. We propose a simulation framework based on quantitative uncertainty and sensitivity analyses to build parsimonious ABMs that serve two purposes: exploration of the outcome space to simulate low-probability but high-consequence events that may have significant policy implications, and explanation of model behavior to describe the system with higher accuracy. The proposed framework is applied to the problem of modeling farmland conservation resulting in land use change. We employ output variance decomposition based on quasi-random sampling of the input space and perform three computational experiments. First, we perform uncertainty analysis to improve model legitimacy, where the distribution of results informs us about the expected value that can be validated against independent data, and provides information on the variance around this mean as well as the extreme results. In our last two computational experiments, we employ sensitivity analysis to produce two simpler versions of the ABM. First, input space is reduced only to inputs that produced the variance of the initial ABM, resulting in a model with output distribution similar to the initial model. Second, we refine the value of the most influential input, producing a model that maintains the mean of the output of initial ABM but with less spread. These simplifications can be used to 1) efficiently explore model outcomes, including outliers that may be important considerations in the design of robust policies, and 2) conduct explanatory analysis that exposes the smallest number of inputs influencing the steady state of the modeled system.

Using uncertainty and sensitivity analyses in socioecological agent-based models to improve their analytical performance and policy relevance.

Directory of Open Access Journals (Sweden)

Arika Ligmann-Zielinska

Full Text Available Agent-based models (ABMs have been widely used to study socioecological systems. They are useful for studying such systems because of their ability to incorporate micro-level behaviors among interacting agents, and to understand emergent phenomena due to these interactions. However, ABMs are inherently stochastic and require proper handling of uncertainty. We propose a simulation framework based on quantitative uncertainty and sensitivity analyses to build parsimonious ABMs that serve two purposes: exploration of the outcome space to simulate low-probability but high-consequence events that may have significant policy implications, and explanation of model behavior to describe the system with higher accuracy. The proposed framework is applied to the problem of modeling farmland conservation resulting in land use change. We employ output variance decomposition based on quasi-random sampling of the input space and perform three computational experiments. First, we perform uncertainty analysis to improve model legitimacy, where the distribution of results informs us about the expected value that can be validated against independent data, and provides information on the variance around this mean as well as the extreme results. In our last two computational experiments, we employ sensitivity analysis to produce two simpler versions of the ABM. First, input space is reduced only to inputs that produced the variance of the initial ABM, resulting in a model with output distribution similar to the initial model. Second, we refine the value of the most influential input, producing a model that maintains the mean of the output of initial ABM but with less spread. These simplifications can be used to 1 efficiently explore model outcomes, including outliers that may be important considerations in the design of robust policies, and 2 conduct explanatory analysis that exposes the smallest number of inputs influencing the steady state of the modeled system.

Sensitivity of surface meteorological analyses to observation networks

Science.gov (United States)

Tyndall, Daniel Paul

A computationally efficient variational analysis system for two-dimensional meteorological fields is developed and described. This analysis approach is most efficient when the number of analysis grid points is much larger than the number of available observations, such as for large domain mesoscale analyses. The analysis system is developed using MATLAB software and can take advantage of multiple processors or processor cores. A version of the analysis system has been exported as a platform independent application (i.e., can be run on Windows, Linux, or Macintosh OS X desktop computers without a MATLAB license) with input/output operations handled by commonly available internet software combined with data archives at the University of Utah. The impact of observation networks on the meteorological analyses is assessed by utilizing a percentile ranking of individual observation sensitivity and impact, which is computed by using the adjoint of the variational surface assimilation system. This methodology is demonstrated using a case study of the analysis from 1400 UTC 27 October 2010 over the entire contiguous United States domain. The sensitivity of this approach to the dependence of the background error covariance on observation density is examined. Observation sensitivity and impact provide insight on the influence of observations from heterogeneous observing networks as well as serve as objective metrics for quality control procedures that may help to identify stations with significant siting, reporting, or representativeness issues.

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)

Synthesis of Trigeneration Systems: Sensitivity Analyses and Resilience

Directory of Open Access Journals (Sweden)

Monica Carvalho

2013-01-01

Full Text Available This paper presents sensitivity and resilience analyses for a trigeneration system designed for a hospital. The following information is utilized to formulate an integer linear programming model: (1 energy service demands of the hospital, (2 technical and economical characteristics of the potential technologies for installation, (3 prices of the available utilities interchanged, and (4 financial parameters of the project. The solution of the model, minimizing the annual total cost, provides the optimal configuration of the system (technologies installed and number of pieces of equipment and the optimal operation mode (operational load of equipment, interchange of utilities with the environment, convenience of wasting cogenerated heat, etc. at each temporal interval defining the demand. The broad range of technical, economic, and institutional uncertainties throughout the life cycle of energy supply systems for buildings makes it necessary to delve more deeply into the fundamental properties of resilient systems: feasibility, flexibility and robustness. The resilience of the obtained solution is tested by varying, within reasonable limits, selected parameters: energy demand, amortization and maintenance factor, natural gas price, self-consumption of electricity, and time-of-delivery feed-in tariffs.

VIPRE modeling of VVER-1000 reactor core for DNB analyses

Energy Technology Data Exchange (ETDEWEB)

Sung, Y.; Nguyen, Q. [Westinghouse Electric Corporation, Pittsburgh, PA (United States); Cizek, J. [Nuclear Research Institute, Prague, (Czech Republic)

1995-09-01

Based on the one-pass modeling approach, the hot channels and the VVER-1000 reactor core can be modeled in 30 channels for DNB analyses using the VIPRE-01/MOD02 (VIPRE) code (VIPRE is owned by Electric Power Research Institute, Palo Alto, California). The VIPRE one-pass model does not compromise any accuracy in the hot channel local fluid conditions. Extensive qualifications include sensitivity studies of radial noding and crossflow parameters and comparisons with the results from THINC and CALOPEA subchannel codes. The qualifications confirm that the VIPRE code with the Westinghouse modeling method provides good computational performance and accuracy for VVER-1000 DNB analyses.

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

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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.

On the use of uncertainty analyses to test hypotheses regarding deterministic model predictions of environmental processes

International Nuclear Information System (INIS)

Gilbert, R.O.; Bittner, E.A.; Essington, E.H.

1995-01-01

This paper illustrates the use of Monte Carlo parameter uncertainty and sensitivity analyses to test hypotheses regarding predictions of deterministic models of environmental transport, dose, risk and other phenomena. The methodology is illustrated by testing whether 238 Pu is transferred more readily than 239+240 Pu from the gastrointestinal (GI) tract of cattle to their tissues (muscle, liver and blood). This illustration is based on a study wherein beef-cattle grazed for up to 1064 days on a fenced plutonium (Pu)-contaminated arid site in Area 13 near the Nevada Test Site in the United States. Periodically, cattle were sacrificed and their tissues analyzed for Pu and other radionuclides. Conditional sensitivity analyses of the model predictions were also conducted. These analyses indicated that Pu cattle tissue concentrations had the largest impact of any model parameter on the pdf of predicted Pu fractional transfers. Issues that arise in conducting uncertainty and sensitivity analyses of deterministic models are discussed. (author)

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.

Extending and Applying Spartan to Perform Temporal Sensitivity Analyses for Predicting Changes in Influential Biological Pathways in Computational Models.

Science.gov (United States)

Alden, Kieran; Timmis, Jon; Andrews, Paul S; Veiga-Fernandes, Henrique; Coles, Mark

2017-01-01

Through integrating real time imaging, computational modelling, and statistical analysis approaches, previous work has suggested that the induction of and response to cell adhesion factors is the key initiating pathway in early lymphoid tissue development, in contrast to the previously accepted view that the process is triggered by chemokine mediated cell recruitment. These model derived hypotheses were developed using spartan, an open-source sensitivity analysis toolkit designed to establish and understand the relationship between a computational model and the biological system that model captures. Here, we extend the functionality available in spartan to permit the production of statistical analyses that contrast the behavior exhibited by a computational model at various simulated time-points, enabling a temporal analysis that could suggest whether the influence of biological mechanisms changes over time. We exemplify this extended functionality by using the computational model of lymphoid tissue development as a time-lapse tool. By generating results at twelve- hour intervals, we show how the extensions to spartan have been used to suggest that lymphoid tissue development could be biphasic, and predict the time-point when a switch in the influence of biological mechanisms might occur.

Sensitivity and uncertainty analyses in aging risk-based prioritizations

International Nuclear Information System (INIS)

Hassan, M.; Uryas'ev, S.; Vesely, W.E.

1993-01-01

Aging risk evaluations of nuclear power plants using Probabilistic Risk Analyses (PRAs) involve assessments of the impact of aging structures, systems, and components (SSCs) on plant core damage frequency (CDF). These assessments can be used to prioritize the contributors to aging risk reflecting the relative risk potential of the SSCs. Aging prioritizations are important for identifying the SSCs contributing most to plant risk and can provide a systematic basis on which aging risk control and management strategies for a plant can be developed. However, these prioritizations are subject to variabilities arising from uncertainties in data, and/or from various modeling assumptions. The objective of this paper is to present an evaluation of the sensitivity of aging prioritizations of active components to uncertainties in aging risk quantifications. Approaches for robust prioritization of SSCs also are presented which are less susceptible to the uncertainties

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)

Pre-waste-emplacement ground-water travel time sensitivity and uncertainty analyses for Yucca Mountain, Nevada

International Nuclear Information System (INIS)

Kaplan, P.G.

1993-01-01

Yucca Mountain, Nevada is a potential site for a high-level radioactive-waste repository. Uncertainty and sensitivity analyses were performed to estimate critical factors in the performance of the site with respect to a criterion in terms of pre-waste-emplacement ground-water travel time. The degree of failure in the analytical model to meet the criterion is sensitive to the estimate of fracture porosity in the upper welded unit of the problem domain. Fracture porosity is derived from a number of more fundamental measurements including fracture frequency, fracture orientation, and the moisture-retention characteristic inferred for the fracture domain

Sensitivity of the direct stop pair production analyses in phenomenological MSSM simplified models with the ATLAS detectors

CERN Document Server

Snyder, Ian Michael; The ATLAS collaboration

2018-01-01

The sensitivity of the searches for the direct pair production of stops often has been evaluated in simple SUSY scenarios, where only a limited set of supersymmetric particles take part to the stop decay. In this talk, the interpretations of the analyses requiring zero, one or two leptons in the final states to simple but well motivated MSSM scenarios will be discussed.

Sensitivity and uncertainty analyses of the HCLL mock-up experiment

International Nuclear Information System (INIS)

Leichtle, D.; Fischer, U.; Kodeli, I.; Perel, R.L.; Klix, A.; Batistoni, P.; Villari, R.

2010-01-01

Within the European Fusion Technology Programme dedicated computational methods, tools and data have been developed and validated for sensitivity and uncertainty analyses of fusion neutronics experiments. The present paper is devoted to this kind of analyses on the recent neutronics experiment on a mock-up of the Helium-Cooled Lithium Lead Test Blanket Module for ITER at the Frascati neutron generator. They comprise both probabilistic and deterministic methodologies for the assessment of uncertainties of nuclear responses due to nuclear data uncertainties and their sensitivities to the involved reaction cross-section data. We have used MCNP and MCSEN codes in the Monte Carlo approach and DORT and SUSD3D in the deterministic approach for transport and sensitivity calculations, respectively. In both cases JEFF-3.1 and FENDL-2.1 libraries for the transport data and mainly ENDF/B-VI.8 and SCALE6.0 libraries for the relevant covariance data have been used. With a few exceptions, the two different methodological approaches were shown to provide consistent results. A total nuclear data related uncertainty in the range of 1-2% (1σ confidence level) was assessed for the tritium production in the HCLL mock-up experiment.

Sensitivity analyses of the peach bottom turbine trip 2 experiment

International Nuclear Information System (INIS)

Bousbia Salah, A.; D'Auria, F.

2003-01-01

In the light of the sustained development in computer technology, the possibilities for code calculations in predicting more realistic transient scenarios in nuclear power plants have been enlarged substantially. Therefore, it becomes feasible to perform 'Best-estimate' simulations through the incorporation of three-dimensional modeling of reactor core into system codes. This method is particularly suited for complex transients that involve strong feedback effects between thermal-hydraulics and kinetics as well as to transient involving local asymmetric effects. The Peach bottom turbine trip test is characterized by a prompt core power excursion followed by a self limiting power behavior. To emphasize and understand the feedback mechanisms involved during this transient, a series of sensitivity analyses were carried out. This should allow the characterization of discrepancies between measured and calculated trends and assess the impact of the thermal-hydraulic and kinetic response of the used models. On the whole, the data comparison revealed a close dependency of the power excursion with the core feedback mechanisms. Thus for a better best estimate simulation of the transient, both of the thermal-hydraulic and the kinetic models should be made more accurate. (author)

Sensitivities and uncertainties of modeled ground temperatures in mountain environments

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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

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

Robust artificial neural network for reliability and sensitivity analyses of complex non-linear systems.

Science.gov (United States)

Oparaji, Uchenna; Sheu, Rong-Jiun; Bankhead, Mark; Austin, Jonathan; Patelli, Edoardo

2017-12-01

Artificial Neural Networks (ANNs) are commonly used in place of expensive models to reduce the computational burden required for uncertainty quantification, reliability and sensitivity analyses. ANN with selected architecture is trained with the back-propagation algorithm from few data representatives of the input/output relationship of the underlying model of interest. However, different performing ANNs might be obtained with the same training data as a result of the random initialization of the weight parameters in each of the network, leading to an uncertainty in selecting the best performing ANN. On the other hand, using cross-validation to select the best performing ANN based on the ANN with the highest R 2 value can lead to biassing in the prediction. This is as a result of the fact that the use of R 2 cannot determine if the prediction made by ANN is biased. Additionally, R 2 does not indicate if a model is adequate, as it is possible to have a low R 2 for a good model and a high R 2 for a bad model. Hence, in this paper, we propose an approach to improve the robustness of a prediction made by ANN. The approach is based on a systematic combination of identical trained ANNs, by coupling the Bayesian framework and model averaging. Additionally, the uncertainties of the robust prediction derived from the approach are quantified in terms of confidence intervals. To demonstrate the applicability of the proposed approach, two synthetic numerical examples are presented. Finally, the proposed approach is used to perform a reliability and sensitivity analyses on a process simulation model of a UK nuclear effluent treatment plant developed by National Nuclear Laboratory (NNL) and treated in this study as a black-box employing a set of training data as a test case. This model has been extensively validated against plant and experimental data and used to support the UK effluent discharge strategy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Probabilistic and Nonprobabilistic Sensitivity Analyses of Uncertain Parameters

Directory of Open Access Journals (Sweden)

Sheng-En Fang

2014-01-01

Full Text Available Parameter sensitivity analyses have been widely applied to industrial problems for evaluating parameter significance, effects on responses, uncertainty influence, and so forth. In the interest of simple implementation and computational efficiency, this study has developed two sensitivity analysis methods corresponding to the situations with or without sufficient probability information. The probabilistic method is established with the aid of the stochastic response surface and the mathematical derivation proves that the coefficients of first-order items embody the parameter main effects on the response. Simultaneously, a nonprobabilistic interval analysis based method is brought forward for the circumstance when the parameter probability distributions are unknown. The two methods have been verified against a numerical beam example with their accuracy compared to that of a traditional variance-based method. The analysis results have demonstrated the reliability and accuracy of the developed methods. And their suitability for different situations has also been discussed.

Global sensitivity analysis of thermomechanical models in modelling of welding; Analyse de sensibilite globale de modeles thermomecanique de simulation numerique du soudage

Energy Technology Data Exchange (ETDEWEB)

Petelet, M

2008-07-01

Current approach of most welding modellers is to content themselves with available material data, and to chose a mechanical model that seems to be appropriate. Among inputs, those controlling the material properties are one of the key problems of welding simulation: material data are never characterized over a sufficiently wide temperature range. This way to proceed neglect the influence of the uncertainty of input data on the result given by the computer code. In this case, how to assess the credibility of prediction? This thesis represents a step in the direction of implementing an innovative approach in welding simulation in order to bring answers to this question, with an illustration on some concretes welding cases.The global sensitivity analysis is chosen to determine which material properties are the most sensitive in a numerical welding simulation and in which range of temperature. Using this methodology require some developments to sample and explore the input space covering welding of different steel materials. Finally, input data have been divided in two groups according to their influence on the output of the model (residual stress or distortion). In this work, complete methodology of the global sensitivity analysis has been successfully applied to welding simulation and lead to reduce the input space to the only important variables. Sensitivity analysis has provided answers to what can be considered as one of the probable frequently asked questions regarding welding simulation: for a given material which properties must be measured with a good accuracy and which ones can be simply extrapolated or taken from a similar material? (author)

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

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.

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.

Long-term gas and brine migration at the Waste Isolation Pilot Plant: Preliminary sensitivity analyses for post-closure 40 CFR 268 (RCRA), May 1992

International Nuclear Information System (INIS)

1992-12-01

This report describes preliminary probabilistic sensitivity analyses of long term gas and brine migration at the Waste Isolation Pilot Plant (WIPP). Because gas and brine are potential transport media for organic compounds and heavy metals, understanding two-phase flow in the repository and the surrounding Salado Formation is essential to evaluating long-term compliance with 40 CFR 268.6, which is the portion of the Land Disposal Restrictions of the Hazardous and Solid Waste Amendments to the Resource Conservation and Recovery Act that states the conditions for disposal of specified hazardous wastes. Calculations described here are designed to provide guidance to the WIPP Project by identifying important parameters and helping to recognize processes not yet modeled that may affect compliance. Based on these analyses, performance is sensitive to shaft-seal permeabilities, parameters affecting gas generation, and the conceptual model used for the disturbed rock zone surrounding the excavation. Brine migration is less likely to affect compliance with 40 CFR 268.6 than gas migration. However, results are preliminary, and additional iterations of uncertainty and sensitivity analyses will be required to provide the confidence needed for a defensible compliance evaluation. Specifically, subsequent analyses will explicitly include effects of salt creep and, when conceptual and computational models are available, pressure-dependent fracturing of anhydrite marker beds

Stochastic methods for the quantification of sensitivities and uncertainties in criticality analyses; Stochastische Methoden zur Quantifizierung von Sensitivitaeten und Unsicherheiten in Kritikalitaetsanalysen

Energy Technology Data Exchange (ETDEWEB)

Behler, Matthias; Bock, Matthias; Stuke, Maik; Wagner, Markus

2014-06-15

This work describes statistical analyses based on Monte Carlo sampling methods for criticality safety analyses. The methods analyse a large number of calculations of a given problem with statistically varied model parameters to determine uncertainties and sensitivities of the computed results. The GRS development SUnCISTT (Sensitivities and Uncertainties in Criticality Inventory and Source Term Tool) is a modular, easily extensible abstract interface program, designed to perform such Monte Carlo sampling based uncertainty and sensitivity analyses in the field of criticality safety. It couples different criticality and depletion codes commonly used in nuclear criticality safety assessments to the well-established GRS tool SUSA for sensitivity and uncertainty analyses. For uncertainty analyses of criticality calculations, SunCISTT couples various SCALE sequences developed at Oak Ridge National Laboratory and the general Monte Carlo N-particle transport code MCNP from Los Alamos National Laboratory to SUSA. The impact of manufacturing tolerances of a fuel assembly configuration on the neutron multiplication factor for the various sequences is shown. Uncertainties in nuclear inventories, dose rates, or decay heat can be investigated via the coupling of the GRS depletion system OREST to SUSA. Some results for a simplified irradiated Pressurized Water Reactor (PWR) UO{sub 2} fuel assembly are shown. SUnCISTT also combines the two aforementioned modules for burnup credit criticality analysis of spent nuclear fuel to ensures an uncertainty and sensitivity analysis using the variations of manufacturing tolerances in the burn-up code and criticality code simultaneously. Calculations and results for a storage cask loaded with typical irradiated PWR UO{sub 2} fuel are shown, including Monte Carlo sampled axial burn-up profiles. The application of SUnCISTT in the field of code validation, specifically, how it is applied to compare a simulation model to available benchmark

Global sensitivity analysis of thermo-mechanical models in numerical weld modelling; Analyse de sensibilite globale de modeles thermomecaniques de simulation numerique du soudage

Energy Technology Data Exchange (ETDEWEB)

Petelet, M

2007-10-15

Current approach of most welding modellers is to content themselves with available material data, and to chose a mechanical model that seems to be appropriate. Among inputs, those controlling the material properties are one of the key problems of welding simulation: material data are never characterized over a sufficiently wide temperature range {exclamation_point} This way to proceed neglect the influence of the uncertainty of input data on the result given by the computer code. In this case, how to assess the credibility of prediction? This thesis represents a step in the direction of implementing an innovative approach in welding simulation in order to bring answers to this question, with an illustration on some concretes welding cases. The global sensitivity analysis is chosen to determine which material properties are the most sensitive in a numerical welding simulation and in which range of temperature. Using this methodology require some developments to sample and explore the input space covering welding of different steel materials. Finally, input data have been divided in two groups according to their influence on the output of the model (residual stress or distortion). In this work, complete methodology of the global sensitivity analysis has been successfully applied to welding simulation and lead to reduce the input space to the only important variables. Sensitivity analysis has provided answers to what can be considered as one of the probable frequently asked questions regarding welding simulation: for a given material which properties must be measured with a good accuracy and which ones can be simply extrapolated or taken from a similar material? (author)

Hospital Standardized Mortality Ratios: Sensitivity Analyses on the Impact of Coding

Science.gov (United States)

Bottle, Alex; Jarman, Brian; Aylin, Paul

2011-01-01

Introduction Hospital standardized mortality ratios (HSMRs) are derived from administrative databases and cover 80 percent of in-hospital deaths with adjustment for available case mix variables. They have been criticized for being sensitive to issues such as clinical coding but on the basis of limited quantitative evidence. Methods In a set of sensitivity analyses, we compared regular HSMRs with HSMRs resulting from a variety of changes, such as a patient-based measure, not adjusting for comorbidity, not adjusting for palliative care, excluding unplanned zero-day stays ending in live discharge, and using more or fewer diagnoses. Results Overall, regular and variant HSMRs were highly correlated (ρ > 0.8), but differences of up to 10 points were common. Two hospitals were particularly affected when palliative care was excluded from the risk models. Excluding unplanned stays ending in same-day live discharge had the least impact despite their high frequency. The largest impacts were seen when capturing postdischarge deaths and using just five high-mortality diagnosis groups. Conclusions HSMRs in most hospitals changed by only small amounts from the various adjustment methods tried here, though small-to-medium changes were not uncommon. However, the position relative to funnel plot control limits could move in a significant minority even with modest changes in the HSMR. PMID:21790587

Safety and sensitivity analyses of a generic geologic disposal system for high-level radioactive waste

International Nuclear Information System (INIS)

Kimura, Hideo; Takahashi, Tomoyuki; Shima, Shigeki; Matsuzuru, Hideo

1994-11-01

This report describes safety and sensitivity analyses of a generic geologic disposal system for HLW, using a GSRW code and an automated sensitivity analysis methodology based on the Differential Algebra. An exposure scenario considered here is based on a normal evolution scenario which excludes events attributable to probabilistic alterations in the environment. The results of sensitivity analyses indicate that parameters related to a homogeneous rock surrounding a disposal facility have higher sensitivities to the output analyzed here than those of a fractured zone and engineered barriers. The sensitivity analysis methodology provides technical information which might be bases for the optimization of design of the disposal facility. Safety analyses were performed on the reference disposal system which involve HLW in amounts corresponding to 16,000 MTU of spent fuels. The individual dose equivalent due to the exposure pathway ingesting drinking water was calculated using both the conservative and realistic values of geochemical parameters. In both cases, the committed dose equivalent evaluated here is the order of 10 -7 Sv, and thus geologic disposal of HLW may be feasible if the disposal conditions assumed here remain unchanged throughout the periods assessed here. (author)

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.

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...

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.

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

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

Global analyses of historical masonry buildings: Equivalent frame vs. 3D solid models

Science.gov (United States)

Clementi, Francesco; Mezzapelle, Pardo Antonio; Cocchi, Gianmichele; Lenci, Stefano

2017-07-01

The paper analyses the seismic vulnerability of two different masonry buildings. It provides both an advanced 3D modelling with solid elements and an equivalent frame modelling. The global structural behaviour and the dynamic properties of the compound have been evaluated using the Finite Element Modelling (FEM) technique, where the nonlinear behaviour of masonry has been taken into account by proper constitutive assumptions. A sensitivity analysis is done to evaluate the effect of the choice of the structural models.

Sensitivity and uncertainty analysis

CERN Document Server

Cacuci, Dan G; Navon, Ionel Michael

2005-01-01

As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable scientific tools. Sensitivity and Uncertainty Analysis. Volume I: Theory focused on the mathematical underpinnings of two important methods for such analyses: the Adjoint Sensitivity Analysis Procedure and the Global Adjoint Sensitivity Analysis Procedure. This volume concentrates on the practical aspects of performing these analyses for large-scale systems. The applications addressed include two-phase flow problems, a radiative c

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)

msgbsR: An R package for analysing methylation-sensitive restriction enzyme sequencing data.

Science.gov (United States)

Mayne, Benjamin T; Leemaqz, Shalem Y; Buckberry, Sam; Rodriguez Lopez, Carlos M; Roberts, Claire T; Bianco-Miotto, Tina; Breen, James

2018-02-01

Genotyping-by-sequencing (GBS) or restriction-site associated DNA marker sequencing (RAD-seq) is a practical and cost-effective method for analysing large genomes from high diversity species. This method of sequencing, coupled with methylation-sensitive enzymes (often referred to as methylation-sensitive restriction enzyme sequencing or MRE-seq), is an effective tool to study DNA methylation in parts of the genome that are inaccessible in other sequencing techniques or are not annotated in microarray technologies. Current software tools do not fulfil all methylation-sensitive restriction sequencing assays for determining differences in DNA methylation between samples. To fill this computational need, we present msgbsR, an R package that contains tools for the analysis of methylation-sensitive restriction enzyme sequencing experiments. msgbsR can be used to identify and quantify read counts at methylated sites directly from alignment files (BAM files) and enables verification of restriction enzyme cut sites with the correct recognition sequence of the individual enzyme. In addition, msgbsR assesses DNA methylation based on read coverage, similar to RNA sequencing experiments, rather than methylation proportion and is a useful tool in analysing differential methylation on large populations. The package is fully documented and available freely online as a Bioconductor package ( https://bioconductor.org/packages/release/bioc/html/msgbsR.html ).

Analysis of Sensitivity and Uncertainty in an Individual-Based Model of a Threatened Wildlife Species

Science.gov (United States)

We present a multi-faceted sensitivity analysis of a spatially explicit, individual-based model (IBM) (HexSim) of a threatened species, the Northern Spotted Owl (Strix occidentalis caurina) on a national forest in Washington, USA. Few sensitivity analyses have been conducted on ...

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.

Advanced surrogate model and sensitivity analysis methods for sodium fast reactor accident assessment

International Nuclear Information System (INIS)

Marrel, A.; Marie, N.; De Lozzo, M.

2015-01-01

Within the framework of the generation IV Sodium Fast Reactors, the safety in case of severe accidents is assessed. From this statement, CEA has developed a new physical tool to model the accident initiated by the Total Instantaneous Blockage (TIB) of a sub-assembly. This TIB simulator depends on many uncertain input parameters. This paper aims at proposing a global methodology combining several advanced statistical techniques in order to perform a global sensitivity analysis of this TIB simulator. The objective is to identify the most influential uncertain inputs for the various TIB outputs involved in the safety analysis. The proposed statistical methodology combining several advanced statistical techniques enables to take into account the constraints on the TIB simulator outputs (positivity constraints) and to deal simultaneously with various outputs. To do this, a space-filling design is used and the corresponding TIB model simulations are performed. Based on this learning sample, an efficient constrained Gaussian process metamodel is fitted on each TIB model outputs. Then, using the metamodels, classical sensitivity analyses are made for each TIB output. Multivariate global sensitivity analyses based on aggregated indices are also performed, providing additional valuable information. Main conclusions on the influence of each uncertain input are derived. - Highlights: • Physical-statistical tool for Sodium Fast Reactors TIB accident. • 27 uncertain parameters (core state, lack of physical knowledge) are highlighted. • Constrained Gaussian process efficiently predicts TIB outputs (safety criteria). • Multivariate sensitivity analyses reveal that three inputs are mainly influential. • The type of corium propagation (thermal or hydrodynamic) is the most influential

Sensitivity and uncertainty analyses applied to criticality safety validation. Volume 2

International Nuclear Information System (INIS)

Broadhead, B.L.; Hopper, C.M.; Parks, C.V.

1999-01-01

This report presents the application of sensitivity and uncertainty (S/U) analysis methodologies developed in Volume 1 to the code/data validation tasks of a criticality safety computational study. Sensitivity and uncertainty analysis methods were first developed for application to fast reactor studies in the 1970s. This work has revitalized and updated the existing S/U computational capabilities such that they can be used as prototypic modules of the SCALE code system, which contains criticality analysis tools currently in use by criticality safety practitioners. After complete development, simplified tools are expected to be released for general use. The methods for application of S/U and generalized linear-least-square methodology (GLLSM) tools to the criticality safety validation procedures were described in Volume 1 of this report. Volume 2 of this report presents the application of these procedures to the validation of criticality safety analyses supporting uranium operations where enrichments are greater than 5 wt %. Specifically, the traditional k eff trending analyses are compared with newly developed k eff trending procedures, utilizing the D and c k coefficients described in Volume 1. These newly developed procedures are applied to a family of postulated systems involving U(11)O 2 fuel, with H/X values ranging from 0--1,000. These analyses produced a series of guidance and recommendations for the general usage of these various techniques. Recommendations for future work are also detailed

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.)

Sensitivity Study of Poisson's Ratio Used in Soil Structure Interaction (SSI) Analyses

International Nuclear Information System (INIS)

Han, Seung-ju; You, Dong-Hyun; Jang, Jung-bum; Yun, Kwan-hee

2016-01-01

The preliminary review for Design Certification (DC) of APR1400 was accepted by NRC on March 4, 2015. After the acceptance of the application for standard DC of APR1400, KHNP has responded the Request for Additional Information (RAI) raised by NRC to undertake a full design certification review. Design certification is achieved through the NRC's rulemaking process, and is founded on the staff's review of the application, which addresses the various safety issues associated with the proposed nuclear power plant design, independent of a specific site. The USNRC issued RAIs pertain to Design Control Document (DCD) Ch.3.7 'Seismic Design' is DCD Tables 3.7A-1 and 3.7A-2 show Poisson’s ratios in the S1 and S2 soil profiles used for SSI analysis as great as 0.47 and 0.48 respectively. Based on staff experience, use of Poisson's ratio approaching these values may result in numerical instability of the SSI analysis results. Sensitivity study is performed using the ACS SASSI NI model of APR1400 with S1 and S2 soil profiles to demonstrate that the Poisson’s ratio values used in the SSI analyses of S1 and S2 soil profile cases do not produce numerical instabilities in the SSI analysis results. No abrupt changes or spurious peaks, which tend to indicate existence of numerical sensitivities in the SASSI solutions, appear in the computed transfer functions of the original SSI analyses that have the maximum dynamic Poisson’s ratio values of 0.47 and 0.48 as well as in the re-computed transfer functions that have the maximum dynamic Poisson’s ratio values limited to 0.42 and 0.45

The Evaluation of Bivariate Mixed Models in Meta-analyses of Diagnostic Accuracy Studies with SAS, Stata and R.

Science.gov (United States)

Vogelgesang, Felicitas; Schlattmann, Peter; Dewey, Marc

2018-05-01

Meta-analyses require a thoroughly planned procedure to obtain unbiased overall estimates. From a statistical point of view not only model selection but also model implementation in the software affects the results. The present simulation study investigates the accuracy of different implementations of general and generalized bivariate mixed models in SAS (using proc mixed, proc glimmix and proc nlmixed), Stata (using gllamm, xtmelogit and midas) and R (using reitsma from package mada and glmer from package lme4). Both models incorporate the relationship between sensitivity and specificity - the two outcomes of interest in meta-analyses of diagnostic accuracy studies - utilizing random effects. Model performance is compared in nine meta-analytic scenarios reflecting the combination of three sizes for meta-analyses (89, 30 and 10 studies) with three pairs of sensitivity/specificity values (97%/87%; 85%/75%; 90%/93%). The evaluation of accuracy in terms of bias, standard error and mean squared error reveals that all implementations of the generalized bivariate model calculate sensitivity and specificity estimates with deviations less than two percentage points. proc mixed which together with reitsma implements the general bivariate mixed model proposed by Reitsma rather shows convergence problems. The random effect parameters are in general underestimated. This study shows that flexibility and simplicity of model specification together with convergence robustness should influence implementation recommendations, as the accuracy in terms of bias was acceptable in all implementations using the generalized approach. Schattauer GmbH.

Low-order modelling of shallow water equations for sensitivity analysis using proper orthogonal decomposition

Science.gov (United States)

Zokagoa, Jean-Marie; Soulaïmani, Azzeddine

2012-06-01

This article presents a reduced-order model (ROM) of the shallow water equations (SWEs) for use in sensitivity analyses and Monte-Carlo type applications. Since, in the real world, some of the physical parameters and initial conditions embedded in free-surface flow problems are difficult to calibrate accurately in practice, the results from numerical hydraulic models are almost always corrupted with uncertainties. The main objective of this work is to derive a ROM that ensures appreciable accuracy and a considerable acceleration in the calculations so that it can be used as a surrogate model for stochastic and sensitivity analyses in real free-surface flow problems. The ROM is derived using the proper orthogonal decomposition (POD) method coupled with Galerkin projections of the SWEs, which are discretised through a finite-volume method. The main difficulty of deriving an efficient ROM is the treatment of the nonlinearities involved in SWEs. Suitable approximations that provide rapid online computations of the nonlinear terms are proposed. The proposed ROM is applied to the simulation of hypothetical flood flows in the Bordeaux breakwater, a portion of the 'Rivière des Prairies' located near Laval (a suburb of Montreal, Quebec). A series of sensitivity analyses are performed by varying the Manning roughness coefficient and the inflow discharge. The results are satisfactorily compared to those obtained by the full-order finite volume model.

Contributions to sensitivity analysis and generalized discriminant analysis; Contributions a l'analyse de sensibilite et a l'analyse discriminante generalisee

Energy Technology Data Exchange (ETDEWEB)

Jacques, J

2005-12-15

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)

Sensitivity analyses of fast reactor systems including thorium and uranium

International Nuclear Information System (INIS)

Marable, J.H.; Weisbin, C.R.

1978-01-01

The Cross Section Evaluation Working Group (CSEWG) has, in conjunction with the development of the fifth version of ENDF/B, assembled new evaluations for 232 Th and 233 U. It is the purpose of this paper to describe briefly some of the more important features of these evaluations relative to ENDF/B-4 to project the change in reactor performance based upon the newer evaluated files and sensitivity coefficients for interesting design problems, and to indicate preliminary results from ongoing uncertainty analyses

Taxing CO2 and subsidising biomass: Analysed in a macroeconomic and sectoral model

DEFF Research Database (Denmark)

Klinge Jacobsen, Henrik

2000-01-01

This paper analyses the combination of taxes and subsidies as an instrument to enable a reduction in CO2 emission. The objective of the study is to compare recycling of a CO2 tax revenue as a subsidy for biomass use as opposed to traditional recycling such as reduced income or corporate taxation....... A model of Denmark's energy supply sector is used to analyse the e€ect of a CO2 tax combined with using the tax revenue for biomass subsidies. The energy supply model is linked to a macroeconomic model such that the macroeconomic consequences of tax policies can be analysed along with the consequences...... for speci®c sectors such as agriculture. Electricity and heat are produced at heat and power plants utilising fuels which minimise total fuel cost, while the authorities regulate capacity expansion technologies. The e€ect of fuel taxes and subsidies on fuels is very sensitive to the fuel substitution...

Parameter sensitivity and identifiability for a biogeochemical model of hypoxia in the northern Gulf of Mexico

Science.gov (United States)

Local sensitivity analyses and identifiable parameter subsets were used to describe numerical constraints of a hypoxia model for bottom waters of the northern Gulf of Mexico. The sensitivity of state variables differed considerably with parameter changes, although most variables ...

Demonstrating the efficiency of the EFPC criterion by means of Sensitivity analyses

International Nuclear Information System (INIS)

Munier, Raymond

2007-04-01

Within the framework of a project to characterise large fractures, a modelling effort was initiated to evaluate the use of a pair of full perimeter criteria, FPC and EFPC, for detecting fractures that could jeopardize the integrity of the canisters in the case of a large nearby earthquake. Though some sensitivity studies were performed in the method study of these mainly targeted aspects of Monte-Carlo simulations. The impact of uncertainties in the DFN model upon the efficiency of the FPI criteria was left unattended. The main purpose of this report is, therefore, to explore the impact of DFN variability upon the efficiency of the FPI criteria. The outcome of the present report may thus be regarded as complementary analyses to the ones presented in SKB-R-06-54. To appreciate the details of the present report, the reader should be acquainted with the simulation procedure described the earlier report. The most important conclusion of this study is that the efficiency of the EFPC is high for all tested model variants. That is, compared to blind deposition, the EFPC is a very powerful tool to identify unsuitable deposition holes and it is essentially insensitive to variations in the DFN Model. If information from adjacent tunnels is used in addition to EFPC, then the probability of detecting a critical deposition hole is almost 100%

Sensitivity analyses of seismic behavior of spent fuel dry cask storage systems

International Nuclear Information System (INIS)

Luk, V.K.; Spencer, B.W.; Shaukat, S.K.; Lam, I.P.; Dameron, R.A.

2003-01-01

Sandia National Laboratories is conducting a research project to develop a comprehensive methodology for evaluating the seismic behavior of spent fuel dry cask storage systems (DCSS) for the Office of Nuclear Regulatory Research of the U.S. Nuclear Regulatory Commission (NRC). A typical Independent Spent Fuel Storage Installation (ISFSI) consists of arrays of free-standing storage casks resting on concrete pads. In the safety review process of these cask systems, their seismically induced horizontal displacements and angular rotations must be quantified to determine whether casks will overturn or neighboring casks will collide during a seismic event. The ABAQUS/Explicit code is used to analyze three-dimensional coupled finite element models consisting of three submodels, which are a cylindrical cask or a rectangular module, a flexible concrete pad, and an underlying soil foundation. The coupled model includes two sets of contact surfaces between the submodels with prescribed coefficients of friction. The seismic event is described by one vertical and two horizontal components of statistically independent seismic acceleration time histories. A deconvolution procedure is used to adjust the amplitudes and frequency contents of these three-component reference surface motions before applying them simultaneously at the soil foundation base. The research project focused on examining the dynamic and nonlinear seismic behavior of the coupled model of free-standing DCSS including soil-structure interaction effects. This paper presents a subset of analysis results for a series of parametric analyses. Input variables in the parametric analyses include: designs of the cask/module, time histories of the seismic accelerations, coefficients of friction at the cask/pad interface, and material properties of the soil foundation. In subsequent research, the analysis results will be compiled and presented in nomograms to highlight the sensitivity of seismic response of DCSS to

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.

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.

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.

Beware the black box: investigating the sensitivity of FEA simulations to modelling factors in comparative biomechanics

Directory of Open Access Journals (Sweden)

Christopher W. Walmsley

2013-11-01

Full Text Available Finite element analysis (FEA is a computational technique of growing popularity in the field of comparative biomechanics, and is an easily accessible platform for form-function analyses of biological structures. However, its rapid evolution in recent years from a novel approach to common practice demands some scrutiny in regards to the validity of results and the appropriateness of assumptions inherent in setting up simulations. Both validation and sensitivity analyses remain unexplored in many comparative analyses, and assumptions considered to be ‘reasonable’ are often assumed to have little influence on the results and their interpretation.Here we report an extensive sensitivity analysis where high resolution finite element (FE models of mandibles from seven species of crocodile were analysed under loads typical for comparative analysis: biting, shaking, and twisting. Simulations explored the effect on both the absolute response and the interspecies pattern of results to variations in commonly used input parameters. Our sensitivity analysis focuses on assumptions relating to the selection of material properties (heterogeneous or homogeneous, scaling (standardising volume, surface area, or length, tooth position (front, mid, or back tooth engagement, and linear load case (type of loading for each feeding type.Our findings show that in a comparative context, FE models are far less sensitive to the selection of material property values and scaling to either volume or surface area than they are to those assumptions relating to the functional aspects of the simulation, such as tooth position and linear load case. Results show a complex interaction between simulation assumptions, depending on the combination of assumptions and the overall shape of each specimen. Keeping assumptions consistent between models in an analysis does not ensure that results can be generalised beyond the specific set of assumptions used. Logically, different

Towards an Industrial Application of Statistical Uncertainty Analysis Methods to Multi-physical Modelling and Safety Analyses

International Nuclear Information System (INIS)

Zhang, Jinzhao; Segurado, Jacobo; Schneidesch, Christophe

2013-01-01

Since 1980's, Tractebel Engineering (TE) has being developed and applied a multi-physical modelling and safety analyses capability, based on a code package consisting of the best estimate 3D neutronic (PANTHER), system thermal hydraulic (RELAP5), core sub-channel thermal hydraulic (COBRA-3C), and fuel thermal mechanic (FRAPCON/FRAPTRAN) codes. A series of methodologies have been developed to perform and to license the reactor safety analysis and core reload design, based on the deterministic bounding approach. Following the recent trends in research and development as well as in industrial applications, TE has been working since 2010 towards the application of the statistical sensitivity and uncertainty analysis methods to the multi-physical modelling and licensing safety analyses. In this paper, the TE multi-physical modelling and safety analyses capability is first described, followed by the proposed TE best estimate plus statistical uncertainty analysis method (BESUAM). The chosen statistical sensitivity and uncertainty analysis methods (non-parametric order statistic method or bootstrap) and tool (DAKOTA) are then presented, followed by some preliminary results of their applications to FRAPCON/FRAPTRAN simulation of OECD RIA fuel rod codes benchmark and RELAP5/MOD3.3 simulation of THTF tests. (authors)

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.

Sensitivity studies for 3-D rod ejection analyses on axial power shape

Energy Technology Data Exchange (ETDEWEB)

Park, Min-Ho; Park, Jin-Woo; Park, Guen-Tae; Ryu, Seok-Hee; Um, Kil-Sup; Lee, Jae-Il [KEPCO NF, Daejeon (Korea, Republic of)

2015-10-15

The current safety analysis methodology using the point kinetics model combined with numerous conservative assumptions result in unrealistic prediction of the transient behavior wasting huge margin for safety analyses while the safety regulation criteria for the reactivity initiated accident are going strict. To deal with this, KNF is developing a 3-D rod ejection analysis methodology using the multi-dimensional code coupling system CHASER. The CHASER system couples three-dimensional core neutron kinetics code ASTRA, sub-channel analysis code THALES, and fuel performance analysis code FROST using message passing interface (MPI). A sensitivity study for 3-D rod ejection analysis on axial power shape (APS) is carried out to survey the tendency of safety parameters by power distributions and to build up a realistic safety analysis methodology while maintaining conservatism. The currently developing 3-D rod ejection analysis methodology using the multi-dimensional core transient analysis code system, CHASER was shown to reasonably reflect the conservative assumptions by tuning up kinetic parameters.

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.

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

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).

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...

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

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.

Demographic origins of skewed operational and adult sex ratios: perturbation analyses of two-sex models.

Science.gov (United States)

Veran, Sophie; Beissinger, Steven R

2009-02-01

Skewed sex ratios - operational (OSR) and Adult (ASR) - arise from sexual differences in reproductive behaviours and adult survival rates due to the cost of reproduction. However, skewed sex-ratio at birth, sex-biased dispersal and immigration, and sexual differences in juvenile mortality may also contribute. We present a framework to decompose the roles of demographic traits on sex ratios using perturbation analyses of two-sex matrix population models. Metrics of sensitivity are derived from analyses of sensitivity, elasticity, life-table response experiments and life stage simulation analyses, and applied to the stable stage distribution instead of lambda. We use these approaches to examine causes of male-biased sex ratios in two populations of green-rumped parrotlets (Forpus passerinus) in Venezuela. Female local juvenile survival contributed the most to the unbalanced OSR and ASR due to a female-biased dispersal rate, suggesting sexual differences in philopatry can influence sex ratios more strongly than the cost of reproduction.

Contributions to sensitivity analysis and generalized discriminant analysis; Contributions a l'analyse de sensibilite et a l'analyse discriminante generalisee

Energy Technology Data Exchange (ETDEWEB)

Jacques, J

2005-12-15

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)

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

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.

Response surfaces and sensitivity analyses for an environmental model of dose calculations

Energy Technology Data Exchange (ETDEWEB)

Iooss, Bertrand [CEA Cadarache, DEN/DER/SESI/LCFR, 13108 Saint Paul lez Durance, Cedex (France)]. E-mail: bertrand.iooss@cea.fr; Van Dorpe, Francois [CEA Cadarache, DEN/DTN/SMTM/LMTE, 13108 Saint Paul lez Durance, Cedex (France); Devictor, Nicolas [CEA Cadarache, DEN/DER/SESI/LCFR, 13108 Saint Paul lez Durance, Cedex (France)

2006-10-15

A parametric sensitivity analysis is carried out on GASCON, a radiological impact software describing the radionuclides transfer to the man following a chronic gas release of a nuclear facility. An effective dose received by age group can thus be calculated according to a specific radionuclide and to the duration of the release. In this study, we are concerned by 18 output variables, each depending of approximately 50 uncertain input parameters. First, the generation of 1000 Monte-Carlo simulations allows us to calculate correlation coefficients between input parameters and output variables, which give a first overview of important factors. Response surfaces are then constructed in polynomial form, and used to predict system responses at reduced computation time cost; this response surface will be very useful for global sensitivity analysis where thousands of runs are required. Using the response surfaces, we calculate the total sensitivity indices of Sobol by the Monte-Carlo method. We demonstrate the application of this method to one site of study and to one reference group near the nuclear research Center of Cadarache (France), for two radionuclides: iodine 129 and uranium 238. It is thus shown that the most influential parameters are all related to the food chain of the goat's milk, in decreasing order of importance: dose coefficient 'effective ingestion', goat's milk ration of the individuals of the reference group, grass ration of the goat, dry deposition velocity and transfer factor to the goat's milk.

Uncertainty and sensitivity analyses of ballast life-cycle cost and payback period

OpenAIRE

Mcmahon, James E.

2000-01-01

The paper introduces an innovative methology for evaluating the relative significance of energy-efficient technologies applied to fluorescent lamp ballasts. The method involves replacing the point estimates of life cycle cost of the ballasts with uncertainty distributions reflecting the whole spectrum of possible costs, and the assessed probability associated with each value. The results of uncertainty and sensitivity analyses will help analysts reduce effort in data collection and carry on a...

Sensitivity analyses for simulating pesticide impacts on honey bee colonies

Science.gov (United States)

We employ Monte Carlo simulation and sensitivity analysis techniques to describe the population dynamics of pesticide exposure to a honey bee colony using the VarroaPop + Pesticide model. Simulations are performed of hive population trajectories with and without pesti...

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...

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 ...

Preliminary performance assessment for the Waste Isolation Pilot Plant, December 1992. Volume 5, Uncertainty and sensitivity analyses of gas and brine migration for undisturbed performance

Energy Technology Data Exchange (ETDEWEB)

1993-08-01

Before disposing of transuranic radioactive waste in the Waste Isolation Pilot Plant (WIPP), the United States Department of Energy (DOE) must evaluate compliance with applicable long-term regulations of the United States Environmental Protection Agency (EPA). Sandia National Laboratories is conducting iterative performance assessments (PAs) of the WIPP for the DOE to provide interim guidance while preparing for a final compliance evaluation. This volume of the 1992 PA contains results of uncertainty and sensitivity analyses with respect to migration of gas and brine from the undisturbed repository. Additional information about the 1992 PA is provided in other volumes. Volume 1 contains an overview of WIPP PA and results of a preliminary comparison with 40 CFR 191, Subpart B. Volume 2 describes the technical basis for the performance assessment, including descriptions of the linked computational models used in the Monte Carlo analyses. Volume 3 contains the reference data base and values for input parameters used in consequence and probability modeling. Volume 4 contains uncertainty and sensitivity analyses with respect to the EPA`s Environmental Standards for the Management and Disposal of Spent Nuclear Fuel, High-Level and Transuranic Radioactive Wastes (40 CFR 191, Subpart B). Finally, guidance derived from the entire 1992 PA is presented in Volume 6. Results of the 1992 uncertainty and sensitivity analyses indicate that, conditional on the modeling assumptions and the assigned parameter-value distributions, the most important parameters for which uncertainty has the potential to affect gas and brine migration from the undisturbed repository are: initial liquid saturation in the waste, anhydrite permeability, biodegradation-reaction stoichiometry, gas-generation rates for both corrosion and biodegradation under inundated conditions, and the permeability of the long-term shaft seal.

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.

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.

The Svalbard intertidal zone: a concept for the use of GIS in applied oil sensitivity, vulnerability and impact analyses

International Nuclear Information System (INIS)

Moe, K.A.; Skeie, G.M.; Brude, O.W.; Loevas, S.M.; Nedreboes, M.; Weslawski, J.M.

2000-01-01

Historical oil spills have shown that environmental damage on the seashore can be measured by acute mortality of single species and destabilisation of the communities. The biota, however, has the potential to recover over some period of time. Applied to the understanding of the fate of oil and population and community dynamics, the impact can be described by the function of the following two factors: the immediate extent and the duration of damage. A simple and robust mathematical model is developed to describe this process in the Svalbard intertidal. Based on the integral of key biological and physical factors, i.e., community specific sensitivity, oil accumulation and retention capacity of the substrate, ice-cover and wave exposure, the model is implemented by a Geographical Information System (GIS) for characterisation of the habitat's sensitivity and vulnerability. Geomorphologic maps and georeferenced biological data are used as input. Digital maps of intertidal zone are compiled, indicating the shoreline sensitivity and vulnerability in terms of coastal segments and grid aggregations. Selected results have been used in the national assessment programme of oil development in the Barents Sea for priorities in environmental impact assessments and risk analyses as well as oil spill contingency planning. (Author)

Marginal Utility of Conditional Sensitivity Analyses for Dynamic Models

Science.gov (United States)

Background/Question/MethodsDynamic ecological processes may be influenced by many factors. Simulation models thatmimic these processes often have complex implementations with many parameters. Sensitivityanalyses are subsequently used to identify critical parameters whose uncertai...

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.

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

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

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

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.

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.

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.

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.

Tests of methods and software for set-valued model calibration and sensitivity analyses

NARCIS (Netherlands)

Janssen PHM; Sanders R; CWM

1995-01-01

Testen worden besproken die zijn uitgevoerd op methoden en software voor calibratie middels 'rotated-random-scanning', en voor gevoeligheidsanalyse op basis van de 'dominant direction analysis' en de 'generalized sensitivity analysis'. Deze technieken werden

Greenhouse gas network design using backward Lagrangian particle dispersion modelling – Part 2: Sensitivity analyses and South African test case

CSIR Research Space (South Africa)

Nickless, A

2014-05-01

Full Text Available observation of atmospheric CO(sub2) concentrations at fixed monitoring stations. The LPDM model, which can be used to derive the sensitivity matrix used in an inversion, was run for each potential site for the months of July (representative of the Southern...

Sensitivity analyses of biodiesel thermo-physical properties under diesel engine conditions

DEFF Research Database (Denmark)

Cheng, Xinwei; Ng, Hoon Kiat; Gan, Suyin

2016-01-01

This reported work investigates the sensitivities of spray and soot developments to the change of thermo-physical properties for coconut and soybean methyl esters, using two-dimensional computational fluid dynamics fuel spray modelling. The choice of test fuels made was due to their contrasting s...

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

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.)

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.

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.

Parameterization and Sensitivity Analysis of a Complex Simulation Model for Mosquito Population Dynamics, Dengue Transmission, and Their Control

Science.gov (United States)

Ellis, Alicia M.; Garcia, Andres J.; Focks, Dana A.; Morrison, Amy C.; Scott, Thomas W.

2011-01-01

Models can be useful tools for understanding the dynamics and control of mosquito-borne disease. More detailed models may be more realistic and better suited for understanding local disease dynamics; however, evaluating model suitability, accuracy, and performance becomes increasingly difficult with greater model complexity. Sensitivity analysis is a technique that permits exploration of complex models by evaluating the sensitivity of the model to changes in parameters. Here, we present results of sensitivity analyses of two interrelated complex simulation models of mosquito population dynamics and dengue transmission. We found that dengue transmission may be influenced most by survival in each life stage of the mosquito, mosquito biting behavior, and duration of the infectious period in humans. The importance of these biological processes for vector-borne disease models and the overwhelming lack of knowledge about them make acquisition of relevant field data on these biological processes a top research priority. PMID:21813844

SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool.

Science.gov (United States)

Zi, Zhike; Zheng, Yanan; Rundell, Ann E; Klipp, Edda

2008-08-15

It has long been recognized that sensitivity analysis plays a key role in modeling and analyzing cellular and biochemical processes. Systems biology markup language (SBML) has become a well-known platform for coding and sharing mathematical models of such processes. However, current SBML compatible software tools are limited in their ability to perform global sensitivity analyses of these models. This work introduces a freely downloadable, software package, SBML-SAT, which implements algorithms for simulation, steady state analysis, robustness analysis and local and global sensitivity analysis for SBML models. This software tool extends current capabilities through its execution of global sensitivity analyses using multi-parametric sensitivity analysis, partial rank correlation coefficient, SOBOL's method, and weighted average of local sensitivity analyses in addition to its ability to handle systems with discontinuous events and intuitive graphical user interface. SBML-SAT provides the community of systems biologists a new tool for the analysis of their SBML models of biochemical and cellular processes.

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.

Uncertainty and sensitivity analyses of ballast life-cycle cost and payback period

Energy Technology Data Exchange (ETDEWEB)

McMahon, James E.; Liu, Xiaomin; Turiel, Ike; Hakim, Sajid; Fisher, Diane

2000-06-01

The paper introduces an innovative methodology for evaluating the relative significance of energy-efficient technologies applied to fluorescent lamp ballasts. The method involves replacing the point estimates of life cycle cost of the ballasts with uncertainty distributions reflecting the whole spectrum of possible costs, and the assessed probability associated with each value. The results of uncertainty and sensitivity analyses will help analysts reduce effort in data collection and carry on analysis more efficiently. These methods also enable policy makers to gain an insightful understanding of which efficient technology alternatives benefit or cost what fraction of consumers, given the explicit assumptions of the analysis.

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

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.

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.

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.

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.

SPES3 Facility RELAP5 Sensitivity Analyses on the Containment System for Design Review

International Nuclear Information System (INIS)

Achilli, A.; Congiu, C.; Ferri, R.; Bianchi, F.; Meloni, P.; Grgic, D.; Dzodzo, M.

2012-01-01

An Italian MSE R and D programme on Nuclear Fission is funding, through ENEA, the design and testing of SPES3 facility at SIET, for IRIS reactor simulation. IRIS is a modular, medium size, advanced, integral PWR, developed by an international consortium of utilities, industries, research centres and universities. SPES3 simulates the primary, secondary and containment systems of IRIS, with 1:100 volume scale, full elevation and prototypical thermal-hydraulic conditions. The RELAP5 code was extensively used in support to the design of the facility to identify criticalities and weak points in the reactor simulation. FER, at Zagreb University, performed the IRIS reactor analyses with the RELAP5 and GOTHIC coupled codes. The comparison between IRIS and SPES3 simulation results led to a simulation-design feedback process with step-by-step modifications of the facility design, up to the final configuration. For this, a series of sensitivity cases was run to investigate specific aspects affecting the trend of the main parameters of the plant, as the containment pressure and EHRS removed power, to limit fuel clad temperature excursions during accidental transients. This paper summarizes the sensitivity analyses on the containment system that allowed to review the SPES3 facility design and confirm its capability to appropriately simulate the IRIS plant.

SPES3 Facility RELAP5 Sensitivity Analyses on the Containment System for Design Review

Directory of Open Access Journals (Sweden)

Andrea Achilli

2012-01-01

Full Text Available An Italian MSE R&D programme on Nuclear Fission is funding, through ENEA, the design and testing of SPES3 facility at SIET, for IRIS reactor simulation. IRIS is a modular, medium size, advanced, integral PWR, developed by an international consortium of utilities, industries, research centres and universities. SPES3 simulates the primary, secondary and containment systems of IRIS, with 1:100 volume scale, full elevation and prototypical thermal-hydraulic conditions. The RELAP5 code was extensively used in support to the design of the facility to identify criticalities and weak points in the reactor simulation. FER, at Zagreb University, performed the IRIS reactor analyses with the RELAP5 and GOTHIC coupled codes. The comparison between IRIS and SPES3 simulation results led to a simulation-design feedback process with step-by-step modifications of the facility design, up to the final configuration. For this, a series of sensitivity cases was run to investigate specific aspects affecting the trend of the main parameters of the plant, as the containment pressure and EHRS removed power, to limit fuel clad temperature excursions during accidental transients. This paper summarizes the sensitivity analyses on the containment system that allowed to review the SPES3 facility design and confirm its capability to appropriately simulate the IRIS plant.

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.

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

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.

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.

NUPEC BWR Full-size Fine-mesh Bundle Test (BFBT) Benchmark. Volume II: uncertainty and sensitivity analyses of void distribution and critical power - Specification

International Nuclear Information System (INIS)

Aydogan, F.; Hochreiter, L.; Ivanov, K.; Martin, M.; Utsuno, H.; Sartori, E.

2010-01-01

experimental cases from the BFBT database for both steady-state void distribution and steady-state critical power uncertainty analyses. In order to study the basic thermal-hydraulics in a single channel, where the concern regarding the cross-flow effect modelling could be removed, an elemental task is proposed, consisting of two sub-tasks that are placed in each phase of the benchmark scope as follows: - Sub-task 1: Void fraction in elemental channel benchmark; - Sub-task 2: Critical power in elemental channel benchmark. The first task can also be utilised as an uncertainty analysis exercise for fine computational fluid dynamics (CFD) models for which the full bundle sensitivity or uncertainty analysis is more difficult. The task is added to the second volume of the specification as an optional exercise. Chapter 2 of this document provides the definition of UA/SA terms. Chapter 3 provides the selection and characterisation of the input uncertain parameters for the BFBT benchmark and the description of the elemental task. Chapter 4 describes the suggested approach for UA/SA of the BFBT benchmark. Chapter 5 provides the selection of data sets for the uncertainty analysis and the elemental task from the BFBT database. Chapter 6 specifies the requested output for void distribution and critical power uncertainty analyses (Exercises I-4 and II-3) as well as for the elemental task. Chapter 7 provides conclusions. Appendix 1 discusses the UA/SA methods. Appendix 2 presents the Phenomena Identification Ranking Tables (PIRT) developed at PSU for void distribution and critical power predictions in order to assist participants in selecting the most sensitive/uncertain code model parameters

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.

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 (NO_x 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, NO_x and hydrocarbons derived from mobile-source emission studies in the MCMA from 1991 to 2006 with the trends of the concentrations of CO, NO_x, and the CO/NO_x 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 NO_x emission factors do not show any strong trend, effectively reducing the ambient VOC/NO_x 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

Accelerator mass spectrometry analyses of environmental radionuclides: sensitivity, precision and standardisation

Science.gov (United States)

Hotchkis; Fink; Tuniz; Vogt

2000-07-01

Accelerator Mass Spectrometry (AMS) is the analytical technique of choice for the detection of long-lived radionuclides which cannot be practically analysed with decay counting or conventional mass spectrometry. AMS allows an isotopic sensitivity as low as one part in 10(15) for 14C (5.73 ka), 10Be (1.6 Ma), 26Al (720 ka), 36Cl (301 ka), 41Ca (104 ka), 129I (16 Ma) and other long-lived radionuclides occurring in nature at ultra-trace levels. These radionuclides can be used as tracers and chronometers in many disciplines: geology, archaeology, astrophysics, biomedicine and materials science. Low-level decay counting techniques have been developed in the last 40-50 years to detect the concentration of cosmogenic, radiogenic and anthropogenic radionuclides in a variety of specimens. Radioactivity measurements for long-lived radionuclides are made difficult by low counting rates and in some cases the need for complicated radiochemistry procedures and efficient detectors of soft beta-particles and low energy x-rays. The sensitivity of AMS is unaffected by the half-life of the isotope being measured, since the atoms not the radiations that result from their decay, are counted directly. Hence, the efficiency of AMS in the detection of long-lived radionuclides is 10(6)-10(9) times higher than decay counting and the size of the sample required for analysis is reduced accordingly. For example, 14C is being analysed in samples containing as little as 20 microg carbon. There is also a world-wide effort to use AMS for the analysis of rare nuclides of heavy mass, such as actinides, with important applications in safeguards and nuclear waste disposal. Finally, AMS microprobes are being developed for the in-situ analysis of stable isotopes in geological samples, semiconductors and other materials. Unfortunately, the use of AMS is limited by the expensive accelerator technology required, but there are several attempts to develop compact AMS spectrometers at low (advances in AMS

Peer review of HEDR uncertainty and sensitivity analyses plan

Energy Technology Data Exchange (ETDEWEB)

Hoffman, F.O.

1993-06-01

This report consists of a detailed documentation of the writings and deliberations of the peer review panel that met on May 24--25, 1993 in Richland, Washington to evaluate your draft report ``Uncertainty/Sensitivity Analysis Plan`` (PNWD-2124 HEDR). The fact that uncertainties are being considered in temporally and spatially varying parameters through the use of alternative time histories and spatial patterns deserves special commendation. It is important to identify early those model components and parameters that will have the most influence on the magnitude and uncertainty of the dose estimates. These are the items that should be investigated most intensively prior to committing to a final set of results.

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.

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.

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

fluvial sorting of the resulting mixture took place. Most particle size correction procedures assume grain size affects are consistent across sources and tracer properties which is not always the case. Consequently, the < 40 µm fraction of selected soil mixtures was analysed to simulate the effect of selective fluvial transport of finer particles and the results were compared to those for source materials. Preliminary findings from this experiment demonstrate the sensitivity of the numerical mixing model outputs to different particle size distributions of source material and the variable impact of fluvial sorting on end member signatures used in mixing models. The results suggest that particle size correction procedures require careful scrutiny in the context of variable source characteristics.

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.

Accounting for Heterogeneity in Relative Treatment Effects for Use in Cost-Effectiveness Models and Value-of-Information Analyses.

Science.gov (United States)

Welton, Nicky J; Soares, Marta O; Palmer, Stephen; Ades, Anthony E; Harrison, David; Shankar-Hari, Manu; Rowan, Kathy M

2015-07-01

Cost-effectiveness analysis (CEA) models are routinely used to inform health care policy. Key model inputs include relative effectiveness of competing treatments, typically informed by meta-analysis. Heterogeneity is ubiquitous in meta-analysis, and random effects models are usually used when there is variability in effects across studies. In the absence of observed treatment effect modifiers, various summaries from the random effects distribution (random effects mean, predictive distribution, random effects distribution, or study-specific estimate [shrunken or independent of other studies]) can be used depending on the relationship between the setting for the decision (population characteristics, treatment definitions, and other contextual factors) and the included studies. If covariates have been measured that could potentially explain the heterogeneity, then these can be included in a meta-regression model. We describe how covariates can be included in a network meta-analysis model and how the output from such an analysis can be used in a CEA model. We outline a model selection procedure to help choose between competing models and stress the importance of clinical input. We illustrate the approach with a health technology assessment of intravenous immunoglobulin for the management of adult patients with severe sepsis in an intensive care setting, which exemplifies how risk of bias information can be incorporated into CEA models. We show that the results of the CEA and value-of-information analyses are sensitive to the model and highlight the importance of sensitivity analyses when conducting CEA in the presence of heterogeneity. The methods presented extend naturally to heterogeneity in other model inputs, such as baseline risk. © The Author(s) 2015.

Controls on inorganic nitrogen leaching from Finnish catchments assessed using a sensitivity and uncertainty analysis of the INCA-N model

Energy Technology Data Exchange (ETDEWEB)

Rankinen, K.; Granlund, K. [Finnish Environmental Inst., Helsinki (Finland); Futter, M. N. [Swedish Univ. of Agricultural Sciences, Uppsala (Sweden)

2013-11-01

The semi-distributed, dynamic INCA-N model was used to simulate the behaviour of dissolved inorganic nitrogen (DIN) in two Finnish research catchments. Parameter sensitivity and model structural uncertainty were analysed using generalized sensitivity analysis. The Mustajoki catchment is a forested upstream catchment, while the Savijoki catchment represents intensively cultivated lowlands. In general, there were more influential parameters in Savijoki than Mustajoki. Model results were sensitive to N-transformation rates, vegetation dynamics, and soil and river hydrology. Values of the sensitive parameters were based on long-term measurements covering both warm and cold years. The highest measured DIN concentrations fell between minimum and maximum values estimated during the uncertainty analysis. The lowest measured concentrations fell outside these bounds, suggesting that some retention processes may be missing from the current model structure. The lowest concentrations occurred mainly during low flow periods; so effects on total loads were small. (orig.)

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.)

An approach of sensitivity and uncertainty analyses methods installation in a safety calculation

International Nuclear Information System (INIS)

Pepin, G.; Sallaberry, C.

2003-01-01

Simulation of the migration in deep geological formations leads to solve convection-diffusion equations in porous media, associated with the computation of hydrogeologic flow. Different time-scales (simulation during 1 million years), scales of space, contrasts of properties in the calculation domain, are taken into account. This document deals more particularly with uncertainties on the input data of the model. These uncertainties are taken into account in total analysis with the use of uncertainty and sensitivity analysis. ANDRA (French national agency for the management of radioactive wastes) carries out studies on the treatment of input data uncertainties and their propagation in the models of safety, in order to be able to quantify the influence of input data uncertainties of the models on the various indicators of safety selected. The step taken by ANDRA consists initially of 2 studies undertaken in parallel: - the first consists of an international review of the choices retained by ANDRA foreign counterparts to carry out their uncertainty and sensitivity analysis, - the second relates to a review of the various methods being able to be used in sensitivity and uncertainty analysis in the context of ANDRA's safety calculations. Then, these studies are supplemented by a comparison of the principal methods on a test case which gathers all the specific constraints (physical, numerical and data-processing) of the problem studied by ANDRA

Using global sensitivity analysis to understand higher order interactions in complex models: an application of GSA on the Revised Universal Soil Loss Equation (RUSLE) to quantify model sensitivity and implications for ecosystem services management in Costa Rica

Science.gov (United States)

Fremier, A. K.; Estrada Carmona, N.; Harper, E.; DeClerck, F.

2011-12-01

Appropriate application of complex models to estimate system behavior requires understanding the influence of model structure and parameter estimates on model output. To date, most researchers perform local sensitivity analyses, rather than global, because of computational time and quantity of data produced. Local sensitivity analyses are limited in quantifying the higher order interactions among parameters, which could lead to incomplete analysis of model behavior. To address this concern, we performed a GSA on a commonly applied equation for soil loss - the Revised Universal Soil Loss Equation. USLE is an empirical model built on plot-scale data from the USA and the Revised version (RUSLE) includes improved equations for wider conditions, with 25 parameters grouped into six factors to estimate long-term plot and watershed scale soil loss. Despite RUSLE's widespread application, a complete sensitivity analysis has yet to be performed. In this research, we applied a GSA to plot and watershed scale data from the US and Costa Rica to parameterize the RUSLE in an effort to understand the relative importance of model factors and parameters across wide environmental space. We analyzed the GSA results using Random Forest, a statistical approach to evaluate parameter importance accounting for the higher order interactions, and used Classification and Regression Trees to show the dominant trends in complex interactions. In all GSA calculations the management of cover crops (C factor) ranks the highest among factors (compared to rain-runoff erosivity, topography, support practices, and soil erodibility). This is counter to previous sensitivity analyses where the topographic factor was determined to be the most important. The GSA finding is consistent across multiple model runs, including data from the US, Costa Rica, and a synthetic dataset of the widest theoretical space. The three most important parameters were: Mass density of live and dead roots found in the upper inch

Robustness of an uncertainty and sensitivity analysis of early exposure results with the MACCS reactor accident consequence model

International Nuclear Information System (INIS)

Helton, J.C.; Johnson, J.D.; McKay, M.D.; Shiver, A.W.; Sprung, J.L.

1995-01-01

Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis and stepwise regression analysis were used in an investigation with the MACCS model of the early health effects associated with a severe accident at a nuclear power station. The following results were obtained in tests to check the robustness of the analysis techniques: two independent Latin hypercube samples produced similar uncertainty and sensitivity analysis results; setting important variables to best-estimate values produced substantial reductions in uncertainty, while setting the less important variables to best-estimate values had little effect on uncertainty; similar sensitivity analysis results were obtained when the original uniform and loguniform distributions assigned to the 34 imprecisely known input variables were changed to left-triangular distributions and then to right-triangular distributions; and analyses with rank-transformed and logarithmically-transformed data produced similar results and substantially outperformed analyses with raw (i.e., untransformed) data

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

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

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.

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.

Generic uncertainty model for DETRA for environmental consequence analyses. Application and sample outputs

International Nuclear Information System (INIS)

Suolanen, V.; Ilvonen, M.

1998-10-01

Computer model DETRA applies a dynamic compartment modelling approach. The compartment structure of each considered application can be tailored individually. This flexible modelling method makes it possible that the transfer of radionuclides can be considered in various cases: aquatic environment and related food chains, terrestrial environment, food chains in general and food stuffs, body burden analyses of humans, etc. In the former study on this subject, modernization of the user interface of DETRA code was carried out. This new interface works in Windows environment and the usability of the code has been improved. The objective of this study has been to further develop and diversify the user interface so that also probabilistic uncertainty analyses can be performed by DETRA. The most common probability distributions are available: uniform, truncated Gaussian and triangular. The corresponding logarithmic distributions are also available. All input data related to a considered case can be varied, although this option is seldomly needed. The calculated output values can be selected as monitored values at certain simulation time points defined by the user. The results of a sensitivity run are immediately available after simulation as graphical presentations. These outcomes are distributions generated for varied parameters, density functions of monitored parameters and complementary cumulative density functions (CCDF). An application considered in connection with this work was the estimation of contamination of milk caused by radioactive deposition of Cs (10 kBq(Cs-137)/m 2 ). The multi-sequence calculation model applied consisted of a pasture modelling part and a dormant season modelling part. These two sequences were linked periodically simulating the realistic practice of care taking of domestic animals in Finland. The most important parameters were varied in this exercise. The performed diversifying of the user interface of DETRA code seems to provide an easily

Updated model for radionuclide transport in the near-surface till at Forsmark - Implementation of decay chains and sensitivity analyses

International Nuclear Information System (INIS)

Pique, Angels; Pekala, Marek; Molinero, Jorge; Duro, Lara; Trinchero, Paolo; Vries, Luis Manuel de

2013-02-01

The Forsmark area has been proposed for potential siting of a deep underground (geological) repository for radioactive waste in Sweden. Safety assessment of the repository requires radionuclide transport from the disposal depth to recipients at the surface to be studied quantitatively. The near-surface quaternary deposits at Forsmark are considered a pathway for potential discharge of radioactivity from the underground facility to the biosphere, thus radionuclide transport in this system has been extensively investigated over the last years. The most recent work of Pique and co-workers (reported in SKB report R-10-30) demonstrated that in case of release of radioactivity the near-surface sedimentary system at Forsmark would act as an important geochemical barrier, retarding the transport of reactive radionuclides through a combination of retention processes. In this report the conceptual model of radionuclide transport in the quaternary till at Forsmark has been updated, by considering recent revisions regarding the near-surface lithology. In addition, the impact of important conceptual assumptions made in the model has been evaluated through a series of deterministic and probabilistic (Monte Carlo) sensitivity calculations. The sensitivity study focused on the following effects: 1. Radioactive decay of 135 Cs, 59 Ni, 230 Th and 226 Ra and effects on their transport. 2. Variability in key geochemical parameters, such as the composition of the deep groundwater, availability of sorbing materials in the till, and mineral equilibria. 3. Variability in hydraulic parameters, such as the definition of hydraulic boundaries, and values of hydraulic conductivity, dispersivity and the deep groundwater inflow rate. The overarching conclusion from this study is that the current implementation of the model is robust (the model is largely insensitive to variations in the parameters within the studied ranges) and conservative (the Base Case calculations have a tendency to

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.

Sensitivity Analysis of the Bone Fracture Risk Model

Science.gov (United States)

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

2017-01-01

environmental factors, factors associated with the fall event, mass and anthropometric values of the astronaut, BMD characteristics, characteristics of the relationship between BMD and bone strength and bone fracture characteristics. The uncertainty in these factors is captured through the use of parameter distributions and the fracture predictions are probability distributions with a mean value and an associated uncertainty. To determine parameter sensitivity, a correlation coefficient is found between the sample set of each model parameter and the calculated fracture probabilities. Each parameters contribution to the variance is found by squaring the correlation coefficients, dividing by the sum of the squared correlation coefficients, and multiplying by 100. Results: Sensitivity analyses of BFxRM simulations of preflight, 0 days post-flight and 365 days post-flight falls onto the hip revealed a subset of the twelve factors within the model which cause the most variation in the fracture predictions. These factors include the spring constant used in the hip biomechanical model, the midpoint FRI parameter within the equation used to convert FRI to fracture probability and preflight BMD values. Future work: Plans are underway to update the BFxRM by incorporating bone strength information from finite element models (FEM) into the bone strength portion of the BFxRM. Also, FEM bone strength information along with fracture outcome data will be incorporated into the FRI to fracture probability.

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

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.)

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.

Modelling and analysing oriented fibrous structures

International Nuclear Information System (INIS)

Rantala, M; Lassas, M; Siltanen, S; Sampo, J; Takalo, J; Timonen, J

2014-01-01

A mathematical model for fibrous structures using a direction dependent scaling law is presented. The orientation of fibrous nets (e.g. paper) is analysed with a method based on the curvelet transform. The curvelet-based orientation analysis has been tested successfully on real data from paper samples: the major directions of fibrefibre orientation can apparently be recovered. Similar results are achieved in tests on data simulated by the new model, allowing a comparison with ground truth

Using plant growth modeling to analyse C source-sink relations under drought: inter and intra specific comparison

Directory of Open Access Journals (Sweden)

Benoit ePallas

2013-11-01

Full Text Available The ability to assimilate C and allocate NSC (non structural carbohydrates to the most appropriate organs is crucial to maximize plant ecological or agronomic performance. Such C source and sink activities are differentially affected by environmental constraints. Under drought, plant growth is generally more sink than source limited as organ expansion or appearance rate is earlier and stronger affected than C assimilation. This favors plant survival and recovery but not always agronomic performance as NSC are stored rather than used for growth due to a modified metabolism in source and sink leaves. Such interactions between plant C and water balance are complex and plant modeling can help analyzing their impact on plant phenotype. This paper addresses the impact of trade-offs between C sink and source activities and plant production under drought, combining experimental and modeling approaches. Two contrasted monocotyledonous species (rice, oil palm were studied. Experimentally, the sink limitation of plant growth under moderate drought was confirmed as well as the modifications in NSC metabolism in source and sink organs. Under severe stress, when C source became limiting, plant NSC concentration decreased. Two plant models dedicated to oil palm and rice morphogenesis were used to perform a sensitivity analysis and further explore how to optimize C sink and source drought sensitivity to maximize plant growth. Modeling results highlighted that optimal drought sensitivity depends both on drought type and species and that modeling is a great opportunity to analyse such complex processes. Further modeling needs and more generally the challenge of using models to support complex trait breeding are discussed.

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

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

Aleatoric and epistemic uncertainties in sampling based nuclear data uncertainty and sensitivity analyses

International Nuclear Information System (INIS)

Zwermann, W.; Krzykacz-Hausmann, B.; Gallner, L.; Klein, M.; Pautz, A.; Velkov, K.

2012-01-01

Sampling based uncertainty and sensitivity analyses due to epistemic input uncertainties, i.e. to an incomplete knowledge of uncertain input parameters, can be performed with arbitrary application programs to solve the physical problem under consideration. For the description of steady-state particle transport, direct simulations of the microscopic processes with Monte Carlo codes are often used. This introduces an additional source of uncertainty, the aleatoric sampling uncertainty, which is due to the randomness of the simulation process performed by sampling, and which adds to the total combined output sampling uncertainty. So far, this aleatoric part of uncertainty is minimized by running a sufficiently large number of Monte Carlo histories for each sample calculation, thus making its impact negligible as compared to the impact from sampling the epistemic uncertainties. Obviously, this process may cause high computational costs. The present paper shows that in many applications reliable epistemic uncertainty results can also be obtained with substantially lower computational effort by performing and analyzing two appropriately generated series of samples with much smaller number of Monte Carlo histories each. The method is applied along with the nuclear data uncertainty and sensitivity code package XSUSA in combination with the Monte Carlo transport code KENO-Va to various critical assemblies and a full scale reactor calculation. It is shown that the proposed method yields output uncertainties and sensitivities equivalent to the traditional approach, with a high reduction of computing time by factors of the magnitude of 100. (authors)

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

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.

Sensitivity analysis of a PWR pressurizer

International Nuclear Information System (INIS)

Bruel, Renata Nunes

1997-01-01

A sensitivity analysis relative to the parameters and modelling of the physical process in a PWR pressurizer has been performed. The sensitivity analysis was developed by implementing the key parameters and theoretical model lings which generated a comprehensive matrix of influences of each changes analysed. The major influences that have been observed were the flashing phenomenon and the steam condensation on the spray drops. The present analysis is also applicable to the several theoretical and experimental areas. (author)

Uncertainty and Sensitivity Analysis of Filtration Models for Non-Fickian transport and Hyperexponential deposition

DEFF Research Database (Denmark)

Yuan, Hao; Sin, Gürkan

2011-01-01

Uncertainty and sensitivity analyses are carried out to investigate the predictive accuracy of the filtration models for describing non-Fickian transport and hyperexponential deposition. Five different modeling approaches, involving the elliptic equation with different types of distributed...... filtration coefficients and the CTRW equation expressed in Laplace space, are selected to simulate eight experiments. These experiments involve both porous media and colloid-medium interactions of different heterogeneity degrees. The uncertainty of elliptic equation predictions with distributed filtration...... coefficients is larger than that with a single filtration coefficient. The uncertainties of model predictions from the elliptic equation and CTRW equation in Laplace space are minimal for solute transport. Higher uncertainties of parameter estimation and model outputs are observed in the cases with the porous...

A three-stage hybrid model for regionalization, trends and sensitivity analyses of temperature anomalies in China from 1966 to 2015

Science.gov (United States)

Wu, Feifei; Yang, XiaoHua; Shen, Zhenyao

2018-06-01

Temperature anomalies have received increasing attention due to their potentially severe impacts on ecosystems, economy and human health. To facilitate objective regionalization and examine regional temperature anomalies, a three-stage hybrid model with stages of regionalization, trends and sensitivity analyses was developed. Annual mean and extreme temperatures were analyzed using the daily data collected from 537 stations in China from 1966 to 2015, including the annual mean, minimum and maximum temperatures (Tm, TNm and TXm) as well as the extreme minimum and maximum temperatures (TNe and TXe). The results showed the following: (1) subregions with coherent temperature changes were identified using the rotated empirical orthogonal function analysis and K-means clustering algorithm. The numbers of subregions were 6, 7, 8, 9 and 8 for Tm, TNm, TXm, TNe and TXe, respectively. (2) Significant increases in temperature were observed in most regions of China from 1966 to 2015, although warming slowed down over the last decade. This warming primarily featured a remarkable increase in its minimum temperature. For Tm and TNm, 95% of the stations showed a significant upward trend at the 99% confidence level. TNe increased the fastest, at a rate of 0.56 °C/decade, whereas 21% of the stations in TXe showed a downward trend. (3) The mean temperatures (Tm, TNm and TXm) in the high-latitude regions increased more quickly than those in the low-latitude regions. The maximum temperature increased significantly at high elevations, whereas the minimum temperature increased greatly at middle-low elevations. The most pronounced warming occurred in eastern China in TNe and northwestern China in TXe, with mean elevations of 51 m and 2098 m, respectively. A cooling trend in TXe was observed at the northwestern end of China. The warming rate in TNe varied the most among the subregions (0.63 °C/decade).

Updated model for radionuclide transport in the near-surface till at Forsmark - Implementation of decay chains and sensitivity analyses

Energy Technology Data Exchange (ETDEWEB)

Pique, Angels; Pekala, Marek; Molinero, Jorge; Duro, Lara; Trinchero, Paolo; Vries, Luis Manuel de [Amphos 21 Consulting S.L., Barcelona (Spain)

2013-02-15

The Forsmark area has been proposed for potential siting of a deep underground (geological) repository for radioactive waste in Sweden. Safety assessment of the repository requires radionuclide transport from the disposal depth to recipients at the surface to be studied quantitatively. The near-surface quaternary deposits at Forsmark are considered a pathway for potential discharge of radioactivity from the underground facility to the biosphere, thus radionuclide transport in this system has been extensively investigated over the last years. The most recent work of Pique and co-workers (reported in SKB report R-10-30) demonstrated that in case of release of radioactivity the near-surface sedimentary system at Forsmark would act as an important geochemical barrier, retarding the transport of reactive radionuclides through a combination of retention processes. In this report the conceptual model of radionuclide transport in the quaternary till at Forsmark has been updated, by considering recent revisions regarding the near-surface lithology. In addition, the impact of important conceptual assumptions made in the model has been evaluated through a series of deterministic and probabilistic (Monte Carlo) sensitivity calculations. The sensitivity study focused on the following effects: 1. Radioactive decay of {sup 135}Cs, {sup 59}Ni, {sup 230}Th and {sup 226}Ra and effects on their transport. 2. Variability in key geochemical parameters, such as the composition of the deep groundwater, availability of sorbing materials in the till, and mineral equilibria. 3. Variability in hydraulic parameters, such as the definition of hydraulic boundaries, and values of hydraulic conductivity, dispersivity and the deep groundwater inflow rate. The overarching conclusion from this study is that the current implementation of the model is robust (the model is largely insensitive to variations in the parameters within the studied ranges) and conservative (the Base Case calculations have a

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.

Economic analysis of hydrogen production through a bio-ethanol steam reforming process: Sensitivity analyses and cost estimations

International Nuclear Information System (INIS)

Song, Hua; Ozkan, Umit S.

2010-01-01

In this study, the hydrogen selling price from ethanol steam reforming has been estimated for two different production scenarios in the United States, i.e. central production (150,000 kg H 2 /day) and distributed (forecourt) production (1500 kg H 2 /day), based on a process flowchart generated by Aspen Plus registered including downstream purification steps and economic analysis model template published by the U.S Department of Energy (DOE). The effect of several processing parameters as well as catalyst properties on the hydrogen selling price has been evaluated. 2.69/kg is estimated as the selling price for a central production process of 150,000 kg H 2 /day and 4.27/kg for a distributed hydrogen production process at a scale of 1500 kg H 2 /day. Among the parameters investigated through sensitivity analyses, ethanol feedstock cost, catalyst cost, and catalytic performance are found to play a significant role on determining the final hydrogen selling price. (author)

Numerical model analysis of the shaded dye-sensitized solar cell module

International Nuclear Information System (INIS)

Chen Shuanghong; Weng Jian; Huang Yang; Zhang Changneng; Hu Linhua; Kong Fantai; Wang Lijun; Dai Songyuan

2010-01-01

On the basis of a numerical model analysis, the photovoltaic performance of a partially shadowed dye-sensitized solar cell (DSC) module is investigated. In this model, the electron continuity equation and the Butler-Vollmer equation are applied considering electron transfer via the interface of transparent conducting oxide/electrolyte in the shaded DSC. The simulation results based on this model are consistent with experimental results. The influence of shading ratio, connection types and the intensity of irradiance has been analysed according to experiments and numerical simulation. It is found that the performance of the DSC obviously declines with an increase in the shaded area due to electron recombination at the TCO/electrolyte interface and that the output power loss of the shadowed DSC modules in series is much larger than that in parallel due to the 'breakdown' occurring at the TCO/electrolyte interface. The impact of shadow on the DSC performance is stronger with increase in irradiation intensity.

Externalizing Behaviour for Analysing System Models

DEFF Research Database (Denmark)

Ivanova, Marieta Georgieva; Probst, Christian W.; Hansen, René Rydhof

2013-01-01

System models have recently been introduced to model organisations and evaluate their vulnerability to threats and especially insider threats. Especially for the latter these models are very suitable, since insiders can be assumed to have more knowledge about the attacked organisation than outside...... attackers. Therefore, many attacks are considerably easier to be performed for insiders than for outsiders. However, current models do not support explicit specification of different behaviours. Instead, behaviour is deeply embedded in the analyses supported by the models, meaning that it is a complex......, if not impossible task to change behaviours. Especially when considering social engineering or the human factor in general, the ability to use different kinds of behaviours is essential. In this work we present an approach to make the behaviour a separate component in system models, and explore how to integrate...

A tool model for predicting atmospheric kinetics with sensitivity analysis

Institute of Scientific and Technical Information of China (English)

无

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.

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 ...

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.

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.

Evaluation of bentonite alteration due to interactions with iron. Sensitivity analyses to identify the important factors for the bentonite alteration

International Nuclear Information System (INIS)

Sasamoto, Hiroshi; Wilson, James; Sato, Tsutomu

2013-01-01

Performance assessment of geological disposal systems for high-level radioactive waste requires a consideration of long-term systems behaviour. It is possible that the alteration of swelling clay present in bentonite buffers might have an impact on buffer functions. In the present study, iron (as a candidate overpack material)-bentonite (I-B) interactions were evaluated as the main buffer alteration scenario. Existing knowledge on alteration of bentonite during I-B interactions was first reviewed, then the evaluation methodology was developed considering modeling techniques previously used overseas. A conceptual model for smectite alteration during I-B interactions was produced. The following reactions and processes were selected: 1) release of Fe 2+ due to overpack corrosion; 2) diffusion of Fe 2+ in compacted bentonite; 3) sorption of Fe 2+ on smectite edge and ion exchange in interlayers; 4) dissolution of primary phases and formation of alteration products. Sensitivity analyses were performed to identify the most important factors for the alteration of bentonite by I-B interactions. (author)

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.

Sensitivity Analysis of DRASTIC Model in Vulnerability Assessment of Shahrood Alluvial Aquifer

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Shadi Abolhasan Almasi

2017-07-01

Full Text Available Groundwater vulnerability assessment is typically accomplished as a management tool to protect groundwater resources. In this research, the DRASTIC model which is an empirical one used for evaluating the potential of an aquifer for pollution was employed to evaluate the vulnerability of Shahrood alluvial aquifer. Moreover, the sensitivity of the model paramneters was assessed to identify the ones with greatest effect on vulnerability. The model layers including depth to groundwater table level, recharge, aquifer media, topography, impact of unsaturated zone, and hydraulic conductivity were prepared and classified in the ArcGIS software based on analyses of both the available data and the layer of surface soil texture using Aster satellite images. Once the vulnerability index was calculated, the sensitivity map of Shahroud aquifer vulnerability was analyzed using the two parameter removal and single parameter sensitivity methods. These were further verified by textural analysis of soil samples from different parts of the region. The layers with appropriate weights were overlaid and the DRASTIC index of the aquifer was estimated at 28 to 148. The highest vulnerability was detected in the northern margins and southwestern parts of the aquifer while other parts were characterized by medium to low vulnerability. The low nitrogen concentration observed in the farm areas and its rise to 45 mg/l in the northern stretches of the aquifer bear witness to the accuracy of the zoning rendered by the DRASTIC model. Based on the vulnerability map of Sharoud aquifer, it was found that 1.6% of the aquifer’s area has a very high vulnerability or potential for pollution followed by 10%, 28.8%, and 18.9% of the area were identified as having high, medium and low potentials for pollution, respecytively. The remaining (i.e., 40.5% was found to have no risk of pollution.

Particle transport model sensitivity on wave-induced processes

Science.gov (United States)

Staneva, Joanna; Ricker, Marcel; Krüger, Oliver; Breivik, Oyvind; Stanev, Emil; Schrum, Corinna

2017-04-01

Different effects of wind waves on the hydrodynamics in the North Sea are investigated using a coupled wave (WAM) and circulation (NEMO) model system. The terms accounting for the wave-current interaction are: the Stokes-Coriolis force, the sea-state dependent momentum and energy flux. The role of the different Stokes drift parameterizations is investigated using a particle-drift model. Those particles can be considered as simple representations of either oil fractions, or fish larvae. In the ocean circulation models the momentum flux from the atmosphere, which is related to the wind speed, is passed directly to the ocean and this is controlled by the drag coefficient. However, in the real ocean, the waves play also the role of a reservoir for momentum and energy because different amounts of the momentum flux from the atmosphere is taken up by the waves. In the coupled model system the momentum transferred into the ocean model is estimated as the fraction of the total flux that goes directly to the currents plus the momentum lost from wave dissipation. Additionally, we demonstrate that the wave-induced Stokes-Coriolis force leads to a deflection of the current. During the extreme events the Stokes velocity is comparable in magnitude to the current velocity. The resulting wave-induced drift is crucial for the transport of particles in the upper ocean. The performed sensitivity analyses demonstrate that the model skill depends on the chosen processes. The results are validated using surface drifters, ADCP, HF radar data and other in-situ measurements in different regions of the North Sea with a focus on the coastal areas. The using of a coupled model system reveals that the newly introduced wave effects are important for the drift-model performance, especially during extremes. Those effects cannot be neglected by search and rescue, oil-spill, transport of biological material, or larva drift modelling.

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

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

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)

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.

Development of ITER 3D neutronics model and nuclear analyses

International Nuclear Information System (INIS)

Zeng, Q.; Zheng, S.; Lu, L.; Li, Y.; Ding, A.; Hu, H.; Wu, Y.

2007-01-01

ITER nuclear analyses rely on the calculations with the three-dimensional (3D) Monte Carlo code e.g. the widely-used MCNP. However, continuous changes in the design of the components require the 3D neutronics model for nuclear analyses should be updated. Nevertheless, the modeling of a complex geometry with MCNP by hand is a very time-consuming task. It is an efficient way to develop CAD-based interface code for automatic conversion from CAD models to MCNP input files. Based on the latest CAD model and the available interface codes, the two approaches of updating 3D nuetronics model have been discussed by ITER IT (International Team): The first is to start with the existing MCNP model 'Brand' and update it through a combination of direct modification of the MCNP input file and generation of models for some components directly from the CAD data; The second is to start from the full CAD model, make the necessary simplifications, and generate the MCNP model by one of the interface codes. MCAM as an advanced CAD-based MCNP interface code developed by FDS Team in China has been successfully applied to update the ITER 3D neutronics model by adopting the above two approaches. The Brand model has been updated to generate portions of the geometry based on the newest CAD model by MCAM. MCAM has also successfully performed conversion to MCNP neutronics model from a full ITER CAD model which is simplified and issued by ITER IT to benchmark the above interface codes. Based on the two updated 3D neutronics models, the related nuclear analyses are performed. This paper presents the status of ITER 3D modeling by using MCAM and its nuclear analyses, as well as a brief introduction of advanced version of MCAM. (authors)

Utilization of Large Scale Surface Models for Detailed Visibility Analyses

Science.gov (United States)

Caha, J.; Kačmařík, M.

2017-11-01

This article demonstrates utilization of large scale surface models with small spatial resolution and high accuracy, acquired from Unmanned Aerial Vehicle scanning, for visibility analyses. The importance of large scale data for visibility analyses on the local scale, where the detail of the surface model is the most defining factor, is described. The focus is not only the classic Boolean visibility, that is usually determined within GIS, but also on so called extended viewsheds that aims to provide more information about visibility. The case study with examples of visibility analyses was performed on river Opava, near the Ostrava city (Czech Republic). The multiple Boolean viewshed analysis and global horizon viewshed were calculated to determine most prominent features and visibility barriers of the surface. Besides that, the extended viewshed showing angle difference above the local horizon, which describes angular height of the target area above the barrier, is shown. The case study proved that large scale models are appropriate data source for visibility analyses on local level. The discussion summarizes possible future applications and further development directions of visibility analyses.

Multiple predictor smoothing methods for sensitivity analysis.

Energy Technology Data Exchange (ETDEWEB)

Helton, Jon Craig; Storlie, Curtis B.

2006-08-01

The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present.

Multiple predictor smoothing methods for sensitivity analysis

International Nuclear Information System (INIS)

Helton, Jon Craig; Storlie, Curtis B.

2006-01-01

The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present

A DNA microarray-based methylation-sensitive (MS)-AFLP hybridization method for genetic and epigenetic analyses.

Science.gov (United States)

Yamamoto, F; Yamamoto, M

2004-07-01

We previously developed a PCR-based DNA fingerprinting technique named the Methylation Sensitive (MS)-AFLP method, which permits comparative genome-wide scanning of methylation status with a manageable number of fingerprinting experiments. The technique uses the methylation sensitive restriction enzyme NotI in the context of the existing Amplified Fragment Length Polymorphism (AFLP) method. Here we report the successful conversion of this gel electrophoresis-based DNA fingerprinting technique into a DNA microarray hybridization technique (DNA Microarray MS-AFLP). By performing a total of 30 (15 x 2 reciprocal labeling) DNA Microarray MS-AFLP hybridization experiments on genomic DNA from two breast and three prostate cancer cell lines in all pairwise combinations, and Southern hybridization experiments using more than 100 different probes, we have demonstrated that the DNA Microarray MS-AFLP is a reliable method for genetic and epigenetic analyses. No statistically significant differences were observed in the number of differences between the breast-prostate hybridization experiments and the breast-breast or prostate-prostate comparisons.

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

Sensitivity analysis and parameter estimation for distributed hydrological modeling: potential of variational methods

Directory of Open Access Journals (Sweden)

W. Castaings

2009-04-01

Full Text Available Variational methods are widely used for the analysis and control of computationally intensive spatially distributed systems. In particular, the adjoint state method enables a very efficient calculation of the derivatives of an objective function (response function to be analysed or cost function to be optimised with respect to model inputs.

In this contribution, it is shown that the potential of variational methods for distributed catchment scale hydrology should be considered. A distributed flash flood model, coupling kinematic wave overland flow and Green Ampt infiltration, is applied to a small catchment of the Thoré basin and used as a relatively simple (synthetic observations but didactic application case.

It is shown that forward and adjoint sensitivity analysis provide a local but extensive insight on the relation between the assigned model parameters and the simulated hydrological response. Spatially distributed parameter sensitivities can be obtained for a very modest calculation effort (~6 times the computing time of a single model run and the singular value decomposition (SVD of the Jacobian matrix provides an interesting perspective for the analysis of the rainfall-runoff relation.

For the estimation of model parameters, adjoint-based derivatives were found exceedingly efficient in driving a bound-constrained quasi-Newton algorithm. The reference parameter set is retrieved independently from the optimization initial condition when the very common dimension reduction strategy (i.e. scalar multipliers is adopted.

Furthermore, the sensitivity analysis results suggest that most of the variability in this high-dimensional parameter space can be captured with a few orthogonal directions. A parametrization based on the SVD leading singular vectors was found very promising but should be combined with another regularization strategy in order to prevent overfitting.

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.

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

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.

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.

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.

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.

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.

Uncertainty and sensitivity analyses for gas and brine migration at the Waste Isolation Pilot Plant, May 1992

International Nuclear Information System (INIS)

Helton, J.C.; Bean, J.E.; Butcher, B.M.; Garner, J.W.; Vaughn, P.; Schreiber, J.D.; Swift, P.N.

1993-08-01

Uncertainty and sensitivity analysis techniques based on Latin hypercube sampling, partial correlation analysis, stepwise regression analysis and examination of scatterplots are used in conjunction with the BRAGFLO model to examine two phase flow (i.e., gas and brine) at the Waste Isolation Pilot Plant (WIPP), which is being developed by the US Department of Energy as a disposal facility for transuranic waste. The analyses consider either a single waste panel or the entire repository in conjunction with the following cases: (1) fully consolidated shaft, (2) system of shaft seals with panel seals, and (3) single shaft seal without panel seals. The purpose of this analysis is to develop insights on factors that are potentially important in showing compliance with applicable regulations of the US Environmental Protection Agency (i.e., 40 CFR 191, Subpart B; 40 CFR 268). The primary topics investigated are (1) gas production due to corrosion of steel, (2) gas production due to microbial degradation of cellulosics, (3) gas migration into anhydrite marker beds in the Salado Formation, (4) gas migration through a system of shaft seals to overlying strata, and (5) gas migration through a single shaft seal to overlying strata. Important variables identified in the analyses include initial brine saturation of the waste, stoichiometric terms for corrosion of steel and microbial degradation of cellulosics, gas barrier pressure in the anhydrite marker beds, shaft seal permeability, and panel seal permeability

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.

Preliminary performance assessment for the Waste Isolation Pilot Plant, December 1992. Volume 4: Uncertainty and sensitivity analyses for 40 CFR 191, Subpart B

Energy Technology Data Exchange (ETDEWEB)

1993-08-01

Before disposing of transuranic radioactive waste in the Waste Isolation Pilot Plant (WIPP), the United States Department of Energy (DOE) must evaluate compliance with applicable long-term regulations of the United States Environmental Protection Agency (EPA). Sandia National Laboratories is conducting iterative performance assessments (PAs) of the WIPP for the DOE to provide interim guidance while preparing for a final compliance evaluation. This volume of the 1992 PA contains results of uncertainty and sensitivity analyses with respect to the EPA`s Environmental Protection Standards for Management and Disposal of Spent Nuclear Fuel, High-Level and Transuranic Radioactive Wastes (40 CFR 191, Subpart B). Additional information about the 1992 PA is provided in other volumes. Results of the 1992 uncertainty and sensitivity analyses indicate that, conditional on the modeling assumptions, the choice of parameters selected for sampling, and the assigned parameter-value distributions, the most important parameters for which uncertainty has the potential to affect compliance with 40 CFR 191B are: drilling intensity, intrusion borehole permeability, halite and anhydrite permeabilities, radionuclide solubilities and distribution coefficients, fracture spacing in the Culebra Dolomite Member of the Rustler Formation, porosity of the Culebra, and spatial variability of Culebra transmissivity. Performance with respect to 40 CFR 191B is insensitive to uncertainty in other parameters; however, additional data are needed to confirm that reality lies within the assigned distributions.

Sensitivity analysis using the FRAPCON-1/EM: development of a calculation model for licensing

International Nuclear Information System (INIS)

Chapot, J.L.C.

1985-01-01

The FRAPCON-1/EM is version of the FRAPCON-1 code which analyses fuel rods performance under normal operation conditions. This version yields conservative results and is used by the NRC in its licensing activities. A sensitivity analysis was made, to determine the combination of models from the FRAPCON-1/EM which yields the most conservative results for a typical Angra-1 reactor fuel rod. The present analysis showed that this code can be used as a calculation tool for the licensing of the Angra-1 reload. (F.E.) [pt

Assessment of decision making models in sensitive technology: the nuclear energy case

International Nuclear Information System (INIS)

Silva, Eduardo Ramos Ferreira da

2007-01-01

In this paper a bibliographic review is proceeded on the decision making processes approaching the sensitive technologies (the military and civilian uses as well), and the nuclear technology herself. It is made a correlation among the development of the nuclear technology and the decision making processes, showing that from 70 decade on, such processes are connected to the national security doctrines influenced by the Brazilian War College. So, every time that the national security is altered, so is the master line of the decision making process altered. In the Brazil case, the alteration appeared from the World War II up to the new proposals coming out from the Ministry of Defense are shown related to the nuclear technology. The existent models are analysed with a conclusion that such models are unveiling at the present situation of the moment, concerning to the nuclear technology

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

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

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...

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.

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

Sensitivity and uncertainty analyses of unsaturated flow travel time in the CHnz unit of Yucca Mountain, Nevada

International Nuclear Information System (INIS)

Nichols, W.E.; Freshley, M.D.

1991-10-01

This report documents the results of sensitivity and uncertainty analyses conducted to improve understanding of unsaturated zone ground-water travel time distribution at Yucca Mountain, Nevada. The US Department of Energy (DOE) is currently performing detailed studies at Yucca Mountain to determine its suitability as a host for a geologic repository for the containment of high-level nuclear wastes. As part of these studies, DOE is conducting a series of Performance Assessment Calculational Exercises, referred to as the PACE problems. The work documented in this report represents a part of the PACE-90 problems that addresses the effects of natural barriers of the site that will stop or impede the long-term movement of radionuclides from the potential repository to the accessible environment. In particular, analyses described in this report were designed to investigate the sensitivity of the ground-water travel time distribution to different input parameters and the impact of uncertainty associated with those input parameters. Five input parameters were investigated in this study: recharge rate, saturated hydraulic conductivity, matrix porosity, and two curve-fitting parameters used for the van Genuchten relations to quantify the unsaturated moisture-retention and hydraulic characteristics of the matrix. 23 refs., 20 figs., 10 tabs

Model tests and numerical analyses on horizontal impedance functions of inclined single piles embedded in cohesionless soil

Science.gov (United States)

Goit, Chandra Shekhar; Saitoh, Masato

2013-03-01

Horizontal impedance functions of inclined single piles are measured experimentally for model soil-pile systems with both the effects of local soil nonlinearity and resonant characteristics. Two practical pile inclinations of 5° and 10° in addition to a vertical pile embedded in cohesionless soil and subjected to lateral harmonic pile head loadings for a wide range of frequencies are considered. Results obtained with low-to-high amplitude of lateral loadings on model soil-pile systems encased in a laminar shear box show that the local nonlinearities have a profound impact on the horizontal impedance functions of piles. Horizontal impedance functions of inclined piles are found to be smaller than the vertical pile and the values decrease as the angle of pile inclination increases. Distinct values of horizontal impedance functions are obtained for the `positive' and `negative' cycles of harmonic loadings, leading to asymmetric force-displacement relationships for the inclined piles. Validation of these experimental results is carried out through three-dimensional nonlinear finite element analyses, and the results from the numerical models are in good agreement with the experimental data. Sensitivity analyses conducted on the numerical models suggest that the consideration of local nonlinearity at the vicinity of the soil-pile interface influence the response of the soil-pile systems.

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.

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.

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.

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.

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

Two Model-Based Methods for Policy Analyses of Fine Particulate Matter Control in China: Source Apportionment and Source Sensitivity

Science.gov (United States)

Li, X.; Zhang, Y.; Zheng, B.; Zhang, Q.; He, K.

2013-12-01

Anthropogenic emissions have been controlled in recent years in China to mitigate fine particulate matter (PM2.5) pollution. Recent studies show that sulfate dioxide (SO2)-only control cannot reduce total PM2.5 levels efficiently. Other species such as nitrogen oxide, ammonia, black carbon, and organic carbon may be equally important during particular seasons. Furthermore, each species is emitted from several anthropogenic sectors (e.g., industry, power plant, transportation, residential and agriculture). On the other hand, contribution of one emission sector to PM2.5 represents contributions of all species in this sector. In this work, two model-based methods are used to identify the most influential emission sectors and areas to PM2.5. The first method is the source apportionment (SA) based on the Particulate Source Apportionment Technology (PSAT) available in the Comprehensive Air Quality Model with extensions (CAMx) driven by meteorological predictions of the Weather Research and Forecast (WRF) model. The second method is the source sensitivity (SS) based on an adjoint integration technique (AIT) available in the GEOS-Chem model. The SA method attributes simulated PM2.5 concentrations to each emission group, while the SS method calculates their sensitivity to each emission group, accounting for the non-linear relationship between PM2.5 and its precursors. Despite their differences, the complementary nature of the two methods enables a complete analysis of source-receptor relationships to support emission control policies. Our objectives are to quantify the contributions of each emission group/area to PM2.5 in the receptor areas and to intercompare results from the two methods to gain a comprehensive understanding of the role of emission sources in PM2.5 formation. The results will be compared in terms of the magnitudes and rankings of SS or SA of emitted species and emission groups/areas. GEOS-Chem with AIT is applied over East Asia at a horizontal grid

Uncertainty, Sensitivity Analysis, and Causal Identification in the Arctic using a Perturbed Parameter Ensemble of the HiLAT Climate Model

Energy Technology Data Exchange (ETDEWEB)

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

2018-02-12

Coupled climate models have a large number of input parameters that can affect output uncertainty. We conducted a sensitivity analysis of sea ice proper:es and Arc:c related climate variables to 5 parameters in the HiLAT climate model: air-ocean turbulent exchange parameter (C), conversion of water vapor to clouds (cldfrc_rhminl) and of ice crystals to snow (micro_mg_dcs), snow thermal conduc:vity (ksno), and maximum snow grain size (rsnw_mlt). We used an elementary effect (EE) approach to rank their importance for output uncertainty. EE is an extension of one-at-a-time sensitivity analyses, but it is more efficient in sampling multi-dimensional parameter spaces. We looked for emerging relationships among climate variables across the model ensemble, and used causal discovery algorithms to establish potential pathways for those relationships.

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

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.

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.

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.

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.

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.

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.

What can we learn from global sensitivity analysis of biochemical systems?

Science.gov (United States)

Kent, Edward; Neumann, Stefan; Kummer, Ursula; Mendes, Pedro

2013-01-01

Most biological models of intermediate size, and probably all large models, need to cope with the fact that many of their parameter values are unknown. In addition, it may not be possible to identify these values unambiguously on the basis of experimental data. This poses the question how reliable predictions made using such models are. Sensitivity analysis is commonly used to measure the impact of each model parameter on its variables. However, the results of such analyses can be dependent on an exact set of parameter values due to nonlinearity. To mitigate this problem, global sensitivity analysis techniques are used to calculate parameter sensitivities in a wider parameter space. We applied global sensitivity analysis to a selection of five signalling and metabolic models, several of which incorporate experimentally well-determined parameters. Assuming these models represent physiological reality, we explored how the results could change under increasing amounts of parameter uncertainty. Our results show that parameter sensitivities calculated with the physiological parameter values are not necessarily the most frequently observed under random sampling, even in a small interval around the physiological values. Often multimodal distributions were observed. Unsurprisingly, the range of possible sensitivity coefficient values increased with the level of parameter uncertainty, though the amount of parameter uncertainty at which the pattern of control was able to change differed among the models analysed. We suggest that this level of uncertainty can be used as a global measure of model robustness. Finally a comparison of different global sensitivity analysis techniques shows that, if high-throughput computing resources are available, then random sampling may actually be the most suitable technique.

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.

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.

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.

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

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.

Performance of neutron kinetics models for ADS transient analyses

International Nuclear Information System (INIS)

Rineiski, A.; Maschek, W.; Rimpault, G.

2002-01-01

Within the framework of the SIMMER code development, neutron kinetics models for simulating transients and hypothetical accidents in advanced reactor systems, in particular in Accelerator Driven Systems (ADSs), have been developed at FZK/IKET in cooperation with CE Cadarache. SIMMER is a fluid-dynamics/thermal-hydraulics code, coupled with a structure model and a space-, time- and energy-dependent neutronics module for analyzing transients and accidents. The advanced kinetics models have also been implemented into KIN3D, a module of the VARIANT/TGV code (stand-alone neutron kinetics) for broadening application and for testing and benchmarking. In the paper, a short review of the SIMMER and KIN3D neutron kinetics models is given. Some typical transients related to ADS perturbations are analyzed. The general models of SIMMER and KIN3D are compared with more simple techniques developed in the context of this work to get a better understanding of the specifics of transients in subcritical systems and to estimate the performance of different kinetics options. These comparisons may also help in elaborating new kinetics models and extending existing computation tools for ADS transient analyses. The traditional point-kinetics model may give rather inaccurate transient reaction rate distributions in an ADS even if the material configuration does not change significantly. This inaccuracy is not related to the problem of choosing a 'right' weighting function: the point-kinetics model with any weighting function cannot take into account pronounced flux shape variations related to possible significant changes in the criticality level or to fast beam trips. To improve the accuracy of the point-kinetics option for slow transients, we have introduced a correction factor technique. The related analyses give a better understanding of 'long-timescale' kinetics phenomena in the subcritical domain and help to evaluate the performance of the quasi-static scheme in a particular case. One

Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method (ESQM v5.2)

Science.gov (United States)

Kalra, Tarandeep S.; Aretxabaleta, Alfredo; Seshadri, Pranay; Ganju, Neil K.; Beudin, Alexis

2017-12-01

Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as the Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant stem density, height, and, to a lesser degree, diameter. Wave dissipation is mostly dependent on the variation in plant stem density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance to optimize efforts and reduce exploration of parameter space for future observational and modeling work.

Prediction of clamp-derived insulin sensitivity from the oral glucose insulin sensitivity index

DEFF Research Database (Denmark)

Tura, Andrea; Chemello, Gaetano; Szendroedi, Julia

2018-01-01

that underwent both a clamp and an OGTT or meal test, thereby allowing calculation of both the M value and OGIS. The population was divided into a training and a validation cohort (n = 359 and n = 154, respectively). After a stepwise selection approach, the best model for M value prediction was applied......AIMS/HYPOTHESIS: The euglycaemic-hyperinsulinaemic clamp is the gold-standard method for measuring insulin sensitivity, but is less suitable for large clinical trials. Thus, several indices have been developed for evaluating insulin sensitivity from the oral glucose tolerance test (OGTT). However......, most of them yield values different from those obtained by the clamp method. The aim of this study was to develop a new index to predict clamp-derived insulin sensitivity (M value) from the OGTT-derived oral glucose insulin sensitivity index (OGIS). METHODS: We analysed datasets of people...

A dialogue game for analysing group model building: framing collaborative modelling and its facilitation

NARCIS (Netherlands)

Hoppenbrouwers, S.J.B.A.; Rouwette, E.A.J.A.

2012-01-01

This paper concerns a specific approach to analysing and structuring operational situations in collaborative modelling. Collaborative modelling is viewed here as 'the goal-driven creation and shaping of models that are based on the principles of rational description and reasoning'. Our long term

Methodology to carry out a sensitivity and uncertainty analysis for cross sections using a coupled model Trace-Parcs

International Nuclear Information System (INIS)

Reyes F, M. C.; Del Valle G, E.; Gomez T, A. M.; Sanchez E, V.

2015-09-01

A methodology was implemented to carry out a sensitivity and uncertainty analysis for cross sections used in a coupled model for Trace/Parcs in a transient of control rod fall of a BWR-5. A model of the reactor core for the neutronic code Parcs was used, in which the assemblies located in the core are described. Thermo-hydraulic model in Trace was a simple model, where only a component type Chan was designed to represent all the core assemblies, which it was within a single vessel and boundary conditions were established. The thermo-hydraulic part was coupled with the neutron part, first for the steady state and then a transient of control rod fall was carried out for the sensitivity and uncertainty analysis. To carry out the analysis of cross sections used in the coupled model Trace/Parcs during the transient, the Probability Density Functions for 22 parameters selected from the total of neutronic parameters that use Parcs were generated, obtaining 100 different cases for the coupled model Trace/Parcs, each one with a database of different cross sections. All these cases were executed with the coupled model, obtaining in consequence 100 different output files for the transient of control rod fall doing emphasis in the nominal power, for which an uncertainty analysis was realized at the same time generate the band of uncertainty. With this analysis is possible to observe the ranges of results of the elected responses varying the selected uncertainty parameters. The sensitivity analysis complements the uncertainty analysis, identifying the parameter or parameters with more influence on the results and thus focuses on these parameters in order to better understand their effects. Beyond the obtained results, because is not a model with real operation data, the importance of this work is to know the application of the methodology to carry out the sensitivity and uncertainty analyses. (Author)

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...

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

Cross-section sensitivity analyses for a Tokamak Experimental Power Reactor

International Nuclear Information System (INIS)

Simmons, E.L.; Gerstl, S.A.W.; Dudziak, D.J.

1977-09-01

The objectives of this report were (1) to determine the sensitivity of neutronic responses in the preliminary design of the Tokamak Experimental Power Reactor by Argonne National Laboratory, and (2) to develop the use of a neutron-gamma coupled cross-section set in the calculation of cross-section sensitivity analysis. Response functions such as neutron plus gamma kerma, Mylar dose, copper transmutation, copper dpa, and activation of the toroidal field coil dewar were investigated. Calculations revealed that the responses were most sensitive to the high-energy group cross sections of iron in the innermost regions containing stainless steel. For example, both the neutron heating of the toroidal field coil and the activation of the toroidal field coil dewar show an integral sensitivity of about -5 with respect to the iron total cross sections. Major contributors are the scattering cross sections of iron, with -2.7 and -4.4 for neutron heating and activation, respectively. The effects of changes in gamma cross sections were generally an order of 10 lower

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.

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)

Systematic comparative and sensitivity analyses of additive and outranking techniques for supporting impact significance assessments

International Nuclear Information System (INIS)

Cloquell-Ballester, Vicente-Agustin; Monterde-Diaz, Rafael; Cloquell-Ballester, Victor-Andres; Santamarina-Siurana, Maria-Cristina

2007-01-01

Assessing the significance of environmental impacts is one of the most important and all together difficult processes of Environmental Impact Assessment. This is largely due to the multicriteria nature of the problem. To date, decision techniques used in the process suffer from two drawbacks, namely the problem of compensation and the problem of identification of the 'exact boundary' between sub-ranges. This article discusses these issues and proposes a methodology for determining the significance of environmental impacts based on comparative and sensitivity analyses using the Electre TRI technique. An application of the methodology for the environmental assessment of a Power Plant project within the Valencian Region (Spain) is presented, and its performance evaluated. It is concluded that contrary to other techniques, Electre TRI automatically identifies those cases where allocation of significance categories is most difficult and, when combined with sensitivity analysis, offers greatest robustness in the face of variation in weights of the significance attributes. Likewise, this research demonstrates the efficacy of systematic comparison between Electre TRI and sum-based techniques, in the solution of assignment problems. The proposed methodology can therefore be regarded as a successful aid to the decision-maker, who will ultimately take the final decision

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

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

by the uncertainties in both SO2 and NH3 emissions. Likewise, the relative uncertainties in the modelled surface concentrations of each of the secondary pollutant variables (NH4+, NO3-, SO42-, and HNO3) were due to uncertainties in at least two input variables. In all cases the spatial distribution of relative uncertainty was found to be geographically heterogeneous. The global methods used here can be applied to conduct sensitivity and uncertainty analyses of other ACTMs.

Risk Factor Analyses for the Return of Spontaneous Circulation in the Asphyxiation Cardiac Arrest Porcine Model

Directory of Open Access Journals (Sweden)

Cai-Jun Wu

2015-01-01

Full Text Available Background: Animal models of asphyxiation cardiac arrest (ACA are frequently used in basic research to mirror the clinical course of cardiac arrest (CA. The rates of the return of spontaneous circulation (ROSC in ACA animal models are lower than those from studies that have utilized ventricular fibrillation (VF animal models. The purpose of this study was to characterize the factors associated with the ROSC in the ACA porcine model. Methods: Forty-eight healthy miniature pigs underwent endotracheal tube clamping to induce CA. Once induced, CA was maintained untreated for a period of 8 min. Two minutes following the initiation of cardiopulmonary resuscitation (CPR, defibrillation was attempted until ROSC was achieved or the animal died. To assess the factors associated with ROSC in this CA model, logistic regression analyses were performed to analyze gender, the time of preparation, the amplitude spectrum area (AMSA from the beginning of CPR and the pH at the beginning of CPR. A receiver-operating characteristic (ROC curve was used to evaluate the predictive value of AMSA for ROSC. Results: ROSC was only 52.1% successful in this ACA porcine model. The multivariate logistic regression analyses revealed that ROSC significantly depended on the time of preparation, AMSA at the beginning of CPR and pH at the beginning of CPR. The area under the ROC curve in for AMSA at the beginning of CPR was 0.878 successful in predicting ROSC (95% confidence intervals: 0.773∼0.983, and the optimum cut-off value was 15.62 (specificity 95.7% and sensitivity 80.0%. Conclusions: The time of preparation, AMSA and the pH at the beginning of CPR were associated with ROSC in this ACA porcine model. AMSA also predicted the likelihood of ROSC in this ACA animal model.

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...

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...

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

Parametric Sensitivity Analysis of Oscillatory Delay Systems with an Application to Gene Regulation.

Science.gov (United States)

Ingalls, Brian; Mincheva, Maya; Roussel, Marc R

2017-07-01

A parametric sensitivity analysis for periodic solutions of delay-differential equations is developed. Because phase shifts cause the sensitivity coefficients of a periodic orbit to diverge, we focus on sensitivities of the extrema, from which amplitude sensitivities are computed, and of the period. Delay-differential equations are often used to model gene expression networks. In these models, the parametric sensitivities of a particular genotype define the local geometry of the evolutionary landscape. Thus, sensitivities can be used to investigate directions of gradual evolutionary change. An oscillatory protein synthesis model whose properties are modulated by RNA interference is used as an example. This model consists of a set of coupled delay-differential equations involving three delays. Sensitivity analyses are carried out at several operating points. Comments on the evolutionary implications of the results are offered.

Comparison of risk sensitivity to human errors in the Oconee and LaSalle PRAs

International Nuclear Information System (INIS)

Wong, S.; Higgins, J.

1991-01-01

This paper describes the comparative analyses of plant risk sensitivity to human errors in the Oconee and La Salle Probabilistic Risk Assessment (PRAs). These analyses were performed to determine the reasons for the observed differences in the sensitivity of core melt frequency (CMF) to changes in human error probabilities (HEPs). Plant-specific design features, PRA methods, and the level of detail and assumptions in the human error modeling were evaluated to assess their influence risk estimates and sensitivities

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.

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

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...

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

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

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.

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

Model-based Recursive Partitioning for Subgroup Analyses

OpenAIRE

Seibold, Heidi; Zeileis, Achim; Hothorn, Torsten

2016-01-01

The identification of patient subgroups with differential treatment effects is the first step towards individualised treatments. A current draft guideline by the EMA discusses potentials and problems in subgroup analyses and formulated challenges to the development of appropriate statistical procedures for the data-driven identification of patient subgroups. We introduce model-based recursive partitioning as a procedure for the automated detection of patient subgroups that are identifiable by...

Beta-Poisson model for single-cell RNA-seq data analyses.

Science.gov (United States)

Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Rantalainen, Mattias; Pawitan, Yudi

2016-07-15

Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ∼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in > 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC CONTACT: yudi.pawitan@ki.se or mattias.rantalainen@ki.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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.

Sensitivity analysis of EQ3

International Nuclear Information System (INIS)

Horwedel, J.E.; Wright, R.Q.; Maerker, R.E.

1990-01-01

A sensitivity analysis of EQ3, a computer code which has been proposed to be used as one link in the overall performance assessment of a national high-level waste repository, has been performed. EQ3 is a geochemical modeling code used to calculate the speciation of a water and its saturation state with respect to mineral phases. The model chosen for the sensitivity analysis is one which is used as a test problem in the documentation of the EQ3 code. Sensitivities are calculated using both the CHAIN and ADGEN options of the GRESS code compiled under G-float FORTRAN on the VAX/VMS and verified by perturbation runs. The analyses were performed with a preliminary Version 1.0 of GRESS which contains several new algorithms that significantly improve the application of ADGEN. Use of ADGEN automates the implementation of the well-known adjoint technique for the efficient calculation of sensitivities of a given response to all the input data. Application of ADGEN to EQ3 results in the calculation of sensitivities of a particular response to 31,000 input parameters in a run time of only 27 times that of the original model. Moreover, calculation of the sensitivities for each additional response increases this factor by only 2.5 percent. This compares very favorably with a running-time factor of 31,000 if direct perturbation runs were used instead. 6 refs., 8 tabs

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.

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

Graphic-based musculoskeletal model for biomechanical analyses and animation.

Science.gov (United States)

Chao, Edmund Y S

2003-04-01

The ability to combine physiology and engineering analyses with computer sciences has opened the door to the possibility of creating the 'Virtual Human' reality. This paper presents a broad foundation for a full-featured biomechanical simulator for the human musculoskeletal system physiology. This simulation technology unites the expertise in biomechanical analysis and graphic modeling to investigate joint and connective tissue mechanics at the structural level and to visualize the results in both static and animated forms together with the model. Adaptable anatomical models including prosthetic implants and fracture fixation devices and a robust computational infrastructure for static, kinematic, kinetic, and stress analyses under varying boundary and loading conditions are incorporated on a common platform, the VIMS (Virtual Interactive Musculoskeletal System). Within this software system, a manageable database containing long bone dimensions, connective tissue material properties and a library of skeletal joint system functional activities and loading conditions are also available and they can easily be modified, updated and expanded. Application software is also available to allow end-users to perform biomechanical analyses interactively. This paper details the design, capabilities, and features of the VIMS development at Johns Hopkins University, an effort possible only through academic and commercial collaborations. Examples using these models and the computational algorithms in a virtual laboratory environment are used to demonstrate the utility of this unique database and simulation technology. This integrated system will impact on medical education, basic research, device development and application, and clinical patient care related to musculoskeletal diseases, trauma, and rehabilitation.

Sensitivity analysis of reactive ecological dynamics.

Science.gov (United States)

Verdy, Ariane; Caswell, Hal

2008-08-01

Ecological systems with asymptotically stable equilibria may exhibit significant transient dynamics following perturbations. In some cases, these transient dynamics include the possibility of excursions away from the equilibrium before the eventual return; systems that exhibit such amplification of perturbations are called reactive. Reactivity is a common property of ecological systems, and the amplification can be large and long-lasting. The transient response of a reactive ecosystem depends on the parameters of the underlying model. To investigate this dependence, we develop sensitivity analyses for indices of transient dynamics (reactivity, the amplification envelope, and the optimal perturbation) in both continuous- and discrete-time models written in matrix form. The sensitivity calculations require expressions, some of them new, for the derivatives of equilibria, eigenvalues, singular values, and singular vectors, obtained using matrix calculus. Sensitivity analysis provides a quantitative framework for investigating the mechanisms leading to transient growth. We apply the methodology to a predator-prey model and a size-structured food web model. The results suggest predator-driven and prey-driven mechanisms for transient amplification resulting from multispecies interactions.

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

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

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.

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.

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

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

Longitudinal Data Analyses Using Linear Mixed Models in SPSS: Concepts, Procedures and Illustrations

Directory of Open Access Journals (Sweden)

Daniel T. L. Shek

2011-01-01

Full Text Available Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes in Hong Kong are presented.

Longitudinal data analyses using linear mixed models in SPSS: concepts, procedures and illustrations.

Science.gov (United States)

Shek, Daniel T L; Ma, Cecilia M S

2011-01-05

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented.

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.

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)

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

Remote Sensing of Seagrass Leaf Area Index and Species: The Capability of a Model Inversion Method Assessed by Sensitivity Analysis and Hyperspectral Data of Florida Bay

Directory of Open Access Journals (Sweden)

John D. Hedley

2017-11-01

Full Text Available The capability for mapping two species of seagrass, Thalassia testudinium and Syringodium filiforme, by remote sensing using a physics based model inversion method was investigated. The model was based on a three-dimensional canopy model combined with a model for the overlying water column. The model included uncertainty propagation based on variation in leaf reflectances, canopy structure, water column properties, and the air-water interface. The uncertainty propagation enabled both a-priori predictive sensitivity analysis of potential capability and the generation of per-pixel error bars when applied to imagery. A primary aim of the work was to compare the sensitivity analysis to results achieved in a practical application using airborne hyperspectral data, to gain insight on the validity of sensitivity analyses in general. Results showed that while the sensitivity analysis predicted a weak but positive discrimination capability for species, in a practical application the relevant spectral differences were extremely small compared to discrepancies in the radiometric alignment of the model with the imagery—even though this alignment was very good. Complex interactions between spectral matching and uncertainty propagation also introduced biases. Ability to discriminate LAI was good, and comparable to previously published methods using different approaches. The main limitation in this respect was spatial alignment with the imagery with in situ data, which was heterogeneous on scales of a few meters. The results provide insight on the limitations of physics based inversion methods and seagrass mapping in general. Complex models can degrade unpredictably when radiometric alignment of the model and imagery is not perfect and incorporating uncertainties can have non-intuitive impacts on method performance. Sensitivity analyses are upper bounds to practical capability, incorporating a term for potential systematic errors in radiometric alignment may

Uncertainty and Sensitivity Analyses for CFD Codes: an Attempt of a State of the Art on the Basis of the CEA Experience

International Nuclear Information System (INIS)

Crecy, Agnes de; Bazin, Pascal

2013-01-01

Uncertainty and sensitivity analyses, associated to best-estimate calculations become paramount for licensing processes and are known as BEPU (Best-Estimate Plus Uncertainties) methods. A recent activity such as the BEMUSE benchmark has shown that the present methods are mature enough for the system thermal-hydraulics codes, even if issues such as the quantification of the uncertainties of the input parameters, and especially, the physical models must be improved. But CFD codes are more and more used for fine 3-D modeling such as, for example, those necessary in dilution or stratification problems. The application of the BEPU methods to CFD codes becomes an issue that must be now addressed. That is precisely the goal of this paper. It consists of two main parts. In the chapter 2, the specificities of CFD codes for BEPU methods are listed, with focuses on the possible difficulties. In the chapter 3, the studies performed at CEA are described. It is important to note that CEA research in this field is only beginning and must not be viewed as a reference approach. (authors)

Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method (ESQM v5.2

Directory of Open Access Journals (Sweden)

T. S. Kalra

2017-12-01

Full Text Available Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST modeling system. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as the Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant stem density, height, and, to a lesser degree, diameter. Wave dissipation is mostly dependent on the variation in plant stem density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance to optimize efforts and reduce exploration of parameter space for future observational and modeling work.

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.

Global and Local Sensitivity Analysis Methods for a Physical System

Science.gov (United States)

Morio, Jerome

2011-01-01

Sensitivity analysis is the study of how the different input variations of a mathematical model influence the variability of its output. In this paper, we review the principle of global and local sensitivity analyses of a complex black-box system. A simulated case of application is given at the end of this paper to compare both approaches.…

Multiple predictor smoothing methods for sensitivity analysis: Example results

International Nuclear Information System (INIS)

Storlie, Curtis B.; Helton, Jon C.

2008-01-01

The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described in the first part of this presentation: (i) locally weighted regression (LOESS), (ii) additive models, (iii) projection pursuit regression, and (iv) recursive partitioning regression. In this, the second and concluding part of the presentation, the indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present

Depletion GPT-free sensitivity analysis for reactor eigenvalue problems

International Nuclear Information System (INIS)

Kennedy, C.; Abdel-Khalik, H.

2013-01-01

This manuscript introduces a novel approach to solving depletion perturbation theory problems without the need to set up or solve the generalized perturbation theory (GPT) equations. The approach, hereinafter denoted generalized perturbation theory free (GPT-Free), constructs a reduced order model (ROM) using methods based in perturbation theory and computes response sensitivity profiles in a manner that is independent of the number or type of responses, allowing for an efficient computation of sensitivities when many responses are required. Moreover, the reduction error from using the ROM is quantified in the GPT-Free approach by means of a Wilks' order statistics error metric denoted the K-metric. Traditional GPT has been recognized as the most computationally efficient approach for performing sensitivity analyses of models with many input parameters, e.g. when forward sensitivity analyses are computationally intractable. However, most neutronics codes that can solve the fundamental (homogenous) adjoint eigenvalue problem do not have GPT capabilities unless envisioned during code development. The GPT-Free approach addresses this limitation by requiring only the ability to compute the fundamental adjoint. This manuscript demonstrates the GPT-Free approach for depletion reactor calculations performed in SCALE6 using the 7x7 UAM assembly model. A ROM is developed for the assembly over a time horizon of 990 days. The approach both calculates the reduction error over the lifetime of the simulation using the K-metric and benchmarks the obtained sensitivities using sample calculations. (authors)

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).

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.

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)

Sensitivity of a carbon and productivity model to climatic, water, terrain, and biophysical parameters in a Rocky Mountain watershed

Energy Technology Data Exchange (ETDEWEB)

Xu, S.; Peddle, D.R.; Coburn, C.A.; Kienzle, S. [Univ. of Lethbridge, Dept. of Geography, Lethbridge, Alberta (Canada)

2008-06-15

Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate-water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter {mu} {+-} 1{sigma}), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha{sup -1}{center_dot}year{sup -1}. This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat

Sensitivity of a carbon and productivity model to climatic, water, terrain, and biophysical parameters in a Rocky Mountain watershed

International Nuclear Information System (INIS)

Xu, S.; Peddle, D.R.; Coburn, C.A.; Kienzle, S.

2008-01-01

Net primary productivity (NPP) is a key component of the terrestrial carbon cycle and is important in ecological, watershed, and forest management studies, and more broadly in global climate change research. Determining the relative importance and magnitude of uncertainty of NPP model inputs is important for proper carbon reporting over larger areas and time periods. This paper presents a systematic evaluation of the boreal ecosystem productivity simulator (BEPS) model in mountainous terrain using an established montane forest test site in Kananaskis, Alberta, in the Canadian Rocky Mountains. Model runs were based on forest (land cover, leaf area index (LAI), biomass) and climate-water inputs (solar radiation, temperature, precipitation, humidity, soil water holding capacity) derived from digital elevation model (DEM) derivatives, climate data, geographical information system (GIS) functions, and topographically corrected satellite imagery. Four sensitivity analyses were conducted as a controlled series of experiments involving (i) NPP individual parameter sensitivity for a full growing season, (ii) NPP independent variation tests (parameter μ ± 1σ), (iii) factorial analyses to assess more complex multiple-factor interactions, and (iv) topographic correction. The results, validated against field measurements, showed that modeled NPP was sensitive to most inputs measured in the study area, with LAI and forest type the most important forest input, and solar radiation the most important climate input. Soil available water holding capacity expressed as a function of wetness index was only significant in conjunction with precipitation when both parameters represented a moisture-deficit situation. NPP uncertainty resulting from topographic influence was equivalent to 140 kg C ha -1 ·year -1 . This suggested that topographic correction of model inputs is important for accurate NPP estimation. The BEPS model, designed originally for flat boreal forests, was shown to be

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.

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

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.

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

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

Multiple predictor smoothing methods for sensitivity analysis: Description of techniques

International Nuclear Information System (INIS)

Storlie, Curtis B.; Helton, Jon C.

2008-01-01

The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (i) locally weighted regression (LOESS), (ii) additive models, (iii) projection pursuit regression, and (iv) recursive partitioning regression. Then, in the second and concluding part of this presentation, the indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present

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...

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.

Sex and smoking sensitive model of radon induced lung cancer

Energy Technology Data Exchange (ETDEWEB)

Zhukovsky, M.; Yarmoshenko, I. [Institute of Industrial Ecology of Ural Branch of Russian Academy of Sciences, Yekaterinburg (Russian Federation)

2006-07-01

Radon and radon progeny inhalation exposure are recognized to cause lung cancer. Only strong evidence of radon exposure health effects was results of epidemiological studies among underground miners. Any single epidemiological study among population failed to find reliable lung cancer risk due to indoor radon exposure. Indoor radon induced lung cancer risk models were developed exclusively basing on extrapolation of miners data. Meta analyses of indoor radon and lung cancer case control studies allowed only little improvements in approaches to radon induced lung cancer risk projections. Valuable data on characteristics of indoor radon health effects could be obtained after systematic analysis of pooled data from single residential radon studies. Two such analyses are recently published. Available new and previous data of epidemiological studies of workers and general population exposed to radon and other sources of ionizing radiation allow filling gaps in knowledge of lung cancer association with indoor radon exposure. The model of lung cancer induced by indoor radon exposure is suggested. The key point of this model is the assumption that excess relative risk depends on both sex and smoking habits of individual. This assumption based on data on occupational exposure by radon and plutonium and also on the data on external radiation exposure in Hiroshima and Nagasaki and the data on external exposure in Mayak nuclear facility. For non-corrected data of pooled European and North American studies the increased sensitivity of females to radon exposure is observed. The mean value of ks for non-corrected data obtained from independent source is in very good agreement with the L.S.S. study and Mayak plutonium workers data. Analysis of corrected data of pooled studies showed little influence of sex on E.R.R. value. The most probable cause of such effect is the change of men/women and smokers/nonsmokers ratios in corrected data sets in North American study. More correct

Sex and smoking sensitive model of radon induced lung cancer

International Nuclear Information System (INIS)

Zhukovsky, M.; Yarmoshenko, I.

2006-01-01

Radon and radon progeny inhalation exposure are recognized to cause lung cancer. Only strong evidence of radon exposure health effects was results of epidemiological studies among underground miners. Any single epidemiological study among population failed to find reliable lung cancer risk due to indoor radon exposure. Indoor radon induced lung cancer risk models were developed exclusively basing on extrapolation of miners data. Meta analyses of indoor radon and lung cancer case control studies allowed only little improvements in approaches to radon induced lung cancer risk projections. Valuable data on characteristics of indoor radon health effects could be obtained after systematic analysis of pooled data from single residential radon studies. Two such analyses are recently published. Available new and previous data of epidemiological studies of workers and general population exposed to radon and other sources of ionizing radiation allow filling gaps in knowledge of lung cancer association with indoor radon exposure. The model of lung cancer induced by indoor radon exposure is suggested. The key point of this model is the assumption that excess relative risk depends on both sex and smoking habits of individual. This assumption based on data on occupational exposure by radon and plutonium and also on the data on external radiation exposure in Hiroshima and Nagasaki and the data on external exposure in Mayak nuclear facility. For non-corrected data of pooled European and North American studies the increased sensitivity of females to radon exposure is observed. The mean value of ks for non-corrected data obtained from independent source is in very good agreement with the L.S.S. study and Mayak plutonium workers data. Analysis of corrected data of pooled studies showed little influence of sex on E.R.R. value. The most probable cause of such effect is the change of men/women and smokers/nonsmokers ratios in corrected data sets in North American study. More correct

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.

Linear regression metamodeling as a tool to summarize and present simulation model results.

Science.gov (United States)

Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M

2013-10-01

Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

Present status of theories and data analyses of mathematical models for carcinogenesis

International Nuclear Information System (INIS)

Kai, Michiaki; Kawaguchi, Isao

2007-01-01

Reviewed are the basic mathematical models (hazard functions), present trend of the model studies and that for radiation carcinogenesis. Hazard functions of carcinogenesis are described for multi-stage model and 2-event model related with cell dynamics. At present, the age distribution of cancer mortality is analyzed, relationship between mutation and carcinogenesis is discussed, and models for colorectal carcinogenesis are presented. As for radiation carcinogenesis, models of Armitage-Doll and of generalized MVK (Moolgavkar, Venson, Knudson, 1971-1990) by 2-stage clonal expansion have been applied to analysis of carcinogenesis in A-bomb survivors, workers in uranium mine (Rn exposure) and smoking doctors in UK and other cases, of which characteristics are discussed. In analyses of A-bomb survivors, models above are applied to solid tumors and leukemia to see the effect, if any, of stage, age of exposure, time progression etc. In miners and smokers, stages of the initiation, promotion and progression in carcinogenesis are discussed on the analyses. Others contain the analyses of workers in Canadian atomic power plant, and of patients who underwent the radiation therapy. Model analysis can help to understand the carcinogenic process in a quantitative aspect rather than to describe the process. (R.T.)

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.

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.

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

Radioecological sensitivity. Danish fallout data revisited

International Nuclear Information System (INIS)

Nielsen, S.P.; Oehlenschlaeger, M.

1999-01-01

Danish fallout data covering four decades are interpreted in terms of radioecological sensitivity. The radioecological sensitivity is the time-integrated radionuclide concentration in an environmental sample from a unit ground deposition (e.g. Bq y kg -1 per Gq m -2 ). The fallout data comprise observed levels of the radionuclides 137 Cs and 90 Sr in precipitation, grass, milk, beef and diet. The data are analysed with different types of radioecological models: traditional UNSCEAR models and more recent dynamic models. The traditional models provide empirical relationships between the annual fallout from precipitation and the annual average levels in grass, milk, beef and diet. The relationships may be derived from spreadsheet calculations. ECOSYS and FARMLAND represent more recent radioecological models, which are available as software for personal computers. These models are more mechanistic and require information on a range of topics, e.g. mode of deposition, nuclide dependent and nuclide independent parameters. The more recent models do not reproduce the fallout data better than the traditional models. But the general features of the more recent models make them suited for prediction of radiological consequences of routine and accidental releases in areas where limited radioecological data are available. The work is part of the NKS/BOK-2.1 project on Important Nordic Food Chains aiming at characterising radioecological sensitivity and variability across the Nordic countries. (au)

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

SVM models for analysing the headstreams of mine water inrush

Energy Technology Data Exchange (ETDEWEB)

Yan Zhi-gang; Du Pei-jun; Guo Da-zhi [China University of Science and Technology, Xuzhou (China). School of Environmental Science and Spatial Informatics

2007-08-15

The support vector machine (SVM) model was introduced to analyse the headstrean of water inrush in a coal mine. The SVM model, based on a hydrogeochemical method, was constructed for recognising two kinds of headstreams and the H-SVMs model was constructed for recognising multi- headstreams. The SVM method was applied to analyse the conditions of two mixed headstreams and the value of the SVM decision function was investigated as a means of denoting the hydrogeochemical abnormality. The experimental results show that the SVM is based on a strict mathematical theory, has a simple structure and a good overall performance. Moreover the parameter W in the decision function can describe the weights of discrimination indices of the headstream of water inrush. The value of the decision function can denote hydrogeochemistry abnormality, which is significant in the prevention of water inrush in a coal mine. 9 refs., 1 fig., 7 tabs.

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

Model-Based Recursive Partitioning for Subgroup Analyses.

Science.gov (United States)

Seibold, Heidi; Zeileis, Achim; Hothorn, Torsten

2016-05-01

The identification of patient subgroups with differential treatment effects is the first step towards individualised treatments. A current draft guideline by the EMA discusses potentials and problems in subgroup analyses and formulated challenges to the development of appropriate statistical procedures for the data-driven identification of patient subgroups. We introduce model-based recursive partitioning as a procedure for the automated detection of patient subgroups that are identifiable by predictive factors. The method starts with a model for the overall treatment effect as defined for the primary analysis in the study protocol and uses measures for detecting parameter instabilities in this treatment effect. The procedure produces a segmented model with differential treatment parameters corresponding to each patient subgroup. The subgroups are linked to predictive factors by means of a decision tree. The method is applied to the search for subgroups of patients suffering from amyotrophic lateral sclerosis that differ with respect to their Riluzole treatment effect, the only currently approved drug for this disease.

On accuracy problems for semi-analytical sensitivity analyses

DEFF Research Database (Denmark)

Pedersen, P.; Cheng, G.; Rasmussen, John

1989-01-01

The semi-analytical method of sensitivity analysis combines ease of implementation with computational efficiency. A major drawback to this method, however, is that severe accuracy problems have recently been reported. A complete error analysis for a beam problem with changing length is carried ou...... pseudo loads in order to obtain general load equilibrium with rigid body motions. Such a method would be readily applicable for any element type, whether analytical expressions for the element stiffnesses are available or not. This topic is postponed for a future study....

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.

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.

Bayesian uncertainty analyses of probabilistic risk models

International Nuclear Information System (INIS)

Pulkkinen, U.

1989-01-01

Applications of Bayesian principles to the uncertainty analyses are discussed in the paper. A short review of the most important uncertainties and their causes is provided. An application of the principle of maximum entropy to the determination of Bayesian prior distributions is described. An approach based on so called probabilistic structures is presented in order to develop a method of quantitative evaluation of modelling uncertainties. The method is applied to a small example case. Ideas for application areas for the proposed method are discussed

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.

The EVEREST project: sensitivity analysis of geological disposal systems

International Nuclear Information System (INIS)

Marivoet, Jan; Wemaere, Isabelle; Escalier des Orres, Pierre; Baudoin, Patrick; Certes, Catherine; Levassor, Andre; Prij, Jan; Martens, Karl-Heinz; Roehlig, Klaus

1997-01-01

The main objective of the EVEREST project is the evaluation of the sensitivity of the radiological consequences associated with the geological disposal of radioactive waste to the different elements in the performance assessment. Three types of geological host formations are considered: clay, granite and salt. The sensitivity studies that have been carried out can be partitioned into three categories according to the type of uncertainty taken into account: uncertainty in the model parameters, uncertainty in the conceptual models and uncertainty in the considered scenarios. Deterministic as well as stochastic calculational approaches have been applied for the sensitivity analyses. For the analysis of the sensitivity to parameter values, the reference technique, which has been applied in many evaluations, is stochastic and consists of a Monte Carlo simulation followed by a linear regression. For the analysis of conceptual model uncertainty, deterministic and stochastic approaches have been used. For the analysis of uncertainty in the considered scenarios, mainly deterministic approaches have been applied

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

Exergetic and thermoeconomic analyses of power plants

International Nuclear Information System (INIS)

Kwak, H.-Y.; Kim, D.-J.; Jeon, J.-S.

2003-01-01

Exergetic and thermoeconomic analyses were performed for a 500-MW combined cycle plant. In these analyses, mass and energy conservation laws were applied to each component of the system. Quantitative balances of the exergy and exergetic cost for each component, and for the whole system was carefully considered. The exergoeconomic model, which represented the productive structure of the system considered, was used to visualize the cost formation process and the productive interaction between components. The computer program developed in this study can determine the production costs of power plants, such as gas- and steam-turbines plants and gas-turbine cogeneration plants. The program can be also be used to study plant characteristics, namely, thermodynamic performance and sensitivity to changes in process and/or component design variables

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.

Ocean acidification over the next three centuries using a simple global climate carbon-cycle model: projections and sensitivities

Energy Technology Data Exchange (ETDEWEB)

Hartin, Corinne A.; Bond-Lamberty, Benjamin; Patel, Pralit; Mundra, Anupriya

2016-08-01

projections and sensitivity analyses, and it is capable of emulating both current observations and large-scale climate models under multiple emission pathways.

Spatiotemporal sensitivity analysis of vertical transport of pesticides in soil

Science.gov (United States)

Environmental fate and transport processes are influenced by many factors. Simulation models that mimic these processes often have complex implementations, which can lead to over-parameterization. Sensitivity analyses are subsequently used to identify critical parameters whose un...

A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses

Science.gov (United States)

Yondo, Raul; Andrés, Esther; Valero, Eusebio

2018-01-01

Full scale aerodynamic wind tunnel testing, numerical simulation of high dimensional (full-order) aerodynamic models or flight testing are some of the fundamental but complex steps in the various design phases of recent civil transport aircrafts. Current aircraft aerodynamic designs have increase in complexity (multidisciplinary, multi-objective or multi-fidelity) and need to address the challenges posed by the nonlinearity of the objective functions and constraints, uncertainty quantification in aerodynamic problems or the restrained computational budgets. With the aim to reduce the computational burden and generate low-cost but accurate models that mimic those full order models at different values of the design variables, Recent progresses have witnessed the introduction, in real-time and many-query analyses, of surrogate-based approaches as rapid and cheaper to simulate models. In this paper, a comprehensive and state-of-the art survey on common surrogate modeling techniques and surrogate-based optimization methods is given, with an emphasis on models selection and validation, dimensionality reduction, sensitivity analyses, constraints handling or infill and stopping criteria. Benefits, drawbacks and comparative discussions in applying those methods are described. Furthermore, the paper familiarizes the readers with surrogate models that have been successfully applied to the general field of fluid dynamics, but not yet in the aerospace industry. Additionally, the review revisits the most popular sampling strategies used in conducting physical and simulation-based experiments in aircraft aerodynamic design. Attractive or smart designs infrequently used in the field and discussions on advanced sampling methodologies are presented, to give a glance on the various efficient possibilities to a priori sample the parameter space. Closing remarks foster on future perspectives, challenges and shortcomings associated with the use of surrogate models by aircraft industrial

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

Groundwater travel time uncertainty analysis: Sensitivity of results to model geometry, and correlations and cross correlations among input parameters

International Nuclear Information System (INIS)

Clifton, P.M.

1984-12-01

The deep basalt formations beneath the Hanford Site are being investigated for the Department of Energy (DOE) to assess their suitability as a host medium for a high level nuclear waste repository. Predicted performance of the proposed repository is an important part of the investigation. One of the performance measures being used to gauge the suitability of the host medium is pre-waste-emplacement groundwater travel times to the accessible environment. Many deterministic analyses of groundwater travel times have been completed by Rockwell and other independent organizations. Recently, Rockwell has completed a preliminary stochastic analysis of groundwater travel times. This document presents analyses that show the sensitivity of the results from the previous stochastic travel time study to: (1) scale of representation of model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross-correlation between transmissivity and effective thickness. 40 refs., 29 figs., 6 tabs

Variance decomposition-based sensitivity analysis via neural networks

International Nuclear Information System (INIS)

Marseguerra, Marzio; Masini, Riccardo; Zio, Enrico; Cojazzi, Giacomo

2003-01-01

This paper illustrates a method for efficiently performing multiparametric sensitivity analyses of the reliability model of a given system. These analyses are of great importance for the identification of critical components in highly hazardous plants, such as the nuclear or chemical ones, thus providing significant insights for their risk-based design and management. The technique used to quantify the importance of a component parameter with respect to the system model is based on a classical decomposition of the variance. When the model of the system is realistically complicated (e.g. by aging, stand-by, maintenance, etc.), its analytical evaluation soon becomes impractical and one is better off resorting to Monte Carlo simulation techniques which, however, could be computationally burdensome. Therefore, since the variance decomposition method requires a large number of system evaluations, each one to be performed by Monte Carlo, the need arises for possibly substituting the Monte Carlo simulation model with a fast, approximated, algorithm. Here we investigate an approach which makes use of neural networks appropriately trained on the results of a Monte Carlo system reliability/availability evaluation to quickly provide with reasonable approximation, the values of the quantities of interest for the sensitivity analyses. The work was a joint effort between the Department of Nuclear Engineering of the Polytechnic of Milan, Italy, and the Institute for Systems, Informatics and Safety, Nuclear Safety Unit of the Joint Research Centre in Ispra, Italy which sponsored the project

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.

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

Analyses and simulations in income frame regulation model for the network sector from 2007

International Nuclear Information System (INIS)

Askeland, Thomas Haave; Fjellstad, Bjoern

2007-01-01

Analyses of the income frame regulation model for the network sector in Norway, introduced 1.st of January 2007. The model's treatment of the norm cost is evaluated, especially the effect analyses carried out by a so called Data Envelopment Analysis model. It is argued that there may exist an age lopsidedness in the data set, and that this should and can be corrected in the effect analyses. The adjustment is proposed corrected for by introducing an age parameter in the data set. Analyses of how the calibration effects in the regulation model affect the business' total income frame, as well as each network company's income frame have been made. It is argued that the calibration, the way it is presented, is not working according to its intention, and should be adjusted in order to provide the sector with the rate of reference in return (ml)

Benchmarking sensitivity of biophysical processes to leaf area changes in land surface models

Science.gov (United States)

Forzieri, Giovanni; Duveiller, Gregory; Georgievski, Goran; Li, Wei; Robestson, Eddy; Kautz, Markus; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

2017-04-01

Land surface models (LSM) are widely applied as supporting tools for policy-relevant assessment of climate change and its impact on terrestrial ecosystems, yet knowledge of their performance skills in representing the sensitivity of biophysical processes to changes in vegetation density is still limited. This is particularly relevant in light of the substantial impacts on regional climate associated with the changes in leaf area index (LAI) following the observed global greening. Benchmarking LSMs on the sensitivity of the simulated processes to vegetation density is essential to reduce their uncertainty and improve the representation of these effects. Here we present a novel benchmark system to assess model capacity in reproducing land surface-atmosphere energy exchanges modulated by vegetation density. Through a collaborative effort of different modeling groups, a consistent set of land surface energy fluxes and LAI dynamics has been generated from multiple LSMs, including JSBACH, JULES, ORCHIDEE, CLM4.5 and LPJ-GUESS. Relationships of interannual variations of modeled surface fluxes to LAI changes have been analyzed at global scale across different climatological gradients and compared with satellite-based products. A set of scoring metrics has been used to assess the overall model performances and a detailed analysis in the climate space has been provided to diagnose possible model errors associated to background conditions. Results have enabled us to identify model-specific strengths and deficiencies. An overall best performing model does not emerge from the analyses. However, the comparison with other models that work better under certain metrics and conditions indicates that improvements are expected to be potentially achievable. A general amplification of the biophysical processes mediated by vegetation is found across the different land surface schemes. Grasslands are characterized by an underestimated year-to-year variability of LAI in cold climates

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.

Uncertainty and Sensitivity Analyses of a Pebble Bed HTGR Loss of Cooling Event

Directory of Open Access Journals (Sweden)

Gerhard Strydom

2013-01-01

Full Text Available The Very High Temperature Reactor Methods Development group at the Idaho National Laboratory identified the need for a defensible and systematic uncertainty and sensitivity approach in 2009. This paper summarizes the results of an uncertainty and sensitivity quantification investigation performed with the SUSA code, utilizing the International Atomic Energy Agency CRP 5 Pebble Bed Modular Reactor benchmark and the INL code suite PEBBED-THERMIX. Eight model input parameters were selected for inclusion in this study, and after the input parameters variations and probability density functions were specified, a total of 800 steady state and depressurized loss of forced cooling (DLOFC transient PEBBED-THERMIX calculations were performed. The six data sets were statistically analyzed to determine the 5% and 95% DLOFC peak fuel temperature tolerance intervals with 95% confidence levels. It was found that the uncertainties in the decay heat and graphite thermal conductivities were the most significant contributors to the propagated DLOFC peak fuel temperature uncertainty. No significant differences were observed between the results of Simple Random Sampling (SRS or Latin Hypercube Sampling (LHS data sets, and use of uniform or normal input parameter distributions also did not lead to any significant differences between these data sets.

Use of flow models to analyse loss of coolant accidents

International Nuclear Information System (INIS)

Pinet, Bernard

1978-01-01

This article summarises current work on developing the use of flow models to analyse loss-of-coolant accident in pressurized-water plants. This work is being done jointly, in the context of the LOCA Technical Committee, by the CEA, EDF and FRAMATOME. The construction of the flow model is very closely based on some theoretical studies of the two-fluid model. The laws of transfer at the interface and at the wall are tested experimentally. The representativity of the model then has to be checked in experiments involving several elementary physical phenomena [fr

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).

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

Recharge is a vital component of the ground-water budget and methods for estimating it range from extremely complex to relatively simple. The most commonly used techniques, however, are limited by the scale of application. One method that can be used to estimate ground-water recharge includes process-based models that compute distributed water budgets on a watershed scale. These models should be evaluated to determine which model parameters are the dominant controls in determining ground-water recharge. Seven existing watershed models from different humid regions of the United States were chosen to analyze the sensitivity of simulated recharge to model parameters. Parameter sensitivities were determined using a nonlinear regression computer program to generate a suite of diagnostic statistics. The statistics identify model parameters that have the greatest effect on simulated ground-water recharge and that compare and contrast the hydrologic system responses to those parameters. Simulated recharge in the Lost River and Big Creek watersheds in Washington State was sensitive to small changes in air temperature. The Hamden watershed model in west-central Minnesota was developed to investigate the relations that wetlands and other landscape features have with runoff processes. Excess soil moisture in the Hamden watershed simulation was preferentially routed to wetlands, instead of to the ground-water system, resulting in little sensitivity of any parameters to recharge. Simulated recharge in the North Fork Pheasant Branch watershed, Wisconsin, demonstrated the greatest sensitivity to parameters related to evapotranspiration. Three watersheds were simulated as part of the Model Parameter Estimation Experiment (MOPEX). Parameter sensitivities for the MOPEX watersheds, Amite River, Louisiana and Mississippi, English River, Iowa, and South Branch Potomac River, West Virginia, were similar and most sensitive to small changes in air temperature and a user-defined flow

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

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

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.

TEMAC, Top Event Sensitivity Analysis

International Nuclear Information System (INIS)

Iman, R.L.; Shortencarier, M.J.

1988-01-01

1 - Description of program or function: TEMAC is designed to permit the user to easily estimate risk and to perform sensitivity and uncertainty analyses with a Boolean expression such as produced by the SETS computer program. SETS produces a mathematical representation of a fault tree used to model system unavailability. In the terminology of the TEMAC program, such a mathematical representation is referred to as a top event. The analysis of risk involves the estimation of the magnitude of risk, the sensitivity of risk estimates to base event probabilities and initiating event frequencies, and the quantification of the uncertainty in the risk estimates. 2 - Method of solution: Sensitivity and uncertainty analyses associated with top events involve mathematical operations on the corresponding Boolean expression for the top event, as well as repeated evaluations of the top event in a Monte Carlo fashion. TEMAC employs a general matrix approach which provides a convenient general form for Boolean expressions, is computationally efficient, and allows large problems to be analyzed. 3 - Restrictions on the complexity of the problem - Maxima of: 4000 cut sets, 500 events, 500 values in a Monte Carlo sample, 16 characters in an event name. These restrictions are implemented through the FORTRAN 77 PARAMATER statement

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.

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

Uncertainty and sensitivity assessments of GPS and GIS integrated applications for transportation.

Science.gov (United States)

Hong, Sungchul; Vonderohe, Alan P

2014-02-10

Uncertainty and sensitivity analysis methods are introduced, concerning the quality of spatial data as well as that of output information from Global Positioning System (GPS) and Geographic Information System (GIS) integrated applications for transportation. In the methods, an error model and an error propagation method form a basis for formulating characterization and propagation of uncertainties. They are developed in two distinct approaches: analytical and simulation. Thus, an initial evaluation is performed to compare and examine uncertainty estimations from the analytical and simulation approaches. The evaluation results show that estimated ranges of output information from the analytical and simulation approaches are compatible, but the simulation approach rather than the analytical approach is preferred for uncertainty and sensitivity analyses, due to its flexibility and capability to realize positional errors in both input data. Therefore, in a case study, uncertainty and sensitivity analyses based upon the simulation approach is conducted on a winter maintenance application. The sensitivity analysis is used to determine optimum input data qualities, and the uncertainty analysis is then applied to estimate overall qualities of output information from the application. The analysis results show that output information from the non-distance-based computation model is not sensitive to positional uncertainties in input data. However, for the distance-based computational model, output information has a different magnitude of uncertainties, depending on position uncertainties in input data.

Sensitivity of Attitude Determination on the Model Assumed for ISAR Radar Mappings

Science.gov (United States)

Lemmens, S.; Krag, H.

2013-09-01

Inverse synthetic aperture radars (ISAR) are valuable instrumentations for assessing the state of a large object in low Earth orbit. The images generated by these radars can reach a sufficient quality to be used during launch support or contingency operations, e.g. for confirming the deployment of structures, determining the structural integrity, or analysing the dynamic behaviour of an object. However, the direct interpretation of ISAR images can be a demanding task due to the nature of the range-Doppler space in which these images are produced. Recently, a tool has been developed by the European Space Agency's Space Debris Office to generate radar mappings of a target in orbit. Such mappings are a 3D-model based simulation of how an ideal ISAR image would be generated by a ground based radar under given processing conditions. These radar mappings can be used to support a data interpretation process. E.g. by processing predefined attitude scenarios during an observation sequence and comparing them with actual observations, one can detect non-nominal behaviour. Vice versa, one can also estimate the attitude states of the target by fitting the radar mappings to the observations. It has been demonstrated for the latter use case that a coarse approximation of the target through an 3D-model is already sufficient to derive the attitude information from the generated mappings. The level of detail required for the 3D-model is determined by the process of generating ISAR images, which is based on the theory of scattering bodies. Therefore, a complex surface can return an intrinsically noisy ISAR image. E.g. when many instruments on a satellite are visible to the observer, the ISAR image can suffer from multipath reflections. In this paper, we will further analyse the sensitivity of the attitude fitting algorithms to variations in the dimensions and the level of detail of the underlying 3D model. Moreover, we investigate the ability to estimate the orientations of different

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

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.

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.

A shock absorber model for structure-borne noise analyses

Science.gov (United States)

Benaziz, Marouane; Nacivet, Samuel; Thouverez, Fabrice

2015-08-01

Shock absorbers are often responsible for undesirable structure-borne noise in cars. The early numerical prediction of this noise in the automobile development process can save time and money and yet remains a challenge for industry. In this paper, a new approach to predicting shock absorber structure-borne noise is proposed; it consists in modelling the shock absorber and including the main nonlinear phenomena responsible for discontinuities in the response. The model set forth herein features: compressible fluid behaviour, nonlinear flow rate-pressure relations, valve mechanical equations and rubber mounts. The piston, base valve and complete shock absorber model are compared with experimental results. Sensitivity of the shock absorber response is evaluated and the most important parameters are classified. The response envelope is also computed. This shock absorber model is able to accurately reproduce local nonlinear phenomena and improves our state of knowledge on potential noise sources within the shock absorber.

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.

USE OF THE SIMPLE LINEAR REGRESSION MODEL IN MACRO-ECONOMICAL ANALYSES

Directory of Open Access Journals (Sweden)

Constantin ANGHELACHE

2011-10-01

Full Text Available The article presents the fundamental aspects of the linear regression, as a toolbox which can be used in macroeconomic analyses. The article describes the estimation of the parameters, the statistical tests used, the homoscesasticity and heteroskedasticity. The use of econometrics instrument in macroeconomics is an important factor that guarantees the quality of the models, analyses, results and possible interpretation that can be drawn at this level.

Social Regulation of Leukocyte Homeostasis: The Role of Glucocorticoid Sensitivity

Science.gov (United States)

Cole, Steve W.

2010-01-01

Recent small-scale genomics analyses suggest that physiologic regulation of pro-inflammatory gene expression by endogenous glucocorticoids may be compromised in individuals who experience chronic social isolation. This could potentially contribute to the elevated prevalence of inflammation-related disease previously observed in social isolates. The present study assessed the relationship between leukocyte distributional sensitivity to glucocorticoid regulation and subjective social isolation in a large population-based sample of older adults. Initial analyses confirmed that circulating neutrophil percentages were elevated, and circulating lymphocyte and monocyte percentages were suppressed, in direct proportion to circulating cortisol levels. However, leukocyte distributional sensitivity to endogenous glucocorticoids was abrogated in individuals reporting either occasional or frequent experiences of subjective social isolation. This finding held in both nonparametric univariate analyses and in multivariate linear models controlling for a variety of biological, social, behavioral, and psychological confounders. The present results suggest that social factors may alter immune cell sensitivity to physiologic regulation by the hypothalamic-pituitary-adrenal axis in ways that could ultimately contribute to the increased physical health risks associated with social isolation. PMID:18394861

A Calculus for Modelling, Simulating and Analysing Compartmentalized Biological Systems

DEFF Research Database (Denmark)

Mardare, Radu Iulian; Ihekwaba, Adoha

2007-01-01

A. Ihekwaba, R. Mardare. A Calculus for Modelling, Simulating and Analysing Compartmentalized Biological Systems. Case study: NFkB system. In Proc. of International Conference of Computational Methods in Sciences and Engineering (ICCMSE), American Institute of Physics, AIP Proceedings, N 2...

Treatment of visceral leishmaniasis: model-based analyses on the spread of antimony-resistant L. donovani in Bihar, India.

Directory of Open Access Journals (Sweden)

Anette Stauch

Full Text Available BACKGROUND: Pentavalent antimonials have been the mainstay of antileishmanial therapy for decades, but increasing failure rates under antimonial treatment have challenged further use of these drugs in the Indian subcontinent. Experimental evidence has suggested that parasites which are resistant against antimonials have superior survival skills than sensitive ones even in the absence of antimonial treatment. METHODS AND FINDINGS: We use simulation studies based on a mathematical L. donovani transmission model to identify parameters which can explain why treatment failure rates under antimonial treatment increased up to 65% in Bihar between 1980 and 1997. Model analyses suggest that resistance to treatment alone cannot explain the observed treatment failure rates. We explore two hypotheses referring to an increased fitness of antimony-resistant parasites: the additional fitness is (i disease-related, by causing more clinical cases (higher pathogenicity or more severe disease (higher virulence, or (ii is transmission-related, by increasing the transmissibility from sand flies to humans or vice versa. CONCLUSIONS: Both hypotheses can potentially explain the Bihar observations. However, increased transmissibility as an explanation appears more plausible because it can occur in the background of asymptomatically transmitted infection whereas disease-related factors would most probably be observable. Irrespective of the cause of fitness, parasites with a higher fitness will finally replace sensitive parasites, even if antimonials are replaced by another drug.

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.

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…

Maladaptive Five Factor Model personality traits associated with Borderline Personality Disorder indirectly affect susceptibility to suicide ideation through increased anxiety sensitivity cognitive concerns.

Science.gov (United States)

Tucker, Raymond P; Lengel, Greg J; Smith, Caitlin E; Capron, Dan W; Mullins-Sweatt, Stephanie N; Wingate, LaRicka R

2016-12-30

The current study investigated the relationship between maladaptive Five-Factor Model (FFM) personality traits, anxiety sensitivity cognitive concerns, and suicide ideation in a sample of 131 undergraduate students who were selected based on their scores on a screening questionnaire regarding Borderline Personality Disorder (BPD) symptoms. Those who endorsed elevated BPD symptoms in a pre-screen analyses completed at the beginning of each semester were oversampled in comparison to those with low or moderate symptoms. Indirect effect (mediation) results indicated that the maladaptive personality traits of anxious/uncertainty, dysregulated anger, self-disturbance, behavioral dysregulation, dissociative tendencies, distrust, manipulativeness, oppositional, and rashness had indirect effects on suicide ideation through anxiety sensitivity cognitive concerns. All of these personality traits correlated to suicide ideation as well. The maladaptive personality traits of despondence, affective dysregulation, and fragility were positive correlates of suicide ideation and predicted suicide ideation when all traits were entered in one linear regression model, but were not indirectly related through anxiety sensitivity cognitive concerns. The implication for targeting anxiety sensitivity cognitive concerns in evidence-based practices for reducing suicide risk in those with BPD is discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Calculating first-order sensitivity measures: A benchmark of some recent methodologies

Energy Technology Data Exchange (ETDEWEB)

Gatelli, D. [Joint Research Centre, European Commission, TP361, Institute of the Protection and Security of the Citizen, Via E. Fermi 2749, 21027 Ispra (Italy)], E-mail: Debora.gatelli@jrc.it; Kucherenko, S. [Imperial College London, London (United Kingdom); Ratto, M.; Tarantola, S. [Joint Research Centre, European Commission, TP361, Institute of the Protection and Security of the Citizen, Via E. Fermi 2749, 21027 Ispra (Italy)

2009-07-15

This work compares three different global sensitivity analysis techniques, namely the state-dependent parameter (SDP) modelling, the random balance designs, and the improved formulas of the Sobol' sensitivity indices. These techniques are not yet commonly known in the literature. Strengths and weaknesses of each technique in terms of efficiency and computational cost are highlighted, thus enabling the user to choose the more suitable method depending on the computational model analysed. Two test functions proposed in the literature are considered. Computational costs and convergence rates for each function are compared and discussed.

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.

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.

[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

Uncertainty and sensitivity analyses of energy and visual performances of office building with external venetian blind shading in hot-dry climate

International Nuclear Information System (INIS)

Singh, Ramkishore; Lazarus, I.J.; Kishore, V.V.N.

2016-01-01

Highlights: • Various alternatives of glazing and venetian blind were simulated for office space. • Daylighting and energy performances were assessed for each alternative. • Large uncertainties were estimated in the energy consumptions and UDI values. • Glazing design parameters were prioritised by performing sensitivity analysis. • WWR, glazing type, blind orientation and slat angle were identified top in priority. - Abstract: Fenestration has become an integral part of the buildings and has a significant impact on the energy and indoor visual performances. Inappropriate design of the fenestration component may lead to low energy efficiency and visual discomfort as a result of high solar and thermal heat gains, excessive daylight and direct sunlight. External venetian blind has been identified as one of the effective shading devices for controlling the heat gains and daylight through fenestration. This study explores uncertainty and sensitivity analyses to identify and prioritize the most influencing parameters for designing glazed components that include external shading devices for office buildings. The study was performed for hot-dry climate of Jodhpur (Latitude 26° 180′N, longitude 73° 010′E) using EnergyPlus, a whole building energy simulation tool providing a large number of inputs for eight façade orientations. A total 150 and 845 data points (for each orientation) for input variables were generated using Hyper Cubic Sampling and extended FAST methods for uncertainty and sensitivity analyses respectively. Results indicated a large uncertainty in the lighting, HVAC, source energy consumptions and useful daylight illuminance (UDI). The estimated coefficients of variation were highest (up to 106%) for UDI, followed by lighting energy (up to 45%) and HVAC energy use (around 33%). The sensitivity analysis identified window to wall ratio, glazing type, blind type (orientation of slats) and slat angle as highly influencing factors for energy and

Application of adjoint sensitivity theory to performance assessment of hydrogeologic concerns

International Nuclear Information System (INIS)

Metcalfe, D.E.; Harper, W.V.

1986-01-01

Sensitivity and uncertainty analyses are important components of performance assessment activities for potential high-level radioactive waste repositories. The application of the adjoint sensitivity technique is demonstrated for the Leadville Limestone in the Paradox Basin, Utah. The adjoint technique is used sequentially to first assist in the calibration of the regional conceptual ground-water flow model to measured potentiometric data. Second, it is used to evaluate the sensitivities of the calculated pressures used to define local scale boundary conditions to regional parameters and boundary conditions

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 ...

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…

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