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)
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.
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.
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.
Model parameters estimation and sensitivity by genetic algorithms
International Nuclear Information System (INIS)
Marseguerra, Marzio; Zio, Enrico; Podofillini, Luca
2003-01-01
In this paper we illustrate the possibility of extracting qualitative information on the importance of the parameters of a model in the course of a Genetic Algorithms (GAs) optimization procedure for the estimation of such parameters. The Genetic Algorithms' search of the optimal solution is performed according to procedures that resemble those of natural selection and genetics: an initial population of alternative solutions evolves within the search space through the four fundamental operations of parent selection, crossover, replacement, and mutation. During the search, the algorithm examines a large amount of solution points which possibly carries relevant information on the underlying model characteristics. A possible utilization of this information amounts to create and update an archive with the set of best solutions found at each generation and then to analyze the evolution of the statistics of the archive along the successive generations. From this analysis one can retrieve information regarding the speed of convergence and stabilization of the different control (decision) variables of the optimization problem. In this work we analyze the evolution strategy followed by a GA in its search for the optimal solution with the aim of extracting information on the importance of the control (decision) variables of the optimization with respect to the sensitivity of the objective function. The study refers to a GA search for optimal estimates of the effective parameters in a lumped nuclear reactor model of literature. The supporting observation is that, as most optimization procedures do, the GA search evolves towards convergence in such a way to stabilize first the most important parameters of the model and later those which influence little the model outputs. In this sense, besides estimating efficiently the parameters values, the optimization approach also allows us to provide a qualitative ranking of their importance in contributing to the model output. The
Sensitivity of numerical dispersion modeling to explosive source parameters
International Nuclear Information System (INIS)
Baskett, R.L.; Cederwall, R.T.
1991-01-01
The calculation of downwind concentrations from non-traditional sources, such as explosions, provides unique challenges to dispersion models. The US Department of Energy has assigned the Atmospheric Release Advisory Capability (ARAC) at the Lawrence Livermore National Laboratory (LLNL) the task of estimating the impact of accidental radiological releases to the atmosphere anywhere in the world. Our experience includes responses to over 25 incidents in the past 16 years, and about 150 exercises a year. Examples of responses to explosive accidents include the 1980 Titan 2 missile fuel explosion near Damascus, Arkansas and the hydrogen gas explosion in the 1986 Chernobyl nuclear power plant accident. Based on judgment and experience, we frequently estimate the source geometry and the amount of toxic material aerosolized as well as its particle size distribution. To expedite our real-time response, we developed some automated algorithms and default assumptions about several potential sources. It is useful to know how well these algorithms perform against real-world measurements and how sensitive our dispersion model is to the potential range of input values. In this paper we present the algorithms we use to simulate explosive events, compare these methods with limited field data measurements, and analyze their sensitivity to input parameters. 14 refs., 7 figs., 2 tabs
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.
Bates, P. D.; Neal, J. C.; Fewtrell, T. J.
2012-12-01
In this we paper we consider two related questions. First, we address the issue of how much physical complexity is necessary in a model in order to simulate floodplain inundation to within validation data error. This is achieved through development of a single code/multiple physics hydraulic model (LISFLOOD-FP) where different degrees of complexity can be switched on or off. Different configurations of this code are applied to four benchmark test cases, and compared to the results of a number of industry standard models. Second we address the issue of how parameter sensitivity and transferability change with increasing complexity using numerical experiments with models of different physical and geometric intricacy. Hydraulic models are a good example system with which to address such generic modelling questions as: (1) they have a strong physical basis; (2) there is only one set of equations to solve; (3) they require only topography and boundary conditions as input data; and (4) they typically require only a single free parameter, namely boundary friction. In terms of complexity required we show that for the problem of sub-critical floodplain inundation a number of codes of different dimensionality and resolution can be found to fit uncertain model validation data equally well, and that in this situation Occam's razor emerges as a useful logic to guide model selection. We find also find that model skill usually improves more rapidly with increases in model spatial resolution than increases in physical complexity, and that standard approaches to testing hydraulic models against laboratory data or analytical solutions may fail to identify this important fact. Lastly, we find that in benchmark testing studies significant differences can exist between codes with identical numerical solution techniques as a result of auxiliary choices regarding the specifics of model implementation that are frequently unreported by code developers. As a consequence, making sound
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 ...
Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.
Jamalian, Samira; Bertram, Christopher D; Richardson, William J; Moore, James E
2013-12-01
Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no effective cure for lymphedema, partly because predictive knowledge of lymphatic system reactions to interventions is lacking. A well-developed model of the system could greatly improve our understanding of its function. Lymphangions, defined as the vessel segment between two valves, are the individual pumping units. Based on our previous lumped-parameter model of a chain of lymphangions, this study aimed to identify the parameters that affect the system output the most using a sensitivity analysis. The system was highly sensitive to minimum valve resistance, such that variations in this parameter caused an order-of-magnitude change in time-average flow rate for certain values of imposed pressure difference. Average flow rate doubled when contraction frequency was increased within its physiological range. Optimum lymphangion length was found to be some 13-14.5 diameters. A peak of time-average flow rate occurred when transmural pressure was such that the pressure-diameter loop for active contractions was centered near maximum passive vessel compliance. Increasing the number of lymphangions in the chain improved the pumping in the presence of larger adverse pressure differences. For a given pressure difference, the optimal number of lymphangions increased with the total vessel length. These results indicate that further experiments to estimate valve resistance more accurately are necessary. The existence of an optimal value of transmural pressure may provide additional guidelines for increasing pumping in areas affected by edema.
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
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.
Directory of Open Access Journals (Sweden)
J. Li
2013-08-01
Full Text Available Proper specification of model parameters is critical to the performance of land surface models (LSMs. Due to high dimensionality and parameter interaction, estimating parameters of an LSM is a challenging task. Sensitivity analysis (SA is a tool that can screen out the most influential parameters on model outputs. In this study, we conducted parameter screening for six output fluxes for the Common Land Model: sensible heat, latent heat, upward longwave radiation, net radiation, soil temperature and soil moisture. A total of 40 adjustable parameters were considered. Five qualitative SA methods, including local, sum-of-trees, multivariate adaptive regression splines, delta test and Morris methods, were compared. The proper sampling design and sufficient sample size necessary to effectively screen out the sensitive parameters were examined. We found that there are 2–8 sensitive parameters, depending on the output type, and about 400 samples are adequate to reliably identify the most sensitive parameters. We also employed a revised Sobol' sensitivity method to quantify the importance of all parameters. The total effects of the parameters were used to assess the contribution of each parameter to the total variances of the model outputs. The results confirmed that global SA methods can generally identify the most sensitive parameters effectively, while local SA methods result in type I errors (i.e., sensitive parameters labeled as insensitive or type II errors (i.e., insensitive parameters labeled as sensitive. Finally, we evaluated and confirmed the screening results for their consistency with the physical interpretation of the model parameters.
Personalization of models with many model parameters: an efficient sensitivity analysis approach.
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.
An approach to measure parameter sensitivity in watershed hydrologic modeling
U.S. Environmental Protection Agency — Abstract Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier...
Heuristic Sensitivity Analysis for Baker's Yeast Model Parameters
Leão, Celina P.; Soares, Filomena O.
2004-01-01
The baker's yeast, essentially composed by living cells of Saccharomyces cerevisiae, used in the bread making and beer industries as a microorganism, has an important industrial role. The simulation procedure represents then a necessary tool to understand clearly the baker's yeast fermentation process. The use of mathematical models based on mass balance equations requires the knowledge of the reaction kinetics, thermodynamics, and transport and physical properties. Models may be more or less...
Emulation of a complex global aerosol model to quantify sensitivity to uncertain parameters
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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
International Nuclear Information System (INIS)
Rout, S.; Mishra, D.G.; Ravi, P.M.; Tripathi, R.M.
2016-01-01
Tritium is one of the radionuclides likely to get released to the environment from Pressurized Heavy Water Reactors. Environmental models are extensively used to quantify the complex environmental transport processes of radionuclides and also to assess the impact to the environment. Model parameters exerting the significant influence on model results are identified through a sensitivity analysis (SA). SA is the study of how the variation (uncertainty) in the output of a mathematical model can be apportioned, qualitatively or quantitatively, to different sources of variation in the input parameters. This study was designed to identify the sensitive model parameters of specific activity model (TRS 1616, IAEA) for environmental transfer of 3 H following release to air and then to vegetation and animal products. Model includes parameters such as air to soil transfer factor (CRs), Tissue Free Water 3 H to Organically Bound 3 H ratio (Rp), Relative humidity (RH), WCP (fractional water content) and WEQp (water equivalent factor) any change in these parameters leads to change in 3 H level in vegetation and animal products consequently change in dose due to ingestion. All these parameters are function of climate and/or plant which change with time, space and species. Estimation of these parameters at every time is a time consuming and also required sophisticated instrumentation. Therefore it is necessary to identify the sensitive parameters and freeze the values of least sensitive parameters at constant values for more accurate estimation of 3 H dose in short time for routine assessment
Quantification of remodeling parameter sensitivity - assessed by a computer simulation model
DEFF Research Database (Denmark)
Thomsen, J.S.; Mosekilde, Li.; Mosekilde, Erik
1996-01-01
We have used a computer simulation model to evaluate the effect of several bone remodeling parameters on vertebral cancellus bone. The menopause was chosen as the base case scenario, and the sensitivity of the model to the following parameters was investigated: activation frequency, formation bal....... However, the formation balance was responsible for the greater part of total mass loss....
Ramadan, Ahmed; Boss, Connor; Choi, Jongeun; Peter Reeves, N; Cholewicki, Jacek; Popovich, John M; Radcliffe, Clark J
2018-07-01
Estimating many parameters of biomechanical systems with limited data may achieve good fit but may also increase 95% confidence intervals in parameter estimates. This results in poor identifiability in the estimation problem. Therefore, we propose a novel method to select sensitive biomechanical model parameters that should be estimated, while fixing the remaining parameters to values obtained from preliminary estimation. Our method relies on identifying the parameters to which the measurement output is most sensitive. The proposed method is based on the Fisher information matrix (FIM). It was compared against the nonlinear least absolute shrinkage and selection operator (LASSO) method to guide modelers on the pros and cons of our FIM method. We present an application identifying a biomechanical parametric model of a head position-tracking task for ten human subjects. Using measured data, our method (1) reduced model complexity by only requiring five out of twelve parameters to be estimated, (2) significantly reduced parameter 95% confidence intervals by up to 89% of the original confidence interval, (3) maintained goodness of fit measured by variance accounted for (VAF) at 82%, (4) reduced computation time, where our FIM method was 164 times faster than the LASSO method, and (5) selected similar sensitive parameters to the LASSO method, where three out of five selected sensitive parameters were shared by FIM and LASSO methods.
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.
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...
Parameter estimation and sensitivity analysis for a mathematical model with time delays of leukemia
Cândea, Doina; Halanay, Andrei; Rǎdulescu, Rodica; Tǎlmaci, Rodica
2017-01-01
We consider a system of nonlinear delay differential equations that describes the interaction between three competing cell populations: healthy, leukemic and anti-leukemia T cells involved in Chronic Myeloid Leukemia (CML) under treatment with Imatinib. The aim of this work is to establish which model parameters are the most important in the success or failure of leukemia remission under treatment using a sensitivity analysis of the model parameters. For the most significant parameters of the model which affect the evolution of CML disease during Imatinib treatment we try to estimate the realistic values using some experimental data. For these parameters, steady states are calculated and their stability is analyzed and biologically interpreted.
Parameter sensitivity and uncertainty of the forest carbon flux model FORUG : a Monte Carlo analysis
Energy Technology Data Exchange (ETDEWEB)
Verbeeck, H.; Samson, R.; Lemeur, R. [Ghent Univ., Ghent (Belgium). Laboratory of Plant Ecology; Verdonck, F. [Ghent Univ., Ghent (Belgium). Dept. of Applied Mathematics, Biometrics and Process Control
2006-06-15
The FORUG model is a multi-layer process-based model that simulates carbon dioxide (CO{sub 2}) and water exchange between forest stands and the atmosphere. The main model outputs are net ecosystem exchange (NEE), total ecosystem respiration (TER), gross primary production (GPP) and evapotranspiration. This study used a sensitivity analysis to identify the parameters contributing to NEE uncertainty in the FORUG model. The aim was to determine if it is necessary to estimate the uncertainty of all parameters of a model to determine overall output uncertainty. Data used in the study were the meteorological and flux data of beech trees in Hesse. The Monte Carlo method was used to rank sensitivity and uncertainty parameters in combination with a multiple linear regression. Simulations were run in which parameters were assigned probability distributions and the effect of variance in the parameters on the output distribution was assessed. The uncertainty of the output for NEE was estimated. Based on the arbitrary uncertainty of 10 key parameters, a standard deviation of 0.88 Mg C per year per NEE was found, which was equal to 24 per cent of the mean value of NEE. The sensitivity analysis showed that the overall output uncertainty of the FORUG model could be determined by accounting for only a few key parameters, which were identified as corresponding to critical parameters in the literature. It was concluded that the 10 most important parameters determined more than 90 per cent of the output uncertainty. High ranking parameters included soil respiration; photosynthesis; and crown architecture. It was concluded that the Monte Carlo technique is a useful tool for ranking the uncertainty of parameters of process-based forest flux models. 48 refs., 2 tabs., 2 figs.
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
Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes
Guerrero, José-Luis; Pernica, Patricia; Wheater, Howard; Mackay, Murray; Spence, Chris
2017-12-01
Lakes might be sentinels of climate change, but the uncertainty in their main feedback to the atmosphere - heat-exchange fluxes - is often not considered within climate models. Additionally, these fluxes are seldom measured, hindering critical evaluation of model output. Analysis of the Canadian Small Lake Model (CSLM), a one-dimensional integral lake model, was performed to assess its ability to reproduce diurnal and seasonal variations in heat fluxes and the sensitivity of simulated fluxes to changes in model parameters, i.e., turbulent transport parameters and the light extinction coefficient (Kd). A C++ open-source software package, Problem Solving environment for Uncertainty Analysis and Design Exploration (PSUADE), was used to perform sensitivity analysis (SA) and identify the parameters that dominate model behavior. The generalized likelihood uncertainty estimation (GLUE) was applied to quantify the fluxes' uncertainty, comparing daily-averaged eddy-covariance observations to the output of CSLM. Seven qualitative and two quantitative SA methods were tested, and the posterior likelihoods of the modeled parameters, obtained from the GLUE analysis, were used to determine the dominant parameters and the uncertainty in the modeled fluxes. Despite the ubiquity of the equifinality issue - different parameter-value combinations yielding equivalent results - the answer to the question was unequivocal: Kd, a measure of how much light penetrates the lake, dominates sensible and latent heat fluxes, and the uncertainty in their estimates is strongly related to the accuracy with which Kd is determined. This is important since accurate and continuous measurements of Kd could reduce modeling uncertainty.
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.
Brange , Charlotte; Smailagic , Amir; Jansson , Anne-Helene; Middleton , Brian; Miller-Larsson , Anna; Taylor , John D.; Silberstein , David S.; Lal , Harbans
2009-01-01
Sensitivity of Disease Parameters to Flexible Budesonide/Formoterol Treatment in an Allergic Rat Model correspondance: Corresponding author. Tel.: +46 46 33 6256; fax: +46 46 33 6624. (Brange, Charlotte) (Brange, Charlotte) AstraZeneca R&D Lund--> , Lund--> - SWEDEN (Brange, Charlotte) AstraZeneca R&D Lund--> , Lund--> - SWEDEN (Brange, Charlotte) AstraZeneca R&D Lun...
Sensitivity Analysis of Input Parameters for a Dynamic Food Chain Model DYNACON
International Nuclear Information System (INIS)
Hwang, Won Tae; Lee, Geun Chang; Han, Moon Hee; Cho, Gyu Seong
2000-01-01
The sensitivity analysis of input parameters for a dynamic food chain model DYNACON was conducted as a function of deposition data for the long-lived radionuclides ( 137 Cs, 90 Sr). Also, the influence of input parameters for the short and long-terms contamination of selected foodstuffs (cereals, leafy vegetables, milk) was investigated. The input parameters were sampled using the LHS technique, and their sensitivity indices represented as PRCC. The sensitivity index was strongly dependent on contamination period as well as deposition data. In case of deposition during the growing stages of plants, the input parameters associated with contamination by foliar absorption were relatively important in long-term contamination as well as short-term contamination. They were also important in short-term contamination in case of deposition during the non-growing stages. In long-term contamination, the influence of input parameters associated with foliar absorption decreased, while the influence of input parameters associated with root uptake increased. These phenomena were more remarkable in case of the deposition of non-growing stages than growing stages, and in case of 90 Sr deposition than 137 Cs deposition. In case of deposition during growing stages of pasture, the input parameters associated with the characteristics of cattle such as feed-milk transfer factor and daily intake rate of cattle were relatively important in contamination of milk
Influence of parameter values on the oscillation sensitivities of two p53-Mdm2 models.
Cuba, Christian E; Valle, Alexander R; Ayala-Charca, Giancarlo; Villota, Elizabeth R; Coronado, Alberto M
2015-09-01
Biomolecular networks that present oscillatory behavior are ubiquitous in nature. While some design principles for robust oscillations have been identified, it is not well understood how these oscillations are affected when the kinetic parameters are constantly changing or are not precisely known, as often occurs in cellular environments. Many models of diverse complexity level, for systems such as circadian rhythms, cell cycle or the p53 network, have been proposed. Here we assess the influence of hundreds of different parameter sets on the sensitivities of two configurations of a well-known oscillatory system, the p53 core network. We show that, for both models and all parameter sets, the parameter related to the p53 positive feedback, i.e. self-promotion, is the only one that presents sizeable sensitivities on extrema, periods and delay. Moreover, varying the parameter set values to change the dynamical characteristics of the response is more restricted in the simple model, whereas the complex model shows greater tunability. These results highlight the importance of the presence of specific network patterns, in addition to the role of parameter values, when we want to characterize oscillatory biochemical systems.
Kouznetsova, I.; Gerhard, J. I.; Mao, X.; Barry, D. A.; Robinson, C.; Brovelli, A.; Harkness, M.; Fisher, A.; Mack, E. E.; Payne, J. A.; Dworatzek, S.; Roberts, J.
2008-12-01
A detailed model to simulate trichloroethene (TCE) dechlorination in anaerobic groundwater systems has been developed and implemented through PHAST, a robust and flexible geochemical modeling platform. The approach is comprehensive but retains flexibility such that models of varying complexity can be used to simulate TCE biodegradation in the vicinity of nonaqueous phase liquid (NAPL) source zones. The complete model considers a full suite of biological (e.g., dechlorination, fermentation, sulfate and iron reduction, electron donor competition, toxic inhibition, pH inhibition), physical (e.g., flow and mass transfer) and geochemical processes (e.g., pH modulation, gas formation, mineral interactions). Example simulations with the model demonstrated that the feedback between biological, physical, and geochemical processes is critical. Successful simulation of a thirty-two-month column experiment with site soil, complex groundwater chemistry, and exhibiting both anaerobic dechlorination and endogenous respiration, provided confidence in the modeling approach. A comprehensive suite of batch simulations was then conducted to estimate the sensitivity of predicted TCE degradation to the 36 model input parameters. A local sensitivity analysis was first employed to rank the importance of parameters, revealing that 5 parameters consistently dominated model predictions across a range of performance metrics. A global sensitivity analysis was then performed to evaluate the influence of a variety of full parameter data sets available in the literature. The modeling study was performed as part of the SABRE (Source Area BioREmediation) project, a public/private consortium whose charter is to determine if enhanced anaerobic bioremediation can result in effective and quantifiable treatment of chlorinated solvent DNAPL source areas. The modelling conducted has provided valuable insight into the complex interactions between processes in the evolving biogeochemical systems
Personalization of models with many model parameters : an efficient sensitivity analysis approach
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
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.
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
Abusam, A.A.A.; Keesman, K.J.; Straten, van G.; Spanjers, H.; Meinema, K.
2001-01-01
This paper demonstrates the application of the factorial sensitivity analysis methodology in studying the influence of variations in stoichiometric, kinetic and operating parameters on the performance indices of an oxidation ditch simulation model (benchmark). Factorial sensitivity analysis
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.
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.
An Investigation on the Sensitivity of the Parameters of Urban Flood Model
M, A. B.; Lohani, B.; Jain, A.
2015-12-01
Global climatic change has triggered weather patterns which lead to heavy and sudden rainfall in different parts of world. The impact of heavy rainfall is severe especially on urban areas in the form of urban flooding. In order to understand the effect of heavy rainfall induced flooding, it is necessary to model the entire flooding scenario more accurately, which is now becoming possible with the availability of high resolution airborne LiDAR data and other real time observations. However, there is not much understanding on the optimal use of these data and on the effect of other parameters on the performance of the flood model. This study aims at developing understanding on these issues. In view of the above discussion, the aim of this study is to (i) understand that how the use of high resolution LiDAR data improves the performance of urban flood model, and (ii) understand the sensitivity of various hydrological parameters on urban flood modelling. In this study, modelling of flooding in urban areas due to heavy rainfall is carried out considering Indian Institute of Technology (IIT) Kanpur, India as the study site. The existing model MIKE FLOOD, which is accepted by Federal Emergency Management Agency (FEMA), is used along with the high resolution airborne LiDAR data. Once the model is setup it is made to run by changing the parameters such as resolution of Digital Surface Model (DSM), manning's roughness, initial losses, catchment description, concentration time, runoff reduction factor. In order to realize this, the results obtained from the model are compared with the field observations. The parametric study carried out in this work demonstrates that the selection of catchment description plays a very important role in urban flood modelling. Results also show the significant impact of resolution of DSM, initial losses and concentration time on urban flood model. This study will help in understanding the effect of various parameters that should be part of a
Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu; Wang, Jing
2015-11-21
Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right, anterior-posterior, and superior-inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation.
International Nuclear Information System (INIS)
Tehrani, Joubin Nasehi; Wang, Jing; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu
2015-01-01
Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney–Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney–Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney–Rivlin material model along left-right, anterior–posterior, and superior–inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation. (paper)
Xi, Qing; Li, Zhao-Fu; Luo, Chuan
2014-05-01
Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.
Li, Wei Bo; Greiter, Matthias; Oeh, Uwe; Hoeschen, Christoph
2011-12-01
The reliability of biokinetic models is essential for the assessment of internal doses and a radiation risk analysis for the public and occupational workers exposed to radionuclides. In the present study, a method for assessing the reliability of biokinetic models by means of uncertainty and sensitivity analysis was developed. In the first part of the paper, the parameter uncertainty was analyzed for two biokinetic models of zirconium (Zr); one was reported by the International Commission on Radiological Protection (ICRP), and one was developed at the Helmholtz Zentrum München-German Research Center for Environmental Health (HMGU). In the second part of the paper, the parameter uncertainties and distributions of the Zr biokinetic models evaluated in Part I are used as the model inputs for identifying the most influential parameters in the models. Furthermore, the most influential model parameter on the integral of the radioactivity of Zr over 50 y in source organs after ingestion was identified. The results of the systemic HMGU Zr model showed that over the first 10 d, the parameters of transfer rates between blood and other soft tissues have the largest influence on the content of Zr in the blood and the daily urinary excretion; however, after day 1,000, the transfer rate from bone to blood becomes dominant. For the retention in bone, the transfer rate from blood to bone surfaces has the most influence out to the endpoint of the simulation; the transfer rate from blood to the upper larger intestine contributes a lot in the later days; i.e., after day 300. The alimentary tract absorption factor (fA) influences mostly the integral of radioactivity of Zr in most source organs after ingestion.
Sensitivity of subject-specific models to Hill muscle-tendon model parameters in simulations of gait
Carbone, V.; Krogt, M.M. van der; Koopman, H.F.J.M.; Verdonschot, N.J.
2016-01-01
Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle-tendon (MT) model parameters for each of
Sensitivity of subject-specific models to Hill muscle-tendon model parameters in simulations of gait
Carbone, Vincenzo; van der Krogt, Marjolein; Koopman, Hubertus F.J.M.; Verdonschot, Nicolaas Jacobus Joseph
2016-01-01
Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle–tendon (MT) model parameters for each of
Directory of Open Access Journals (Sweden)
Jie Bao
2015-12-01
Full Text Available Effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash–Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA approaches, including analysis of variance based on the generalized linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.
He, Li-hong; Wang, Hai-yan; Lei, Xiang-dong
2016-02-01
Model based on vegetation ecophysiological process contains many parameters, and reasonable parameter values will greatly improve simulation ability. Sensitivity analysis, as an important method to screen out the sensitive parameters, can comprehensively analyze how model parameters affect the simulation results. In this paper, we conducted parameter sensitivity analysis of BIOME-BGC model with a case study of simulating net primary productivity (NPP) of Larix olgensis forest in Wangqing, Jilin Province. First, with the contrastive analysis between field measurement data and the simulation results, we tested the BIOME-BGC model' s capability of simulating the NPP of L. olgensis forest. Then, Morris and EFAST sensitivity methods were used to screen the sensitive parameters that had strong influence on NPP. On this basis, we also quantitatively estimated the sensitivity of the screened parameters, and calculated the global, the first-order and the second-order sensitivity indices. The results showed that the BIOME-BGC model could well simulate the NPP of L. olgensis forest in the sample plot. The Morris sensitivity method provided a reliable parameter sensitivity analysis result under the condition of a relatively small sample size. The EFAST sensitivity method could quantitatively measure the impact of simulation result of a single parameter as well as the interaction between the parameters in BIOME-BGC model. The influential sensitive parameters for L. olgensis forest NPP were new stem carbon to new leaf carbon allocation and leaf carbon to nitrogen ratio, the effect of their interaction was significantly greater than the other parameter' teraction effect.
Sensitivity testing practice on pre-processing parameters in hard and soft coupled modeling
Directory of Open Access Journals (Sweden)
Z. Ignaszak
2010-01-01
Full Text Available This paper pays attention to the problem of practical applicability of coupled modeling with the use of hard and soft models types and necessity of adapted to that models data base possession. The data base tests results for cylindrical 30 mm diameter casting made of AlSi7Mg alloy were presented. In simulation tests that were applied the Calcosoft system with CAFE (Cellular Automaton Finite Element module. This module which belongs to „multiphysics” models enables structure prediction of complete casting with division of columnar and equiaxed crystals zones of -phase. Sensitivity tests of coupled model on the particular values parameters changing were made. On these basis it was determined the relations of CET (columnar-to-equaiaxed transition zone position influence. The example of virtual structure validation based on real structure with CET zone location and grain size was shown.
International Nuclear Information System (INIS)
Prindle, R.W.; Hopkins, P.L.
1990-10-01
The Hydrologic Code Intercomparison Project (HYDROCOIN) was formed to evaluate hydrogeologic models and computer codes and their use in performance assessment for high-level radioactive-waste repositories. This report describes the results of a study for HYDROCOIN of model sensitivity for isothermal, unsaturated flow through layered, fractured tuffs. We investigated both the types of flow behavior that dominate the performance measures and the conditions and model parameters that control flow behavior. We also examined the effect of different conceptual models and modeling approaches on our understanding of system behavior. The analyses included single- and multiple-parameter variations about base cases in one-dimensional steady and transient flow and in two-dimensional steady flow. The flow behavior is complex even for the highly simplified and constrained system modeled here. The response of the performance measures is both nonlinear and nonmonotonic. System behavior is dominated by abrupt transitions from matrix to fracture flow and by lateral diversion of flow. The observed behaviors are strongly influenced by the imposed boundary conditions and model constraints. Applied flux plays a critical role in determining the flow type but interacts strongly with the composite-conductivity curves of individual hydrologic units and with the stratigraphy. One-dimensional modeling yields conservative estimates of distributions of groundwater travel time only under very limited conditions. This study demonstrates that it is wrong to equate the shortest possible water-travel path with the fastest path from the repository to the water table. 20 refs., 234 figs., 10 tabs
Parameter sensitivity study of a Field II multilayer transducer model on a convex transducer
DEFF Research Database (Denmark)
Bæk, David; Jensen, Jørgen Arendt; Willatzen, Morten
2009-01-01
A multilayer transducer model for predicting a transducer impulse response has in earlier works been developed and combined with the Field II software. This development was tested on current, voltage, and intensity measurements on piezoceramics discs (Bæk et al. IUS 2008) and a convex 128 element...... ultrasound imaging transducer (Bæk et al. ICU 2009). The model benefits from its 1D simplicity and hasshown to give an amplitude error around 1.7‐2 dB. However, any prediction of amplitude, phase, and attenuation of pulses relies on the accuracy of manufacturer supplied material characteristics, which may...... is a quantitative calibrated model for a complete ultrasound system. This includes a sensitivity study aspresented here.Statement of Contribution/MethodsThe study alters 35 different model parameters which describe a 128 element convex transducer from BK Medical Aps. The changes are within ±20 % of the values...
Energy Technology Data Exchange (ETDEWEB)
Avila Moreno, R.; Barrdahl, R.; Haegg, C.
1995-05-01
The main objective of the present study was to carry out a screening and a sensitivity analysis of the SSI TOOLBOX source term model SOSIM. This model is a part of the SSI TOOLBOX for radiological impact assessment of the Swedish disposal concept for high-level waste KBS-3. The outputs of interest for this purpose were: the total released fraction, the time of total release, the time and value of maximum release rate, the dose rates after direct releases of the biosphere. The source term equations were derived and simple equations and methods were proposed for calculation of these. A literature survey has been performed in order to determine a characteristic variation range and a nominal value for each model parameter. In order to reduce the model uncertainties the authors recommend a change in the initial boundary condition for solution of the diffusion equation for highly soluble nuclides. 13 refs.
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.
Parameter Sensitivity of High–Order Equivalent Circuit Models Of Turbine Generator
Directory of Open Access Journals (Sweden)
T. Niewierowicz–Swiecicka
2010-01-01
Full Text Available This work shows the results of a parametric sensitivity analysis applied to a state–space representation of high–order two–axis equivalent circuits (ECs of a turbo generator (150 MVA, 120 MW, 13.8 kV y 50 Hz. The main purpose of this study is to evaluate each parameter impact on the transient response of the analyzed two–axis models –d–axis ECs with one to five damper branches and q–axis ECs from one to four damper branches–. The parametric sensitivity concept is formulated in a general context and the sensibility function is established from the generator response to a short circuit condition. Results ponder the importance played by each parameter in the model behavior. The algorithms were design within MATLAB® environment. The study gives way to conclusions on electromagnetic aspects of solid rotor synchronous generators that have not been previously studied. The methodology presented here can be applied to any other physical system.
A practical method to assess model sensitivity and parameter uncertainty in C cycle models
Delahaies, Sylvain; Roulstone, Ian; Nichols, Nancy
2015-04-01
The carbon cycle combines multiple spatial and temporal scales, from minutes to hours for the chemical processes occurring in plant cells to several hundred of years for the exchange between the atmosphere and the deep ocean and finally to millennia for the formation of fossil fuels. Together with our knowledge of the transformation processes involved in the carbon cycle, many Earth Observation systems are now available to help improving models and predictions using inverse modelling techniques. A generic inverse problem consists in finding a n-dimensional state vector x such that h(x) = y, for a given N-dimensional observation vector y, including random noise, and a given model h. The problem is well posed if the three following conditions hold: 1) there exists a solution, 2) the solution is unique and 3) the solution depends continuously on the input data. If at least one of these conditions is violated the problem is said ill-posed. The inverse problem is often ill-posed, a regularization method is required to replace the original problem with a well posed problem and then a solution strategy amounts to 1) constructing a solution x, 2) assessing the validity of the solution, 3) characterizing its uncertainty. The data assimilation linked ecosystem carbon (DALEC) model is a simple box model simulating the carbon budget allocation for terrestrial ecosystems. Intercomparison experiments have demonstrated the relative merit of various inverse modelling strategies (MCMC, ENKF) to estimate model parameters and initial carbon stocks for DALEC using eddy covariance measurements of net ecosystem exchange of CO2 and leaf area index observations. Most results agreed on the fact that parameters and initial stocks directly related to fast processes were best estimated with narrow confidence intervals, whereas those related to slow processes were poorly estimated with very large uncertainties. While other studies have tried to overcome this difficulty by adding complementary
International Nuclear Information System (INIS)
Ward, R.C.; Kocher, D.C.; Hicks, B.B.; Hosker, R.P. Jr.; Ku, J.Y.; Rao, K.S.
1985-01-01
We have studied the sensitivity of results from the CRAC2 computer code, which predicts health impacts from a reactor-accident scenario, to uncertainties in selected meteorological models and parameters. The sources of uncertainty examined include the models for plume rise and wet deposition and the meteorological bin-sampling procedure. An alternative plume-rise model usually had little effect on predicted health impacts. In an alternative wet-deposition model, the scavenging rate depends only on storm type, rather than on rainfall rate and atmospheric stability class as in the CRAC2 model. Use of the alternative wet-deposition model in meteorological bin-sampling runs decreased predicted mean early injuries by as much as a factor of 2-3 and, for large release heights and sensible heat rates, decreased mean early fatalities by nearly an order of magnitude. The bin-sampling procedure in CRAC2 was expanded by dividing each rain bin into four bins that depend on rainfall rate. Use of the modified bin structure in conjunction with the CRAC2 wet-deposition model changed all predicted health impacts by less than a factor of 2. 9 references
Directory of Open Access Journals (Sweden)
Dongdong Liu
2014-01-01
Full Text Available This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline and 1960 (Soil B, nonsaline were used, with bulk densities of 1.4 or 1.5 g/cm3. A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent when θ0 was increased. Soil physical quality was described better by the S parameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils.
Liu, Dongdong; She, Dongli; Yu, Shuang'en; Shao, Guangcheng; Chen, Dan
2014-01-01
This study was conducted to assess the influences of soil surface conditions and initial soil water content on water movement in unsaturated sodic soils of reclaimed coastal areas. Data was collected from column experiments in which two soils from a Chinese coastal area reclaimed in 2007 (Soil A, saline) and 1960 (Soil B, nonsaline) were used, with bulk densities of 1.4 or 1.5 g/cm(3). A 1D-infiltration model was created using a finite difference method and its sensitivity to hydraulic related parameters was tested. The model well simulated the measured data. The results revealed that soil compaction notably affected the water retention of both soils. Model simulations showed that increasing the ponded water depth had little effect on the infiltration process, since the increases in cumulative infiltration and wetting front advancement rate were small. However, the wetting front advancement rate increased and the cumulative infiltration decreased to a greater extent when θ₀ was increased. Soil physical quality was described better by the S parameter than by the saturated hydraulic conductivity since the latter was also affected by the physical chemical effects on clay swelling occurring in the presence of different levels of electrolytes in the soil solutions of the two soils.
Liwarska-Bizukojc, Ewa; Biernacki, Rafal
2010-10-01
In order to simulate biological wastewater treatment processes, data concerning wastewater and sludge composition, process kinetics and stoichiometry are required. Selection of the most sensitive parameters is an important step of model calibration. The aim of this work is to verify the predictability of the activated sludge model, which is implemented in BioWin software, and select its most influential kinetic and stoichiometric parameters with the help of sensitivity analysis approach. Two different measures of sensitivity are applied: the normalised sensitivity coefficient (S(i,j)) and the mean square sensitivity measure (delta(j)(msqr)). It occurs that 17 kinetic and stoichiometric parameters of the BioWin activated sludge (AS) model can be regarded as influential on the basis of S(i,j) calculations. Half of the influential parameters are associated with growth and decay of phosphorus accumulating organisms (PAOs). The identification of the set of the most sensitive parameters should support the users of this model and initiate the elaboration of determination procedures for the parameters, for which it has not been done yet. Copyright 2010 Elsevier Ltd. All rights reserved.
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.
Rasul, H.; Wu, M.; Olofsson, B.
2017-12-01
Modelling moisture and heat changes in road layers is very important to understand road hydrology and for better construction and maintenance of roads in a sustainable manner. In cold regions due to the freezing/thawing process in the partially saturated material of roads, the modeling task will become more complicated than simple model of flow through porous media without freezing/thawing pores considerations. This study is presenting a 2-D model simulation for a section of highway with considering freezing/thawing and vapor changes. Partial deferential equations (PDEs) are used in formulation of the model. Parameters are optimized from modelling results based on the measured data from test station on E18 highway near Stockholm. Impacts of phase change considerations in the modelling are assessed by comparing the modeled soil moisture with TDR-measured data. The results show that the model can be used for prediction of water and ice content in different layers of the road and at different seasons. Parameter sensitivities are analyzed by implementing a calibration strategy. In addition, the phase change consideration is evaluated in the modeling process, by comparing the PDE model with another model without considerations of freezing/thawing in roads. The PDE model shows high potential in understanding the moisture dynamics in the road system.
Tehrani, Joubin Nasehi; Yang, Yin; Werner, Rene; Lu, Wei; Low, Daniel; Guo, Xiaohu; Wang, Jing
2015-01-01
Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional com...
Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende
2014-01-01
Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.
Investigations of the sensitivity of a coronal mass ejection model (ENLIL) to solar input parameters
DEFF Research Database (Denmark)
Falkenberg, Thea Vilstrup; Vršnak, B.; Taktakishvili, A.
2010-01-01
Understanding space weather is not only important for satellite operations and human exploration of the solar system but also to phenomena here on Earth that may potentially disturb and disrupt electrical signals. Some of the most violent space weather effects are caused by coronal mass ejections...... (CMEs), but in order to predict the caused effects, we need to be able to model their propagation from their origin in the solar corona to the point of interest, e.g., Earth. Many such models exist, but to understand the models in detail we must understand the primary input parameters. Here we...... investigate the parameter space of the ENLILv2.5b model using the CME event of 25 July 2004. ENLIL is a time‐dependent 3‐D MHD model that can simulate the propagation of cone‐shaped interplanetary coronal mass ejections (ICMEs) through the solar system. Excepting the cone parameters (radius, position...
Shaw, Jeremy A.; Daescu, Dacian N.
2017-08-01
This article presents the mathematical framework to evaluate the sensitivity of a forecast error aspect to the input parameters of a weak-constraint four-dimensional variational data assimilation system (w4D-Var DAS), extending the established theory from strong-constraint 4D-Var. Emphasis is placed on the derivation of the equations for evaluating the forecast sensitivity to parameters in the DAS representation of the model error statistics, including bias, standard deviation, and correlation structure. A novel adjoint-based procedure for adaptive tuning of the specified model error covariance matrix is introduced. Results from numerical convergence tests establish the validity of the model error sensitivity equations. Preliminary experiments providing a proof-of-concept are performed using the Lorenz multi-scale model to illustrate the theoretical concepts and potential benefits for practical applications.
DEFF Research Database (Denmark)
Sayar, N.A.; Chen, B.H.; Lye, G.J.
2009-01-01
In this paper we have used a proposed mathematical model, describing the carbon-carbon bond format ion reaction between beta-hydroxypyruvate and glycolaldehyde to synthesise L-erythrulose, catalysed by the enzyme transketolase, for the analysis of the sensitivity of the process to its kinetic...
Wen, Jessica; Koo, Soh Myoung; Lape, Nancy
2018-02-01
While predictive models of transdermal transport have the potential to reduce human and animal testing, microscopic stratum corneum (SC) model output is highly dependent on idealized SC geometry, transport pathway (transcellular vs. intercellular), and penetrant transport parameters (e.g., compound diffusivity in lipids). Most microscopic models are limited to a simple rectangular brick-and-mortar SC geometry and do not account for variability across delivery sites, hydration levels, and populations. In addition, these models rely on transport parameters obtained from pure theory, parameter fitting to match in vivo experiments, and time-intensive diffusion experiments for each compound. In this work, we develop a microscopic finite element model that allows us to probe model sensitivity to variations in geometry, transport pathway, and hydration level. Given the dearth of experimentally-validated transport data and the wide range in theoretically-predicted transport parameters, we examine the model's response to a variety of transport parameters reported in the literature. Results show that model predictions are strongly dependent on all aforementioned variations, resulting in order-of-magnitude differences in lag times and permeabilities for distinct structure, hydration, and parameter combinations. This work demonstrates that universally predictive models cannot fully succeed without employing experimentally verified transport parameters and individualized SC structures. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
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
van Santen, R.B.; de Swart, H.E.; van Dijk, T.A.G.P.
2011-01-01
An integrated field data-modelling approach is employed to investigate relationships between the wavelength of tidal sand waves and four environmental parameters: tidal current amplitude, water depth, tidal ellipticity and median grain size. From echo sounder data at 23 locations on the Dutch
Chen, Zhuowei; Shi, Liangsheng; Ye, Ming; Zhu, Yan; Yang, Jinzhong
2018-06-01
Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. By using a new variance-based global sensitivity analysis method, this paper identifies important parameters for nitrogen reactive transport with simultaneous consideration of these three uncertainties. A combination of three scenarios of soil temperature and two scenarios of soil moisture creates a total of six scenarios. Four alternative models describing the effect of soil temperature and moisture content are used to evaluate the reduction functions used for calculating actual reaction rates. The results show that for nitrogen reactive transport problem, parameter importance varies substantially among different models and scenarios. Denitrification and nitrification process is sensitive to soil moisture content status rather than to the moisture function parameter. Nitrification process becomes more important at low moisture content and low temperature. However, the changing importance of nitrification activity with respect to temperature change highly relies on the selected model. Model-averaging is suggested to assess the nitrification (or denitrification) contribution by reducing the possible model error. Despite the introduction of biochemical heterogeneity or not, fairly consistent parameter importance rank is obtained in this study: optimal denitrification rate (Kden) is the most important parameter; reference temperature (Tr) is more important than temperature coefficient (Q10); empirical constant in moisture response function (m) is the least important one. Vertical distribution of soil moisture but not temperature plays predominant role controlling nitrogen reaction. This study provides insight into the nitrogen reactive transport modeling and demonstrates an effective strategy of selecting the important parameters when future temperature and soil moisture carry uncertainties or when modelers face with multiple ways of establishing nitrogen
International Nuclear Information System (INIS)
Moon, S-W; Baek, Y-H; Han, M; Rhee, J-K; Kim, S-D; Oh, J-H
2010-01-01
In this paper, we present a simple and reliable technique for determining the small-signal equivalent circuit model parameters of the 0.1 µm metamorphic high electron mobility transistors (MHEMTs) in a millimeter-wave frequency range. The initial eight extrinsic parameters of the MHEMT are extracted using two S-parameter (scattering parameter) sets measured under the pinched-off and zero-biased cold field-effect transistor conditions by avoiding the forward gate biasing. Furthermore, highly calibration-sensitive values of the R s , L s and C pd are optimized by using a gradient optimization method to improve the modeling accuracy. The accuracy enhancement of this procedure is successfully verified with an excellent correlation between the measured and calculated S-parameters up to 65 GHz
Kulasiri, Don; Liang, Jingyi; He, Yao; Samarasinghe, Sandhya
2017-04-21
We investigate the epistemic uncertainties of parameters of a mathematical model that describes the dynamics of CaMKII-NMDAR complex related to memory formation in synapses using global sensitivity analysis (GSA). The model, which was published in this journal, is nonlinear and complex with Ca 2+ patterns with different level of frequencies as inputs. We explore the effects of parameter on the key outputs of the model to discover the most sensitive ones using GSA and partial ranking correlation coefficient (PRCC) and to understand why they are sensitive and others are not based on the biology of the problem. We also extend the model to add presynaptic neurotransmitter vesicles release to have action potentials as inputs of different frequencies. We perform GSA on this extended model to show that the parameter sensitivities are different for the extended model as shown by PRCC landscapes. Based on the results of GSA and PRCC, we reduce the original model to a less complex model taking the most important biological processes into account. We validate the reduced model against the outputs of the original model. We show that the parameter sensitivities are dependent on the inputs and GSA would make us understand the sensitivities and the importance of the parameters. A thorough phenomenological understanding of the relationships involved is essential to interpret the results of GSA and hence for the possible model reduction. Copyright © 2017 Elsevier Ltd. All rights reserved.
Flow analysis with WaSiM-ETH – model parameter sensitivity at different scales
Directory of Open Access Journals (Sweden)
J. Cullmann
2006-01-01
Full Text Available WaSiM-ETH (Gurtz et al., 2001, a widely used water balance simulation model, is tested for its suitability to serve for flow analysis in the context of rainfall runoff modelling and flood forecasting. In this paper, special focus is on the resolution of the process domain in space as well as in time. We try to couple model runs with different calculation time steps in order to reduce the effort arising from calculating the whole flow hydrograph at the hourly time step. We aim at modelling on the daily time step for water balance purposes, switching to the hourly time step whenever high-resolution information is necessary (flood forecasting. WaSiM-ETH is used at different grid resolutions, thus we try to become clear about being able to transfer the model in spatial resolution. We further use two different approaches for the overland flow time calculation within the sub-basins of the test watershed to gain insights about the process dynamics portrayed by the model. Our findings indicate that the model is very sensitive to time and space resolution and cannot be transferred across scales without recalibration.
Marsudi, Hidayat, Noor; Wibowo, Ratno Bagus Edy
2017-12-01
In this article, we present a deterministic model for the transmission dynamics of HIV/AIDS in which condom campaign and antiretroviral therapy are both important for the disease management. We calculate the effective reproduction number using the next generation matrix method and investigate the local and global stability of the disease-free equilibrium of the model. Sensitivity analysis of the effective reproduction number with respect to the model parameters were carried out. Our result shows that efficacy rate of condom campaign, transmission rate for contact with the asymptomatic infective, progression rate from the asymptomatic infective to the pre-AIDS infective, transmission rate for contact with the pre-AIDS infective, ARV therapy rate, proportion of the susceptible receiving condom campaign and proportion of the pre-AIDS receiving ARV therapy are highly sensitive parameters that effect the transmission dynamics of HIV/AIDS infection.
DEFF Research Database (Denmark)
Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen
2011-01-01
Uncertainty derived from one of the process models – such as one-dimensional secondary settling tank (SST) models – can impact the output of the other process models, e.g., biokinetic (ASM1), as well as the integrated wastewater treatment plant (WWTP) models. The model structure and parameter...... and from the last aerobic bioreactor upstream to the SST (Garrett/hydraulic method). For model structure uncertainty, two one-dimensional secondary settling tank (1-D SST) models are assessed, including a first-order model (the widely used Takács-model), in which the feasibility of using measured...... uncertainty of settler models can therefore propagate, and add to the uncertainties in prediction of any plant performance criteria. Here we present an assessment of the relative significance of secondary settling model performance in WWTP simulations. We perform a global sensitivity analysis (GSA) based...
International Nuclear Information System (INIS)
Rempfer, Johannes; Stocker, Thomas F.; Joos, Fortunat; Dutay, Jean-Claude; Siddall, Mark
2011-01-01
The neodymium (Nd) isotopic composition (Nd) of seawater is a quasi-conservative tracer of water mass mixing and is assumed to hold great potential for paleo-oceanographic studies. Here we present a comprehensive approach for the simulation of the two neodymium isotopes 143 Nd, and 144 Nd using the Bern3D model, a low resolution ocean model. The high computational efficiency of the Bern3D model in conjunction with our comprehensive approach allows us to systematically and extensively explore the sensitivity of Nd concentrations and ε Nd to the parametrisation of sources and sinks. Previous studies have been restricted in doing so either by the chosen approach or by computational costs. Our study thus presents the most comprehensive survey of the marine Nd cycle to date. Our model simulates both Nd concentrations as well as ε Nd in good agreement with observations. ε Nd co-varies with salinity, thus underlining its potential as a water mass proxy. Results confirm that the continental margins are required as a Nd source to simulate Nd concentrations and ε Nd consistent with observations. We estimate this source to be slightly smaller than reported in previous studies and find that above a certain magnitude its magnitude affects ε Nd only to a small extent. On the other hand, the parametrisation of the reversible scavenging considerably affects the ability of the model to simulate both, Nd concentrations and ε Nd . Furthermore, despite their small contribution, we find dust and rivers to be important components of the Nd cycle. In additional experiments, we systematically varied the diapycnal diffusivity as well as the Atlantic-to-Pacific freshwater flux to explore the sensitivity of Nd concentrations and its isotopic signature to the strength and geometry of the overturning circulation. These experiments reveal that Nd concentrations and ε Nd are comparatively little affected by variations in diapycnal diffusivity and the Atlantic-to-Pacific freshwater flux
Directory of Open Access Journals (Sweden)
Thomas Cornelissen
2016-05-01
Full Text Available Parameterization of physically based and distributed hydrological models for mesoscale catchments remains challenging because the commonly available data base is insufficient for calibration. In this paper, we parameterize a mesoscale catchment for the distributed model HydroGeoSphere by transferring evapotranspiration parameters calibrated at a highly-equipped headwater catchment in addition to literature data. Based on this parameterization, the sensitivity of the mesoscale catchment to spatial variability in land use, potential evapotranspiration and precipitation and of the headwater catchment to mesoscale soil and land use data was conducted. Simulations of the mesoscale catchment with transferred parameters reproduced daily discharge dynamics and monthly evapotranspiration of grassland, deciduous and coniferous vegetation in a satisfactory manner. Precipitation was the most sensitive input data with respect to total runoff and peak flow rates, while simulated evapotranspiration components and patterns were most sensitive to spatially distributed land use parameterization. At the headwater catchment, coarse soil data resulted in a change in runoff generating processes based on the interplay between higher wetness prior to a rainfall event, enhanced groundwater level rise and accordingly, lower transpiration rates. Our results indicate that the direct transfer of parameters is a promising method to benefit highly equipped simulations of the headwater catchments.
Brange, Charlotte; Smailagic, Amir; Jansson, Anne-Helene; Middleton, Brian; Miller-Larsson, Anna; Taylor, John D; Silberstein, David S; Lal, Harbans
2009-02-01
Clinical studies show that flexible dosing (maintenance and symptom-driven dose adjustments) of budesonide and formoterol (BUD/FORM) improves control of asthma exacerbations as compared to fixed maintenance dosing protocols (maintenance therapy) even when the latter utilize higher BUD/FORM doses. This suggests that dose-response relationships for certain pathobiologic mechanisms in asthma shift over time. Here, we have conducted animal studies to address this issue. (1) To test in an animal asthma-like model whether it is possible to achieve the same or greater pharmacological control over bronchoconstriction and airway/lung inflammation, and with less total drug used, by flexible BUD/FORM dosing (upward adjustment of doses) in association with allergen challenges. (2) To determine whether the benefit requires adjustment of both drug components. Rats sensitized on days 0 and 7 were challenged intratracheally with ovalbumin on days 14 and 21. On days 13-21, rats were treated intratracheally with fixed maintenance or flexible BUD/FORM combinations. On day 22, rats were challenged with methacholine and lungs were harvested for analysis. A flexible BUD/FORM dosing regimen (using 3.3 times less total drug than the fixed maintenance high dose regimen), delivered the same or greater reductions of excised lung gas volume (a measure of gas trapped in lung by bronchoconstriction) and lung weight (a measure of inflammatory oedema). When either BUD or FORM alone was increased on days of challenge, the benefit of the flexible dose upward adjustment was lost. Flexible dosing of the BUD/FORM combination improves the pharmacological inhibition of allergen-induced bronchoconstriction and an inflammatory oedema in an allergic asthma-like rat model.
Huberts, W; de Jonge, C; van der Linden, W P M; Inda, M A; Passera, K; Tordoir, J H M; van de Vosse, F N; Bosboom, E M H
2013-06-01
Decision-making in vascular access surgery for hemodialysis can be supported by a pulse wave propagation model that is able to simulate pressure and flow changes induced by the creation of a vascular access. To personalize such a model, patient-specific input parameters should be chosen. However, the number of input parameters that can be measured in clinical routine is limited. Besides, patient data are compromised with uncertainty. Incomplete and uncertain input data will result in uncertainties in model predictions. In part A, we analyzed how the measurement uncertainty in the input propagates to the model output by means of a sensitivity analysis. Of all 73 input parameters, 16 parameters were identified to be worthwhile to measure more accurately and 51 could be fixed within their measurement uncertainty range, but these latter parameters still needed to be measured. Here, we present a methodology for assessing the model input parameters that can be taken constant and therefore do not need to be measured. In addition, a method to determine the value of this parameter is presented. For the pulse wave propagation model applied to vascular access surgery, six patient-specific datasets were analyzed and it was found that 47 out of 73 parameters can be fixed on a generic value. These model parameters are not important for personalization of the wave propagation model. Furthermore, we were able to determine a generic value for 37 of the 47 fixable model parameters. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Clifton, P.M.
1985-03-01
This study examines the sensitivity of the travel time distribution predicted by a reference case model to (1) scale of representation of the model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross correlations between transmissivity and effective thickness. The basis for the reference model is the preliminary stochastic travel time model previously documented by the Basalt Waste Isolation Project. Results of this study show the following. The variability of the predicted travel times can be adequately represented when the ratio between the size of the zones used to represent the model parameters and the log-transmissivity correlation range is less than about one-fifth. The size of the model domain and the types of boundary conditions can have a strong impact on the distribution of travel times. Longer log-transmissivity correlation ranges cause larger variability in the predicted travel times. Positive cross correlation between transmissivity and effective thickness causes a decrease in the travel time variability. These results demonstrate the need for a sound conceptual model prior to conducting a stochastic travel time analysis
International Nuclear Information System (INIS)
Cho, Dong-Keun; Sun, Gwang-Min; Choi, Jongwon; Hwang, Dong-Hyun; Hwang, Tae-Won; Yang, Ho-Yeon; Park, Dong-Hwan
2011-01-01
The sensitivity of parameters related with reactor physics on the source terms of decommissioning wastes from a CANDU reactor was investigated in order to find a viable, simplified burned core model of a Monte Carlo simulation for decommissioning waste characterization. First, a sensitivity study was performed for the level of nuclide consideration in an irradiated fuel and implicit geometry modeling, the effects of side structural components of the core, and structural supporters for reactive devices. The overall effects for computation memory, calculation time, and accuracy were then investigated with a full-core model. From the results, it was revealed that the level of nuclide consideration and geometry homogenization are not important factors when the ratio of macroscopic neutron absorption cross section (MNAC) relative to a total value exceeded 0.95. The most important factor affecting the neutron flux of the pressure tube was shown to be the structural supporters for reactivity devices, showing an 10% difference. Finally, it was concluded that a bundle-average homogeneous model considering a MNAC of 0.95, which is the simplest model in this study, could be a viable approximate model, with about 25% lower computation memory, 40% faster simulation time, and reasonable engineering accuracy compared with a model with an explicit geometry employing an MNAC of 0.99. (author)
International Nuclear Information System (INIS)
Charpin, C.; Bonnefille, M.; Charrier, A.; Giorla, J.; Holstein, P.A.; Malinie, G.
2000-01-01
Our study is in line with the robustness of the LMJ target and the definition of safety margins. It is based on the determination of the 'acceptable gain', defined as 75% of the nominal gain. We have tested the sensitivity of the gain to physical and numerical parameters in the case of deteriorated implosions, i.e. when implosion conditions are not optimized. Moreover, we have simplified the radiative transport model, which enabled us to save a lot of computing time. All our calculations were done with the Lagrangian code FCI2 in a very simplified configuration. (authors)
Energy Technology Data Exchange (ETDEWEB)
Fields, Laura [Fermilab; Genser, Krzysztof [Fermilab; Hatcher, Robert [Fermilab; Kelsey, Michael [SLAC; Perdue, Gabriel [Fermilab; Wenzel, Hans [Fermilab; Wright, Dennis H. [SLAC; Yarba, Julia [Fermilab
2017-08-21
Geant4 is the leading detector simulation toolkit used in high energy physics to design detectors and to optimize calibration and reconstruction software. It employs a set of carefully validated physics models to simulate interactions of particles with matter across a wide range of interaction energies. These models, especially the hadronic ones, rely largely on directly measured cross-sections and phenomenological predictions with physically motivated parameters estimated by theoretical calculation or measurement. Because these models are tuned to cover a very wide range of possible simulation tasks, they may not always be optimized for a given process or a given material. This raises several critical questions, e.g. how sensitive Geant4 predictions are to the variations of the model parameters, or what uncertainties are associated with a particular tune of a Geant4 physics model, or a group of models, or how to consistently derive guidance for Geant4 model development and improvement from a wide range of available experimental data. We have designed and implemented a comprehensive, modular, user-friendly software toolkit to study and address such questions. It allows one to easily modify parameters of one or several Geant4 physics models involved in the simulation, and to perform collective analysis of multiple variants of the resulting physics observables of interest and comparison against a variety of corresponding experimental data. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. flexible run-time configurable workflow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented and illustrated with results obtained with Geant4 key hadronic models.
DEFF Research Database (Denmark)
Sørensen, Jacob Viborg Tornfeldt; Madsen, Henrik; Madsen, H.
2006-01-01
In applications of data assimilation algorithms, a number of poorly known assimilation parameters usually need to be specified. Hence, the documented success of data assimilation methodologies must rely on a moderate sensitivity to these parameters. This contribution presents a parameter sensitiv...
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
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
DEFF Research Database (Denmark)
Ferrari, A.; Gutierrez, S.; Sin, Gürkan
2016-01-01
A steady state model for a production scale milk drying process was built to help process understanding and optimization studies. It involves a spray chamber and also internal/external fluid beds. The model was subjected to a comprehensive statistical analysis for quality assurance using...
Contreras-Reyes, Eduardo; Garay, Jeremías
2018-01-01
The outer rise is a topographic bulge seaward of the trench at a subduction zone that is caused by bending and flexure of the oceanic lithosphere as subduction commences. The classic model of the flexure of oceanic lithosphere w (x) is a hydrostatic restoring force acting upon an elastic plate at the trench axis. The governing parameters are elastic thickness Te, shear force V0, and bending moment M0. V0 and M0 are unknown variables that are typically replaced by other quantities such as the height of the fore-bulge, wb, and the half-width of the fore-bulge, (xb - xo). However, this method is difficult to implement with the presence of excessive topographic noise around the bulge of the outer rise. Here, we present an alternative method to the classic model, in which lithospheric flexure w (x) is a function of the flexure at the trench axis w0, the initial dip angle of subduction β0, and the elastic thickness Te. In this investigation, we apply a sensitivity analysis to both methods in order to determine the impact of the differing parameters on the solution, w (x). The parametric sensitivity analysis suggests that stable solutions for the alternative approach requires relatively low β0 values (rise bulge. The alternative method is a more suitable approach, assuming that accurate geometric information at the trench axis (i.e., w0 and β0) is available.
Salvati, Agnese; Palme, Massimo; Inostroza, Luis
2017-10-01
Although Urban Heat Island (UHI) is a fundamental effect modifying the urban climate, being widely studied, the relative weight of the parameters involved in its generation is still not clear. This paper investigates the hierarchy of importance of eight parameters responsible for UHI intensity in the Mediterranean context. Sensitivity analyses have been carried out using the Urban Weather Generator model, considering the range of variability of: 1) city radius, 2) urban morphology, 3) tree coverage, 4) anthropogenic heat from vehicles, 5) building’s cooling set point, 6) heat released to canyon from HVAC systems, 7) wall construction properties and 8) albedo of vertical and horizontal surfaces. Results show a clear hierarchy of significance among the considered parameters; the urban morphology is the most important variable, causing a relative change up to 120% of the annual average UHI intensity in the Mediterranean context. The impact of anthropogenic sources of heat such as cooling systems and vehicles is also significant. These results suggest that urban morphology parameters can be used as descriptors of the climatic performance of different urban areas, easing the work of urban planners and designers in understanding a complex physical phenomenon, such as the UHI.
Fang, Z.; Ward, A. L.; Fang, Y.; Yabusaki, S.
2011-12-01
High-resolution geologic models have proven effective in improving the accuracy of subsurface flow and transport predictions. However, many of the parameters in subsurface flow and transport models cannot be determined directly at the scale of interest and must be estimated through inverse modeling. A major challenge, particularly in vadose zone flow and transport, is the inversion of the highly-nonlinear, high-dimensional problem as current methods are not readily scalable for large-scale, multi-process models. In this paper we describe the implementation of a fully automated approach for addressing complex parameter optimization and sensitivity issues on massively parallel multi- and many-core systems. The approach is based on the integration of PNNL's extreme scale Subsurface Transport Over Multiple Phases (eSTOMP) simulator, which uses the Global Array toolkit, with the Beowulf-Cluster inspired parallel nonlinear parameter estimation software, BeoPEST in the MPI mode. In the eSTOMP/BeoPEST implementation, a pre-processor generates all of the PEST input files based on the eSTOMP input file. Simulation results for comparison with observations are extracted automatically at each time step eliminating the need for post-process data extractions. The inversion framework was tested with three different experimental data sets: one-dimensional water flow at Hanford Grass Site; irrigation and infiltration experiment at the Andelfingen Site; and a three-dimensional injection experiment at Hanford's Sisson and Lu Site. Good agreements are achieved in all three applications between observations and simulations in both parameter estimates and water dynamics reproduction. Results show that eSTOMP/BeoPEST approach is highly scalable and can be run efficiently with hundreds or thousands of processors. BeoPEST is fault tolerant and new nodes can be dynamically added and removed. A major advantage of this approach is the ability to use high-resolution geologic models to preserve
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
Directory of Open Access Journals (Sweden)
Li Wang
2017-02-01
Full Text Available The ability to obtain appropriate parameters for an advanced pressurized water reactor (PWR unit model is of great significance for power system analysis. The attributes of that ability include the following: nonlinear relationships, long transition time, intercoupled parameters and difficult obtainment from practical test, posed complexity and difficult parameter identification. In this paper, a model and a parameter identification method for the PWR primary loop system were investigated. A parameter identification process was proposed, using a particle swarm optimization (PSO algorithm that is based on random perturbation (RP-PSO. The identification process included model variable initialization based on the differential equations of each sub-module and program setting method, parameter obtainment through sub-module identification in the Matlab/Simulink Software (Math Works Inc., Natick, MA, USA as well as adaptation analysis for an integrated model. A lot of parameter identification work was carried out, the results of which verified the effectiveness of the method. It was found that the change of some parameters, like the fuel temperature and coolant temperature feedback coefficients, changed the model gain, of which the trajectory sensitivities were not zero. Thus, obtaining their appropriate values had significant effects on the simulation results. The trajectory sensitivities of some parameters in the core neutron dynamic module were interrelated, causing the parameters to be difficult to identify. The model parameter sensitivity could be different, which would be influenced by the model input conditions, reflecting the parameter identifiability difficulty degree for various input conditions.
Huberts, W; de Jonge, C; van der Linden, W P M; Inda, M A; Tordoir, J H M; van de Vosse, F N; Bosboom, E M H
2013-06-01
Previously, a pulse wave propagation model was developed that has potential in supporting decision-making in arteriovenous fistula (AVF) surgery for hemodialysis. To adapt the wave propagation model to personalized conditions, patient-specific input parameters should be available. In clinics, the number of measurable input parameters is limited which results in sparse datasets. In addition, patient data are compromised with uncertainty. These uncertain and incomplete input datasets will result in model output uncertainties. By means of a sensitivity analysis the propagation of input uncertainties into output uncertainty can be studied which can give directions for input measurement improvement. In this study, a computational framework has been developed to perform such a sensitivity analysis with a variance-based method and Monte Carlo simulations. The framework was used to determine the influential parameters of our pulse wave propagation model applied to AVF surgery, with respect to parameter prioritization and parameter fixing. With this we were able to determine the model parameters that have the largest influence on the predicted mean brachial flow and systolic radial artery pressure after AVF surgery. Of all 73 parameters 51 could be fixed within their measurement uncertainty interval without significantly influencing the output, while 16 parameters importantly influence the output uncertainty. Measurement accuracy improvement should thus focus on these 16 influential parameters. The most rewarding are measurement improvements of the following parameters: the mean aortic flow, the aortic windkessel resistance, the parameters associated with the smallest arterial or venous diameters of the AVF in- and outflow tract and the radial artery windkessel compliance. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.
DEFF Research Database (Denmark)
NJOMO WANDJI, Wilfried
: decrease of conservatism level, improvement of design procedures, and development of innovative structural systems that suit well for large wind turbines. The increasing size of the structure introduces new problems that were not present for small structures. These problems include: (i) the preparation...... substructures. In addition to being aggressive, conditions for offshore environments and the associated models are highly uncertain. Appropriate statistical methodologies should be used in order to design robust structures, which are structures whose engineering performance is not significantly affected....... These research areas are differentially implemented through tasks on various wind turbine structures (shaft, jacket, semi-floater, monopile, and grouted joint). In particular the following research questions are answered: How are extreme and fatigue loads on a given structure influenced by the design of other...
Wang, Yuan; Zhang, Na; Yu, Gui-rui
2010-07-01
By using modified carbon-water cycle model EPPML (ecosystem productivity process model for landscape), the carbon absorption and respiration in Qianyanzhou artificial masson pine forest ecosystem in 2003 and 2004 were simulated, and the sensitivity of the model parameters was analyzed. The results showed that EPPML could effectively simulate the carbon cycle process of this ecosystem. The simulated annual values and the seasonal variations of gross primary productivity (GPP), net ecosystem productivity (NEP), and ecosystem respiration (Re) not only fitted well with the measured data, but also reflected the major impacts of extreme weather on carbon flows. The artificial masson pine forest ecosystem in Qianyanzhou was a strong carbon sink in both 2003 and 2004. Due to the coupling of high temperature and severe drought in the growth season in 2003, the carbon absorption in 2003 was lower than that in 2004. The annual NEP in 2003 and 2004 was 481.8 and 516.6 g C x m(-2) x a(-1), respectively. The key climatic factors giving important impacts on the seasonal variations of carbon cycle were solar radiation during early growth season, drought during peak growth season, and precipitation during post-peak growth season. Autotrophic respiration (Ra) and net primary productivity (NPP) had the similar seasonal variations. Soil heterotrophic respiration (Rh) was mainly affected by soil temperature at yearly scale, and by soil water content at monthly scale. During wet growth season, the higher the soil water content, the lower the Rh was; during dry growth season, the higher the precipitation during the earlier two months, the higher the Rh was. The maximum RuBP carboxylation rate at 25 degrees C (Vm25), specific leaf area (SLA), maximum leaf nitrogen content (LNm), average leaf nitrogen content (LN), and conversion coefficient of biomass to carbon (C/B) had the greatest influence on annual NEP. Different carbon cycle process could have different responses to sensitive
Energy Technology Data Exchange (ETDEWEB)
Moriyama, Kiyofumi; Park, Hyun Sun, E-mail: hejsunny@postech.ac.kr; Hwang, Byoungcheol; Jung, Woo Hyun
2016-06-15
Highlights: • Application of JASMINE code to melt jet breakup and coolability in APR1400 condition. • Coolability indexes for quasi steady state breakup and cooling process. • Typical case in complete breakup/solidification, film boiling quench not reached. • Significant impact of water depth and melt jet size; weak impact of model parameters. - Abstract: The breakup of a melt jet falling in a water pool and the coolability of the melt particles produced by such jet breakup are important phenomena in terms of the mitigation of severe accident consequences in light water reactors, because the molten and relocated core material is the primary heat source that governs the accident progression. We applied a modified version of the fuel–coolant interaction simulation code, JASMINE, developed at Japan Atomic Energy Agency (JAEA) to a plant scale simulation of melt jet breakup and cooling assuming an ex-vessel condition in the APR1400, a Korean advanced pressurized water reactor. Also, we examined the sensitivity on seven model parameters and five initial/boundary condition variables. The results showed that the melt cooling performance of a 6 m deep water pool in the reactor cavity is enough for removing the initial melt enthalpy for solidification, for a melt jet of 0.2 m initial diameter. The impacts of the model parameters were relatively weak and that of some of the initial/boundary condition variables, namely the water depth and melt jet diameter, were very strong. The present model indicated that a significant fraction of the melt jet is not broken up and forms a continuous melt pool on the containment floor in cases with a large melt jet diameter, 0.5 m, or a shallow water pool depth, ≤3 m.
Zhang, Y. Y.; Shao, Q. X.; Ye, A. Z.; Xing, H. T.; Xia, J.
2016-02-01
Integrated water system modeling is a feasible approach to understanding severe water crises in the world and promoting the implementation of integrated river basin management. In this study, a classic hydrological model (the time variant gain model: TVGM) was extended to an integrated water system model by coupling multiple water-related processes in hydrology, biogeochemistry, water quality, and ecology, and considering the interference of human activities. A parameter analysis tool, which included sensitivity analysis, autocalibration and model performance evaluation, was developed to improve modeling efficiency. To demonstrate the model performances, the Shaying River catchment, which is the largest highly regulated and heavily polluted tributary of the Huai River basin in China, was selected as the case study area. The model performances were evaluated on the key water-related components including runoff, water quality, diffuse pollution load (or nonpoint sources) and crop yield. Results showed that our proposed model simulated most components reasonably well. The simulated daily runoff at most regulated and less-regulated stations matched well with the observations. The average correlation coefficient and Nash-Sutcliffe efficiency were 0.85 and 0.70, respectively. Both the simulated low and high flows at most stations were improved when the dam regulation was considered. The daily ammonium-nitrogen (NH4-N) concentration was also well captured with the average correlation coefficient of 0.67. Furthermore, the diffuse source load of NH4-N and the corn yield were reasonably simulated at the administrative region scale. This integrated water system model is expected to improve the simulation performances with extension to more model functionalities, and to provide a scientific basis for the implementation in integrated river basin managements.
Directory of Open Access Journals (Sweden)
Nita Suhartini
2010-06-01
Full Text Available A study of soil erosion rates had been done on a slightly and long slope of cultivated area in Ciawi - Bogor, using 137Cs technique. The objective of the present study was to evaluate the applicability of the 137Cs technique in obtaining spatially distributed information of soil redistribution at small catchment. This paper reports the result of the choice of conversion model for erosion rate estimates and the sensitive of the changes in the model parameter. For this purpose, small site was selected, namely landuse I (LU-I. The top of a slope was chosen as a reference site. The erosion/deposit rate of individual sampling points was estimated using the conversion models, namely Proportional Model (PM, Mass Balance Model 1 (MBM1 and Mass Balance Model 2 (MBM2. A comparison of the conversion models showed that the lowest value is obtained by the PM. The MBM1 gave values closer to MBM2, but MBM2 gave a reliable values. In this study, a sensitivity analysis suggest that the conversion models are sensitive to changes in parameters that depend on the site conditions, but insensitive to changes in parameters that interact to the onset of 137Cs fallout input. Keywords: soil erosion, environmental radioisotope, cesium
Field-sensitivity To Rheological Parameters
Freund, Jonathan; Ewoldt, Randy
2017-11-01
We ask this question: where in a flow is a quantity of interest Q quantitatively sensitive to the model parameters θ-> describing the rheology of the fluid? This field sensitivity is computed via the numerical solution of the adjoint flow equations, as developed to expose the target sensitivity δQ / δθ-> (x) via the constraint of satisfying the flow equations. Our primary example is a sphere settling in Carbopol, for which we have experimental data. For this Carreau-model configuration, we simultaneously calculate how much a local change in the fluid intrinsic time-scale λ, limit-viscosities ηo and η∞, and exponent n would affect the drag D. Such field sensitivities can show where different fluid physics in the model (time scales, elastic versus viscous components, etc.) are important for the target observable and generally guide model refinement based on predictive goals. In this case, the computational cost of solving the local sensitivity problem is negligible relative to the flow. The Carreau-fluid/sphere example is illustrative; the utility of field sensitivity is in the design and analysis of less intuitive flows, for which we provide some additional examples.
PERFORMANCE EVALUATION AND PARAMETERS SENSITIVITY ...
Indian Academy of Sciences (India)
86
wetland (242.21 km2), Malaysia using MIKE SHE distributed model while coupling ..... the ponding water which may lead to rise in the water table level. ..... catchment; and Ds = 2.09 mm represents the amount of depression storages over the ...
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.
Energy Technology Data Exchange (ETDEWEB)
Ibsen, Lars Bo; Liingaard, M.
2006-12-15
A lumped-parameter model represents the frequency dependent soil-structure interaction of a massless foundation placed on or embedded into an unbounded soil domain. In this technical report the steps of establishing a lumped-parameter model are presented. Following sections are included in this report: Static and dynamic formulation, Simple lumped-parameter models and Advanced lumped-parameter models. (au)
Fujimura, Kazumasa; Iseri, Yoshihiko; Kanae, Shinjiro; Murakami, Masahiro
2014-05-01
Accurate estimation of low flow can contribute to better water resources management and also lead to more reliable evaluation of climate change impacts on water resources. In the early study, the nonlinearity of low flow related to the storage in the basin was suggested by Horton (1937) as the exponential function of Q=KSN, where Q is the discharge, S is the storage, K is a constant and N is the exponent value. In the recent study by Ding (2011) showed the general storage-discharge equation of Q = KNSN. Since the constant K is defined as the fractional recession constant and symbolized as Au by Ando et al. (1983), in this study, we rewrite this equation as Qg=AuNSgN, where Qg is the groundwater runoff and Sg is the groundwater storage. Although this equation was applied to a short-term runoff event of less than 14 hours using the unit hydrograph method by Ding, it was not yet applied for a long-term runoff event including low flow more than 10 years. This study performed a sensitive analysis of two parameters of the constant Au and exponent value N by using the hourly hydrological model for two mountainous basins in Japan. The hourly hydrological model used in this study was presented by Fujimura et al. (2012), which comprise the Diskin-Nazimov infiltration model, groundwater recharge and groundwater runoff calculations, and a direct runoff component. The study basins are the Sameura Dam basin (SAME basin) (472 km2) located in the western Japan which has variability of rainfall, and the Shirakawa Dam basin (SIRA basin) (205km2) located in a region of heavy snowfall in the eastern Japan, that are different conditions of climate and geology. The period of available hourly data for the SAME basin is 20 years from 1 January 1991 to 31 December 2010, and for the SIRA basin is 10 years from 1 October 2003 to 30 September 2013. In the sensitive analysis, we prepared 19900 sets of the two parameters of Au and N, the Au value ranges from 0.0001 to 0.0100 in steps of 0
Directory of Open Access Journals (Sweden)
Silvério Rosa
2018-02-01
Full Text Available A state wide Human Respiratory Syncytial Virus (HRSV surveillance system was implemented in Florida in 1999 to support clinical decision-making for prophylaxis of premature infants. The research presented in this paper addresses the problem of fitting real data collected by the Florida HRSV surveillance system by using a periodic SEIRS mathematical model. A sensitivity and cost-effectiveness analysis of the model is done and an optimal control problem is formulated and solved with treatment as the control variable.
Harvey, Natalie J.; Huntley, Nathan; Dacre, Helen F.; Goldstein, Michael; Thomson, David; Webster, Helen
2018-01-01
Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME) to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations for a small operational
Directory of Open Access Journals (Sweden)
N. J. Harvey
2018-01-01
Full Text Available Following the disruption to European airspace caused by the eruption of Eyjafjallajökull in 2010 there has been a move towards producing quantitative predictions of volcanic ash concentration using volcanic ash transport and dispersion simulators. However, there is no formal framework for determining the uncertainties of these predictions and performing many simulations using these complex models is computationally expensive. In this paper a Bayesian linear emulation approach is applied to the Numerical Atmospheric-dispersion Modelling Environment (NAME to better understand the influence of source and internal model parameters on the simulator output. Emulation is a statistical method for predicting the output of a computer simulator at new parameter choices without actually running the simulator. A multi-level emulation approach is applied using two configurations of NAME with different numbers of model particles. Information from many evaluations of the computationally faster configuration is combined with results from relatively few evaluations of the slower, more accurate, configuration. This approach is effective when it is not possible to run the accurate simulator many times and when there is also little prior knowledge about the influence of parameters. The approach is applied to the mean ash column loading in 75 geographical regions on 14 May 2010. Through this analysis it has been found that the parameters that contribute the most to the output uncertainty are initial plume rise height, mass eruption rate, free tropospheric turbulence levels and precipitation threshold for wet deposition. This information can be used to inform future model development and observational campaigns and routine monitoring. The analysis presented here suggests the need for further observational and theoretical research into parameterisation of atmospheric turbulence. Furthermore it can also be used to inform the most important parameter perturbations
Directory of Open Access Journals (Sweden)
Sílvia N. M. Yanagi
2011-12-01
Full Text Available This study evaluates the sensitivity of the surface albedo simulated by the Integrated Biosphere Simulator (IBIS to a set of Amazonian tropical rainforest canopy architectural and optical parameters. The parameters tested in this study are the orientation and reflectance of the leaves of upper and lower canopies in the visible (VIS and near-infrared (NIR spectral bands. The results are evaluated against albedo measurements taken above the K34 site at the INPA (Instituto Nacional de Pesquisas da Amazônia Cuieiras Biological Reserve. The sensitivity analysis indicates a strong response to the upper canopy leaves orientation (x up and to the reflectivity in the near-infrared spectral band (rNIR,up, a smaller sensitivity to the reflectivity in the visible spectral band (rVIS,up and no sensitivity at all to the lower canopy parameters, which is consistent with the canopy structure. The combination of parameters that minimized the Root Mean Square Error and mean relative error are Xup = 0.86, rVIS,up = 0.062 and rNIR,up = 0.275. The parameterizations performed resulted in successful simulations of tropical rainforest albedo by IBIS, indicating its potential to simulate the canopy radiative transfer for narrow spectral bands and permitting close comparison with remote sensing products.Este estudo avalia a sensibilidade do albedo da superfície pelo Simulador Integrado da Biosfera (IBIS a um conjunto de parâmetros que representam algumas propriedades arquitetônicas e óticas do dossel da floresta tropical Amazônica. Os parâmetros testados neste estudo são a orientação e refletância das folhas do dossel superior e inferior nas bandas espectrais do visível (VIS e infravermelho próximo (NIR. Os resultados são avaliados contra observações feitas no sítio K34 pertencente ao Instituto Nacional de Pesquisas da Amazônia (INPA na Reserva Biológica de Cuieiras. A análise de sensibilidade indica uma forte resposta aos parâmetros de orienta
International Nuclear Information System (INIS)
Iman, R.L.; Davenport, J.M.; Waddell, R.K.; Stephens, H.P.; Leap, D.I.
1979-01-01
Statistical methodology has been applied to the investigation of the regional hydrologic systems of a large area encompassing the Nevada Test Site (NTS) as a part of the overall evaluation of the NTS for deep geologic disposal of nuclear waste. Statistical techniques including Latin hypercube sampling were used to perform a sensitivity analysis on a two-dimensional finite-element code of 16 geohydrologic zones used to model the regional ground-water flow system. The Latin hypercube sample has been modified to include correlations between corresponding variables from zone to zone. From the results of sensitivity analysis it was found that: (1) the ranking of the relative importance of input variables between locations within the same geohydrologic zone were similar, but not identical; and (2) inclusion of a correlation structure for input variables had a significant effect on the ranking of their relative importance. The significance of these results is discussed with respect to the hydrology of the region
Qian, Y.; Wang, C.; Huang, M.; Berg, L. K.; Duan, Q.; Feng, Z.; Shrivastava, M. B.; Shin, H. H.; Hong, S. Y.
2016-12-01
This study aims to quantify the relative importance and uncertainties of different physical processes and parameters in affecting simulated surface fluxes and land-atmosphere coupling strength over the Amazon region. We used two-legged coupling metrics, which include both terrestrial (soil moisture to surface fluxes) and atmospheric (surface fluxes to atmospheric state or precipitation) legs, to diagnose the land-atmosphere interaction and coupling strength. Observations made using the Department of Energy's Atmospheric Radiation Measurement (ARM) Mobile Facility during the GoAmazon field campaign together with satellite and reanalysis data are used to evaluate model performance. To quantify the uncertainty in physical parameterizations, we performed a 120 member ensemble of simulations with the WRF model using a stratified experimental design including 6 cloud microphysics, 3 convection, 6 PBL and surface layer, and 3 land surface schemes. A multiple-way analysis of variance approach is used to quantitatively analyze the inter- and intra-group (scheme) means and variances. To quantify parameter sensitivity, we conducted an additional 256 WRF simulations in which an efficient sampling algorithm is used to explore the multiple-dimensional parameter space. Three uncertainty quantification approaches are applied for sensitivity analysis (SA) of multiple variables of interest to 20 selected parameters in YSU PBL and MM5 surface layer schemes. Results show consistent parameter sensitivity across different SA methods. We found that 5 out of 20 parameters contribute more than 90% total variance, and first-order effects dominate comparing to the interaction effects. Results of this uncertainty quantification study serve as guidance for better understanding the roles of different physical processes in land-atmosphere interactions, quantifying model uncertainties from various sources such as physical processes, parameters and structural errors, and providing insights for
Scapin, M; Peroni, M
2011-01-01
The main objective of this paper is getting strain-hardening, thermal and strain-rate parameters for a material model in order to correctly reproduce the deformation process that occurs in high strain-rate scenario, in which the material reaches also high levels of plastic deformation and temperature. In particular, in this work the numerical inverse method is applied to extract material strength parameters from experimental data obtained via mechanical tests at different strain-rates (from quasi-static loading to high strain-rate) and temperatures (between 20 C and 1000 C) for an alumina dispersion strengthened copper material, which commercial name is GLIDCOP. Thanks to its properties GLIDCOP finds several applications in particle accelerator technologies, where problems of thermal management, combined with structural requirements, play a key role. Currently, it is used for the construction of structural and functional parts of the particle beam collimation system. Since the extreme condition in which the m...
A sensitivity analysis approach to optical parameters of scintillation detectors
International Nuclear Information System (INIS)
Ghal-Eh, N.; Koohi-Fayegh, R.
2008-01-01
In this study, an extended version of the Monte Carlo light transport code, PHOTRACK, has been used for a sensitivity analysis to estimate the importance of different wavelength-dependent parameters in the modelling of light collection process in scintillators
Sanz, E.; Voss, C.I.
2006-01-01
Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data. Covariance analysis of the Henry problem indicates that in order to generally reduce variance of parameter estimates, the ideal places to measure pressure are as far away from the coast as possible, at any depth, and the ideal places to measure concentration are near the bottom of the aquifer between the center of the transition zone and its inland fringe. These observations are located in and near high-sensitivity regions of system parameters, which may be identified in a sensitivity analysis with respect to several parameters. However, both the form of error distribution in the observations and the observation weights impact the spatial sensitivity distributions, and different choices for error distributions or weights can result in significantly different regions of high sensitivity. Thus, in order to design effective sampling networks, the error form and weights must be carefully considered. For the Henry problem, permeability and freshwater inflow can be estimated with low estimation variance from only pressure or only
Yang, Ben; Qian, Yun; Berg, Larry K.; Ma, Po-Lun; Wharton, Sonia; Bulaevskaya, Vera; Yan, Huiping; Hou, Zhangshuan; Shaw, William J.
2017-01-01
We evaluate the sensitivity of simulated turbine-height wind speeds to 26 parameters within the Mellor-Yamada-Nakanishi-Niino (MYNN) planetary boundary-layer scheme and MM5 surface-layer scheme of the Weather Research and Forecasting model over an area of complex terrain. An efficient sampling algorithm and generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of simulated turbine-height wind speeds. The results indicate that most of the variability in the ensemble simulations is due to parameters related to the dissipation of turbulent kinetic energy (TKE), Prandtl number, turbulent length scales, surface roughness, and the von Kármán constant. The parameter associated with the TKE dissipation rate is found to be most important, and a larger dissipation rate produces larger hub-height wind speeds. A larger Prandtl number results in smaller nighttime wind speeds. Increasing surface roughness reduces the frequencies of both extremely weak and strong airflows, implying a reduction in the variability of wind speed. All of the above parameters significantly affect the vertical profiles of wind speed and the magnitude of wind shear. The relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability.
de Lima Neves Seefelder, Carolina; Mergili, Martin
2016-04-01
We use the software tools r.slope.stability and TRIGRS to produce factor of safety and slope failure susceptibility maps for the Quitite and Papagaio catchments, Rio de Janeiro, Brazil. The key objective of the work consists in exploring the sensitivity of the geotechnical (r.slope.stability) and geohydraulic (TRIGRS) parameterization on the model outcomes in order to define suitable parameterization strategies for future slope stability modelling. The two landslide-prone catchments Quitite and Papagaio together cover an area of 4.4 km², extending between 12 and 995 m a.s.l. The study area is dominated by granitic bedrock and soil depths of 1-3 m. Ranges of geotechnical and geohydraulic parameters are derived from literature values. A landslide inventory related to a rainfall event in 1996 (250 mm in 48 hours) is used for model evaluation. We attempt to identify those combinations of effective cohesion and effective internal friction angle yielding the best correspondence with the observed landslide release areas in terms of the area under the ROC Curve (AUCROC), and in terms of the fraction of the area affected by the release of landslides. Thereby we test multiple parameter combinations within defined ranges to derive the slope failure susceptibility (fraction of tested parameter combinations yielding a factor of safety smaller than 1). We use the tool r.slope.stability (comparing the infinite slope stability model and an ellipsoid-based sliding surface model) to test and to optimize the geotechnical parameters, and TRIGRS (a coupled hydraulic-infinite slope stability model) to explore the sensitivity of the model results to the geohydraulic parameters. The model performance in terms of AUCROC is insensitive to the variation of the geotechnical parameterization within much of the tested ranges. Assuming fully saturated soils, r.slope.stability produces rather conservative predictions, whereby the results yielded with the sliding surface model are more
Energy Technology Data Exchange (ETDEWEB)
Staudt, Christian; Kaiser, Jan Christian [Helmholtz Zentrum Muenchen, Institute of Radiation Protection, Munich (Germany); Proehl, Gerhard [International Atomic Energy Agency, Division of Radiation, Transport and Waste Safety, Wagramerstrasse 5, 1400 Vienna (Austria)
2014-07-01
Radioecological models are used to assess the exposure of hypothetical populations to radionuclides. Potential radionuclide sources are deep geological repositories for high level radioactive waste. Assessment time frames are long since releases from those repositories are only expected in the far future, and radionuclide migration to the geosphere biosphere interface will take additional time. Due to the long time frames, climate conditions at the repository site will change, leading to changing exposure pathways and model parameters. To identify climate dependent changes in exposure in the far field of a deep geological repository a range of reference biosphere models representing climate analogues for potential future climate states at a German site were developed. In this approach, model scenarios are developed for different contemporary climate states. It is assumed that the exposure pathways and parameters of the contemporary biosphere in the far field of the repository will change to be similar to those at the analogue sites. Since current climate models cannot predict climate developments over the assessment time frame of 1 million years, analogues for a range of realistically possible future climate conditions were selected. These climate states range from steppe to permafrost climate. As model endpoint Biosphere Dose conversion factors (BDCF) are calculated. The radionuclide specific BDCF describe the exposure of a population to radionuclides entering the biosphere in near surface ground water. The BDCF are subject to uncertainties in the exposure pathways and model parameters. In the presented work, probabilistic and sensitivity analysis was used to assess the influence of model parameter uncertainties on the BDCF and the relevance of individual parameters for the model result. This was done for the long half-live radionuclides Cs-135, I-129 and U-238. In addition to this, BDCF distributions for nine climate reference regions and several scenarios were
Sensitivity analysis in multi-parameter probabilistic systems
International Nuclear Information System (INIS)
Walker, J.R.
1987-01-01
Probabilistic methods involving the use of multi-parameter Monte Carlo analysis can be applied to a wide range of engineering systems. The output from the Monte Carlo analysis is a probabilistic estimate of the system consequence, which can vary spatially and temporally. Sensitivity analysis aims to examine how the output consequence is influenced by the input parameter values. Sensitivity analysis provides the necessary information so that the engineering properties of the system can be optimized. This report details a package of sensitivity analysis techniques that together form an integrated methodology for the sensitivity analysis of probabilistic systems. The techniques have known confidence limits and can be applied to a wide range of engineering problems. The sensitivity analysis methodology is illustrated by performing the sensitivity analysis of the MCROC rock microcracking model
Parameter uncertainty effects on variance-based sensitivity analysis
International Nuclear Information System (INIS)
Yu, W.; Harris, T.J.
2009-01-01
In the past several years there has been considerable commercial and academic interest in methods for variance-based sensitivity analysis. The industrial focus is motivated by the importance of attributing variance contributions to input factors. A more complete understanding of these relationships enables companies to achieve goals related to quality, safety and asset utilization. In a number of applications, it is possible to distinguish between two types of input variables-regressive variables and model parameters. Regressive variables are those that can be influenced by process design or by a control strategy. With model parameters, there are typically no opportunities to directly influence their variability. In this paper, we propose a new method to perform sensitivity analysis through a partitioning of the input variables into these two groupings: regressive variables and model parameters. A sequential analysis is proposed, where first an sensitivity analysis is performed with respect to the regressive variables. In the second step, the uncertainty effects arising from the model parameters are included. This strategy can be quite useful in understanding process variability and in developing strategies to reduce overall variability. When this method is used for nonlinear models which are linear in the parameters, analytical solutions can be utilized. In the more general case of models that are nonlinear in both the regressive variables and the parameters, either first order approximations can be used, or numerically intensive methods must be used
Sensitivity of Footbridge Vibrations to Stochastic Walking Parameters
DEFF Research Database (Denmark)
Pedersen, Lars; Frier, Christian
2010-01-01
of the pedestrian. A stochastic modelling approach is adopted for this paper and it facilitates quantifying the probability of exceeding various vibration levels, which is useful in a discussion of serviceability of a footbridge design. However, estimates of statistical distributions of footbridge vibration levels...... to walking loads might be influenced by the models assumed for the parameters of the load model (the walking parameters). The paper explores how sensitive estimates of the statistical distribution of vertical footbridge response are to various stochastic assumptions for the walking parameters. The basis...... for the study is a literature review identifying different suggestions as to how the stochastic nature of these parameters may be modelled, and a parameter study examines how the different models influence estimates of the statistical distribution of footbridge vibrations. By neglecting scatter in some...
Energy Technology Data Exchange (ETDEWEB)
Aslam, Tariq Dennis [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-10-03
A reactive ow model for the tri-amino-tri-nitro-benzene (TATB) based plastic bonded explosive PBX 9502 is presented. This newly devised model is based primarily on the shock temperature of the material, along with local pressure, and accurately models a broader range of detonation and initiation scenarios. The equation of state for the reactants and products, as well as the thermodynamic closure of pressure and temperature equilibration are carried over from the Wescott-Stewart-Davis (WSD) model7,8. Thus, modifying an existing WSD model in a hydrocode should be rather straightforward.
Van Bockstal, Pieter-Jan; Mortier, Séverine Thérèse F C; Corver, Jos; Nopens, Ingmar; Gernaey, Krist V; De Beer, Thomas
2018-02-01
Pharmaceutical batch freeze-drying is commonly used to improve the stability of biological therapeutics. The primary drying step is regulated by the dynamic settings of the adaptable process variables, shelf temperature T s and chamber pressure P c . Mechanistic modelling of the primary drying step leads to the optimal dynamic combination of these adaptable process variables in function of time. According to Good Modelling Practices, a Global Sensitivity Analysis (GSA) is essential for appropriate model building. In this study, both a regression-based and variance-based GSA were conducted on a validated mechanistic primary drying model to estimate the impact of several model input parameters on two output variables, the product temperature at the sublimation front T i and the sublimation rate ṁ sub . T s was identified as most influential parameter on both T i and ṁ sub , followed by P c and the dried product mass transfer resistance α Rp for T i and ṁ sub , respectively. The GSA findings were experimentally validated for ṁ sub via a Design of Experiments (DoE) approach. The results indicated that GSA is a very useful tool for the evaluation of the impact of different process variables on the model outcome, leading to essential process knowledge, without the need for time-consuming experiments (e.g., DoE). Copyright © 2017 Elsevier B.V. All rights reserved.
Tudela, Ignacio; Bonete, Pedro; Fullana, Andres; Conesa, Juan Antonio
2011-01-01
The unreacted-core shrinking (UCS) model is employed to characterize fluid-particle reactions that are important in industry and research. An approach to understand the UCS model by numerical methods is presented, which helps the visualization of the influence of the variables that control the overall heterogeneous process. Use of this approach in…
Eldyasti, Ahmed; Nakhla, George; Zhu, Jesse
2012-05-01
Biofilm models are valuable tools for process engineers to simulate biological wastewater treatment. In order to enhance the use of biofilm models implemented in contemporary simulation software, model calibration is both necessary and helpful. The aim of this work was to develop a calibration protocol of the particulate biofilm model with a help of the sensitivity analysis of the most important parameters in the biofilm model implemented in BioWin® and verify the predictability of the calibration protocol. A case study of a circulating fluidized bed bioreactor (CFBBR) system used for biological nutrient removal (BNR) with a fluidized bed respirometric study of the biofilm stoichiometry and kinetics was used to verify and validate the proposed calibration protocol. Applying the five stages of the biofilm calibration procedures enhanced the applicability of BioWin®, which was capable of predicting most of the performance parameters with an average percentage error (APE) of 0-20%. Copyright Â© 2012 Elsevier Ltd. All rights reserved.
Liu, Ke; Zeng, Xiangmiao; Qiao, Lei; Li, Xisheng; Yang, Yubo; Dai, Cuihong; Hou, Aiju; Xu, Dechang
2014-01-01
The excessive production of lactic acid by L. bulgaricus during yogurt storage is a phenomenon we are always tried to prevent. The methods used in industry either control the post-acidification inefficiently or kill the probiotics in yogurt. Genetic methods of changing the activity of one enzyme related to lactic acid metabolism make the bacteria short of energy to growth, although they are efficient ways in controlling lactic acid production. A model of pH-induced promoter regulation on the production of lactic acid by L. bulgaricus was built. The modelled lactic acid metabolism without pH-induced promoter regulation fitted well with wild type L. bulgaricus (R2LAC = 0.943, R2LA = 0.942). Both the local sensitivity analysis and Sobol sensitivity analysis indicated parameters Tmax, GR, KLR, S, V0, V1 and dLR were sensitive. In order to guide the future biology experiments, three adjustable parameters, KLR, V0 and V1, were chosen for further simulations. V0 had little effect on lactic acid production if the pH-induced promoter could be well induced when pH decreased to its threshold. KLR and V1 both exhibited great influence on the producing of lactic acid. The proposed method of introducing a pH-induced promoter to regulate a repressor gene could restrain the synthesis of lactic acid if an appropriate strength of promoter and/or an appropriate strength of ribosome binding sequence (RBS) in lacR gene has been designed.
International Nuclear Information System (INIS)
Kato, Tomoko; Makino, Hitoshi; Uchida, Masahiro; Suzuki, Yuji
2004-01-01
In the safety assessment of the deep geological disposal system of the high-level radioactive waste (HLW), biosphere assessment is often necessary to estimate future radiological impacts on human beings (e.g. radiation dose). In order to estimate the dose, the surface environment (biosphere) into which future releases of radionuclides might occur and the associated future human behaviour needs to be considered. However, for a deep repository, such releases might not occur for many thousands of years after disposal. Over such timescales, it is impossible to predict with any certainty how the biosphere and human behaviour will evolve. To avoid endless speculation aimed at reducing such uncertainty, the 'Reference Biospheres' concept has been developed for use in the safety assessment of HLW disposal. As the aim of the safety assessment with a hypothetical HLW disposal system by JNC was to demonstrate the technical feasibility and reliability of the Japanese disposal concept for a range of geological and surface environments, some biosphere models were developed using the 'Reference Biospheres' concept and the BIOMASS Methodology. These models have been used to derive factors to convert the radionuclide flux from a geosphere to a biosphere into a dose (flux to dose conversion factors). Moreover, sensitivity analysis for parameters in the biosphere models was performed to evaluate and understand the relative importance of parameters. It was concluded that transport parameters in the surface environments, annual amount of food consumption, distribution coefficients on soils and sediments, transfer coefficients of radionuclides to animal products and concentration ratios for marine organisms would have larger influence on the flux to dose conversion factors than any other parameters. (author)
Williams, J. E.; van der Swaluw, E.; de Vries, W. J.; Sauter, F. J.; van Pul, W. A. J.; Hoogerbrugge, R.
2015-08-01
We present a parameterization developed to simulate Ammonium particle (NH4+) concentrations in the Operational Priority Substances (OPS) source-receptor model, without the necessity of using a detailed chemical scheme. By using the ratios of the main pre-cursor gases SO2, NO2 and NH3, and utilising calculations performed using a chemical box-model, we show that the parameterization can simulate annual mean NH4+ concentration fields to within ∼15% of measured values at locations throughout the Netherlands. Performing simulations for different decades, we find a strong correlation of simulated NH4+ distributions for both past (1993-1995) and present (2009-2012) time periods. Although the total concentration of NH4+ has decreased over the period, we find that the fraction of NH4+ transported into the Netherlands has increased from around 40% in the past to 50% for present-day. This is due to the variable efficiency of mitigation practises across economic sectors. Performing simulations for the year 2020 using associated emission estimates, we show that there are generally decreases of ∼8-25% compared to present day concentrations. By altering the meteorological fields applied in the future simulations, we show that a significant uncertainty of between ∼50 and 100% exists on this estimated NH4+ distribution as a result of variability in the temperature dependent emission terms and relative humidity. Therefore, any projections of future NH4+ distributions should be performed using well chosen meteorological fields representing recent meteorological situations.
Estimation of parameter sensitivities for stochastic reaction networks
Gupta, Ankit
2016-01-07
Quantification of the effects of parameter uncertainty is an important and challenging problem in Systems Biology. We consider this problem in the context of stochastic models of biochemical reaction networks where the dynamics is described as a continuous-time Markov chain whose states represent the molecular counts of various species. For such models, effects of parameter uncertainty are often quantified by estimating the infinitesimal sensitivities of some observables with respect to model parameters. The aim of this talk is to present a holistic approach towards this problem of estimating parameter sensitivities for stochastic reaction networks. Our approach is based on a generic formula which allows us to construct efficient estimators for parameter sensitivity using simulations of the underlying model. We will discuss how novel simulation techniques, such as tau-leaping approximations, multi-level methods etc. can be easily integrated with our approach and how one can deal with stiff reaction networks where reactions span multiple time-scales. We will demonstrate the efficiency and applicability of our approach using many examples from the biological literature.
An International Workshop on Uncertainty, Sensitivity, and Parameter Estimation for Multimedia Environmental Modeling was held August 1921, 2003, at the U.S. Nuclear Regulatory Commission Headquarters in Rockville, Maryland, USA. The workshop was organized and convened by the Fe...
Pattern statistics on Markov chains and sensitivity to parameter estimation
Directory of Open Access Journals (Sweden)
Nuel Grégory
2006-10-01
Full Text Available Abstract Background: In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,.... Results: In the particular case where pattern statistics (overlap counting only computed through binomial approximations we use the delta-method to give an explicit expression of σ, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. Conclusion: We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation.
Accuracy and sensitivity analysis on seismic anisotropy parameter estimation
Yan, Fuyong; Han, De-Hua
2018-04-01
There is significant uncertainty in measuring the Thomsen’s parameter δ in laboratory even though the dimensions and orientations of the rock samples are known. It is expected that more challenges will be encountered in the estimating of the seismic anisotropy parameters from field seismic data. Based on Monte Carlo simulation of vertical transversely isotropic layer cake model using the database of laboratory anisotropy measurement from the literature, we apply the commonly used quartic non-hyperbolic reflection moveout equation to estimate the seismic anisotropy parameters and test its accuracy and sensitivities to the source-receive offset, vertical interval velocity error and time picking error. The testing results show that the methodology works perfectly for noise-free synthetic data with short spread length. However, this method is extremely sensitive to the time picking error caused by mild random noises, and it requires the spread length to be greater than the depth of the reflection event. The uncertainties increase rapidly for the deeper layers and the estimated anisotropy parameters can be very unreliable for a layer with more than five overlain layers. It is possible that an isotropic formation can be misinterpreted as a strong anisotropic formation. The sensitivity analysis should provide useful guidance on how to group the reflection events and build a suitable geological model for anisotropy parameter inversion.
International Nuclear Information System (INIS)
Carlson, David J.; Stewart, Robert D.; Semenenko, Vladimir A.
2006-01-01
The poor treatment prognosis for tumors with high levels of hypoxia is usually attributed to the decreased sensitivity of hypoxic cells to ionizing radiation. Mechanistic considerations suggest that linear quadratic (LQ) survival model radiosensitivity parameters for hypoxic (H) and aerobic (A) cells are related by α H =α A /oxygen enhancement ratio (OER) and (α/β) H =OER(α/β) A . The OER parameter may be interpreted as the ratio of the dose to the hypoxic cells to the dose to the aerobic cells required to produce the same number of DSBs per cell. The validity of these expressions is tested against survival data for mammalian cells irradiated in vitro with low- and high-LET radiation. Estimates of hypoxic and aerobic radiosensitivity parameters are derived from independent and simultaneous least-squares fits to the survival data. An external bootstrap procedure is used to test whether independent fits to the survival data give significantly better predictions than simultaneous fits to the aerobic and hypoxic data. For low-LET radiation, estimates of the OER derived from the in vitro data are between 2.3 and 3.3 for extreme levels of hypoxia. The estimated range for the OER is similar to the oxygen enhancement ratios reported in the literature for the initial yield of DSBs. The half-time for sublethal damage repair was found to be independent of oxygen concentration. Analysis of patient survival data for cervix cancer suggests an average OER less than or equal to 1.5, which corresponds to a pO 2 of 5 mm Hg (0.66%) in the in vitro experiments. Because the OER derived from the cervix cancer data is averaged over cells at all oxygen levels, cells irradiated in vivo under extreme levels of hypoxia (<0.5 mm Hg) may have an OER substantially higher than 1.5. The reported analyses of in vitro data, as well as mechanistic considerations, provide strong support for the expressions relating hypoxic and aerobic radiosensitivity parameters. The formulas are also useful
Energy Technology Data Exchange (ETDEWEB)
Lopez Garcia, I.; Escalera Perez, R. [Universidad Autonoma Metropolitana - Azcapotzalco (Mexico)]. E-mail: irvinlopez@yahoo.com; r.escalera@ieee.org; Niewierowicz Swiecicka, T. [Instituto Politecnico Nacional, U.P. Adolfo Lopez Mateos (Mexico)]. E-mail: tniewi@ipn.mx; Campero Littlewood, E.[Universidad Autonoma Metropolitana - Azcapotzalco (Mexico)]. E-mail: ecl@correo.azc.uam.mx
2010-01-15
This work shows the results of a parametric sensitivity analysis applied to a state-space representation of high-order two-axis equivalent circuits (Ecs) of a turbo generator (150 MVA, 120 MW, 13.8 kV y 50 Hz). The main purpose of this study is to evaluate each parameter impact on the transient response of the analyzed two axis models -d axis Ecs with one to five damper branches and q axis Ecs from one to four damper branches-. The parametric sensitivity concept is formulated in a general context and the sensibility function is established from the generator response to a short circuit condition. Results ponder the importance played by each parameter in the model behavior. The algorithms were design within MATLAB environment. The study gives way to conclusion on electromagnetic aspects of solid rotor synchronous generators that have not been previously studied. The methodology presented here can be applied to any other physical system. [Spanish] En este trabajo se presentan los resultados del analisis de sensibilidad parametrica realizado a modelos de circuitos equivalentes de orden superior de un turbogenerador (150 MVA, 120 MW, 13.8 kV y 50 Hz). La representacion del generador sincrono se hace en el espacio de estados, utilizando la teoria de dos ejes (d y a). El objetivo del estudio de sensibilidad es evaluar el impacto que tiene cada uno de los parametros en la respuesta transitoria de los modelos analizados -circuitos equivalentes desde una hasta cinco ramas de amortiguamiento en el eje d y de una a cuatro ramas en el eje q-. En este trabajo el concepto de sensibilidad parametrica se formula en terminos generales, planteando la funcion de sensibilidad a partir de condiciones de cortocircuito en las terminales del generador. Los resultados se presentan senalando el nivel de importancia de cada parametro en el comportamiento del modelo. Los algoritmos utilizados fueron disenados en MATLAB. Asi, este estudio permite inferir aspectos electromagneticos de los
Directory of Open Access Journals (Sweden)
Brahim Tighilet
Full Text Available Vestibular disorders, by inducing significant posturo-locomotor and cognitive disorders, can significantly impair the most basic tasks of everyday life. Their precise diagnosis is essential to implement appropriate therapeutic countermeasures. Monitoring their evolution is also very important to validate or, on the contrary, to adapt the undertaken therapeutic actions. To date, the diagnosis methods of posturo-locomotor impairments are restricted to examinations that most often lack sensitivity and precision. In the present work we studied the alterations of the dynamic weight distribution in a rodent model of sudden and complete unilateral vestibular loss. We used a system of force sensors connected to a data analysis system to quantify in real time and in an automated way the weight bearing of the animal on the ground. We show here that sudden, unilateral, complete and permanent loss of the vestibular inputs causes a severe alteration of the dynamic ground weight distribution of vestibulo lesioned rodents. Characteristics of alterations in the dynamic weight distribution vary over time and follow the sequence of appearance and disappearance of the various symptoms that compose the vestibular syndrome. This study reveals for the first time that dynamic weight bearing is a very sensitive parameter for evaluating posturo-locomotor function impairment. Associated with more classical vestibular examinations, this paradigm can considerably enrich the methods for assessing and monitoring vestibular disorders. Systematic application of this type of evaluation to the dizzy or unstable patient could improve the detection of vestibular deficits and allow predicting better their impact on posture and walk. Thus it could also allow a better follow-up of the therapeutic approaches for rehabilitating gait and balance.
Tighilet, Brahim; Péricat, David; Frelat, Alais; Cazals, Yves; Rastoldo, Guillaume; Boyer, Florent; Dumas, Olivier; Chabbert, Christian
2017-01-01
Vestibular disorders, by inducing significant posturo-locomotor and cognitive disorders, can significantly impair the most basic tasks of everyday life. Their precise diagnosis is essential to implement appropriate therapeutic countermeasures. Monitoring their evolution is also very important to validate or, on the contrary, to adapt the undertaken therapeutic actions. To date, the diagnosis methods of posturo-locomotor impairments are restricted to examinations that most often lack sensitivity and precision. In the present work we studied the alterations of the dynamic weight distribution in a rodent model of sudden and complete unilateral vestibular loss. We used a system of force sensors connected to a data analysis system to quantify in real time and in an automated way the weight bearing of the animal on the ground. We show here that sudden, unilateral, complete and permanent loss of the vestibular inputs causes a severe alteration of the dynamic ground weight distribution of vestibulo lesioned rodents. Characteristics of alterations in the dynamic weight distribution vary over time and follow the sequence of appearance and disappearance of the various symptoms that compose the vestibular syndrome. This study reveals for the first time that dynamic weight bearing is a very sensitive parameter for evaluating posturo-locomotor function impairment. Associated with more classical vestibular examinations, this paradigm can considerably enrich the methods for assessing and monitoring vestibular disorders. Systematic application of this type of evaluation to the dizzy or unstable patient could improve the detection of vestibular deficits and allow predicting better their impact on posture and walk. Thus it could also allow a better follow-up of the therapeutic approaches for rehabilitating gait and balance.
ECOS - analysis of sensitivity to database and input parameters
International Nuclear Information System (INIS)
Sumerling, T.J.; Jones, C.H.
1986-06-01
The sensitivity of doses calculated by the generic biosphere code ECOS to parameter changes has been investigated by the authors for the Department of the Environment as part of its radioactive waste management research programme. The sensitivity of results to radionuclide dependent parameters has been tested by specifying reasonable parameter ranges and performing code runs for best estimate, upper-bound and lower-bound parameter values. The work indicates that doses are most sensitive to scenario parameters: geosphere input fractions, area of contaminated land, land use and diet, flux of contaminated waters and water use. Recommendations are made based on the results of sensitivity. (author)
Seismic analysis of steam generator and parameter sensitivity studies
International Nuclear Information System (INIS)
Qian Hao; Xu Dinggen; Yang Ren'an; Liang Xingyun
2013-01-01
Background: The steam generator (SG) serves as the primary means for removing the heat generated within the reactor core and is part of the reactor coolant system (RCS) pressure boundary. Purpose: Seismic analysis in required for SG, whose seismic category is Cat. I. Methods: The analysis model of SG is created with moisture separator assembly and tube bundle assembly herein. The seismic analysis is performed with RCS pipe and Reactor Pressure Vessel (RPV). Results: The seismic stress results of SG are obtained. In addition, parameter sensitivities of seismic analysis results are studied, such as the effect of another SG, support, anti-vibration bars (AVBs), and so on. Our results show that seismic results are sensitive to support and AVBs setting. Conclusions: The guidance and comments on these parameters are summarized for equipment design and analysis, which should be focused on in future new type NPP SG's research and design. (authors)
A parameter tree approach to estimating system sensitivities to parameter sets
International Nuclear Information System (INIS)
Jarzemba, M.S.; Sagar, B.
2000-01-01
A post-processing technique for determining relative system sensitivity to groups of parameters and system components is presented. It is assumed that an appropriate parametric model is used to simulate system behavior using Monte Carlo techniques and that a set of realizations of system output(s) is available. The objective of our technique is to analyze the input vectors and the corresponding output vectors (that is, post-process the results) to estimate the relative sensitivity of the output to input parameters (taken singly and as a group) and thereby rank them. This technique is different from the design of experimental techniques in that a partitioning of the parameter space is not required before the simulation. A tree structure (which looks similar to an event tree) is developed to better explain the technique. Each limb of the tree represents a particular combination of parameters or a combination of system components. For convenience and to distinguish it from the event tree, we call it the parameter tree. To construct the parameter tree, the samples of input parameter values are treated as either a '+' or a '-' based on whether or not the sampled parameter value is greater than or less than a specified branching criterion (e.g., mean, median, percentile of the population). The corresponding system outputs are also segregated into similar bins. Partitioning the first parameter into a '+' or a '-' bin creates the first level of the tree containing two branches. At the next level, realizations associated with each first-level branch are further partitioned into two bins using the branching criteria on the second parameter and so on until the tree is fully populated. Relative sensitivities are then inferred from the number of samples associated with each branch of the tree. The parameter tree approach is illustrated by applying it to a number of preliminary simulations of the proposed high-level radioactive waste repository at Yucca Mountain, NV. Using a
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 ...
Directory of Open Access Journals (Sweden)
B. Likozar
2012-09-01
Full Text Available Mathematical models for a batch process were developed to predict concentration distributions for an active ingredient (vancomycin adsorption on a representative hydrophobic-molecule adsorbent, using differently diluted crude fermentation broth with cells as the feedstock. The kinetic parameters were estimated using the maximization of the coefficient of determination by a heuristic algorithm. The parameters were estimated for each fermentation broth concentration using four concentration distributions at initial vancomycin concentrations of 4.96, 1.17, 2.78, and 5.54 g l−¹. In sequence, the models and their parameters were validated for fermentation broth concentrations of 0, 20, 50, and 100% (v/v by calculating the coefficient of determination for each concentration distribution at the corresponding initial concentration. The applicability of the validated models for process optimization was investigated by using the models as process simulators to optimize the two process efficiencies.
Directory of Open Access Journals (Sweden)
narges javidan
2017-02-01
, evapotranspiration, temperature, and discharge are used as inputs. Additionally, three main maps of the digital elevation model, soil map (texture, and landuse are also applied and converted to digital formats. The result of the simulation shows a good agreement between the simulated hydrography and the observed one. The routing of overland flow and channel flow is implemented by the method of the diffusive wave approximation. A sensitivity test shows that the parameter of ﬂood frequency and the channel roughness coefﬁcient have a large inﬂuence on the outﬂow hydrography and the calculated watershed unit hydrograph, while the threshold of minimum slope and the threshold of drainage area in delineating channel networks have a marginal effect.
Sensitivity of transient synchrotron radiation to tokamak plasma parameters
International Nuclear Information System (INIS)
Fisch, N.J.; Kritz, A.H.
1988-12-01
Synchrotron radiation from a hot plasma can inform on certain plasma parameters. The dependence on plasma parameters is particularly sensitive for the transient radiation response to a brief, deliberate, perturbation of hot plasma electrons. We investigate how such a radiation response can be used to diagnose a variety of plasma parameters in a tokamak. 18 refs., 13 figs
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.
International Nuclear Information System (INIS)
Sidorenko, V.D.
1978-01-01
The equations are discussed for calculating the importance of neutron function in heterogeneous media obtained with the integral transport theory method. The thermalization effect in the thermal range is described using the differential model. The account of neutron slowing-down in the epithermal range is accomplished in the age approximation. The fast range is described in the 3-group approximation. On the basis of the equations derived the share of delayed neutrons and lifetimes of prompt neutrons are calculated and compared with available experimental data. In the thermal range the sensitivity of cross sections to some parameters of the differential model is analyzed for reactor cells typical for WWER type reactor cores. The models and approximations used are found to be adequate for the calculations
Neutrino Oscillation Parameter Sensitivity in Future Long-Baseline Experiments
Energy Technology Data Exchange (ETDEWEB)
Bass, Matthew [Colorado State Univ., Fort Collins, CO (United States)
2014-01-01
The study of neutrino interactions and propagation has produced evidence for physics beyond the standard model and promises to continue to shed light on rare phenomena. Since the discovery of neutrino oscillations in the late 1990s there have been rapid advances in establishing the three flavor paradigm of neutrino oscillations. The 2012 discovery of a large value for the last unmeasured missing angle has opened the way for future experiments to search for charge-parity symmetry violation in the lepton sector. This thesis presents an analysis of the future sensitivity to neutrino oscillations in the three flavor paradigm for the T2K, NO A, LBNE, and T2HK experiments. The theory of the three flavor paradigm is explained and the methods to use these theoretical predictions to design long baseline neutrino experiments are described. The sensitivity to the oscillation parameters for each experiment is presented with a particular focus on the search for CP violation and the measurement of the neutrino mass hierarchy. The variations of these sensitivities with statistical considerations and experimental design optimizations taken into account are explored. The effects of systematic uncertainties in the neutrino flux, interaction, and detection predictions are also considered by incorporating more advanced simulations inputs from the LBNE experiment.
Sensitivity analysis on parameters and processes affecting vapor intrusion risk
Picone, Sara
2012-03-30
A one-dimensional numerical model was developed and used to identify the key processes controlling vapor intrusion risks by means of a sensitivity analysis. The model simulates the fate of a dissolved volatile organic compound present below the ventilated crawl space of a house. In contrast to the vast majority of previous studies, this model accounts for vertical variation of soil water saturation and includes aerobic biodegradation. The attenuation factor (ratio between concentration in the crawl space and source concentration) and the characteristic time to approach maximum concentrations were calculated and compared for a variety of scenarios. These concepts allow an understanding of controlling mechanisms and aid in the identification of critical parameters to be collected for field situations. The relative distance of the source to the nearest gas-filled pores of the unsaturated zone is the most critical parameter because diffusive contaminant transport is significantly slower in water-filled pores than in gas-filled pores. Therefore, attenuation factors decrease and characteristic times increase with increasing relative distance of the contaminant dissolved source to the nearest gas diffusion front. Aerobic biodegradation may decrease the attenuation factor by up to three orders of magnitude. Moreover, the occurrence of water table oscillations is of importance. Dynamic processes leading to a retreating water table increase the attenuation factor by two orders of magnitude because of the enhanced gas phase diffusion. © 2012 SETAC.
Robust estimation of hydrological model parameters
Directory of Open Access Journals (Sweden)
A. Bárdossy
2008-11-01
Full Text Available The estimation of hydrological model parameters is a challenging task. With increasing capacity of computational power several complex optimization algorithms have emerged, but none of the algorithms gives a unique and very best parameter vector. The parameters of fitted hydrological models depend upon the input data. The quality of input data cannot be assured as there may be measurement errors for both input and state variables. In this study a methodology has been developed to find a set of robust parameter vectors for a hydrological model. To see the effect of observational error on parameters, stochastically generated synthetic measurement errors were applied to observed discharge and temperature data. With this modified data, the model was calibrated and the effect of measurement errors on parameters was analysed. It was found that the measurement errors have a significant effect on the best performing parameter vector. The erroneous data led to very different optimal parameter vectors. To overcome this problem and to find a set of robust parameter vectors, a geometrical approach based on Tukey's half space depth was used. The depth of the set of N randomly generated parameters was calculated with respect to the set with the best model performance (Nash-Sutclife efficiency was used for this study for each parameter vector. Based on the depth of parameter vectors, one can find a set of robust parameter vectors. The results show that the parameters chosen according to the above criteria have low sensitivity and perform well when transfered to a different time period. The method is demonstrated on the upper Neckar catchment in Germany. The conceptual HBV model was used for this study.
Small particle bed reactors: Sensitivity to Brayton cycle parameters
Coiner, John R.; Short, Barry J.
Relatively simple particle bed reactor (PBR) algorithms were developed for optimizing low power closed Brayton cycle (CBC) systems. These algorithms allow the system designer to understand the relationship among key system parameters as well as the sensitivity of the PBR size and mass (a major system component) to variations in these parameters. Thus, system optimization can be achieved.
Model parameter updating using Bayesian networks
International Nuclear Information System (INIS)
Treml, C.A.; Ross, Timothy J.
2004-01-01
This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.
Impact Responses and Parameters Sensitivity Analysis of Electric Wheelchairs
Directory of Open Access Journals (Sweden)
Song Wang
2018-06-01
Full Text Available The shock and vibration of electric wheelchairs undergoing road irregularities is inevitable. The road excitation causes the uneven magnetic gap of the motor, and the harmful vibration decreases the recovery rate of rehabilitation patients. To effectively suppress the shock and vibration, this paper introduces the DA (dynamic absorber to the electric wheelchair. Firstly, a vibration model of the human-wheelchair system with the DA was created. The models of the road excitation for wheelchairs going up a step and going down a step were proposed, respectively. To reasonably evaluate the impact level of the human-wheelchair system undergoing the step–road transition, evaluation indexes were given. Moreover, the created vibration model and the road–step model were validated via tests. Then, to reveal the vibration suppression performance of the DA, the impact responses and the amplitude frequency characteristics were numerically simulated and compared. Finally, a sensitivity analysis of the impact responses to the tire static radius r and the characteristic parameters was carried out. The results show that the DA can effectively suppress the shock and vibration of the human-wheelchair system. Moreover, for the electric wheelchair going up a step and going down a step, there are some differences in the vibration behaviors.
International Nuclear Information System (INIS)
Yu, C.
1986-01-01
The migration of radionuclides in a geologic medium is controlled by the hydrogeologic parameters of the medium such as dispersion coefficient, pore water velocity, retardation factor, degradation rate, mass transfer coefficient, water content, and fraction of dead-end pores. These hydrogeologic parameters are often used to predict the migration of buried wastes in nuclide transport models such as the conventional advection-dispersion model, the mobile-immobile pores model, the nonequilibrium adsorption-desorption model, and the general group transfer concentration model. One of the most important factors determining the accuracy of predicting waste migration is the accuracy of the parameter values used in the model. More sensitive parameters have a greater influence on the results and hence should determined (measured or estimated) more accurately than less sensitive parameters. A formal parameter sensitivity analysis is carried out in this paper. Parameter identification techniques to determine the hydrogeologic parameters of the flow system are discussed. The dependence of the accuracy of the estimated parameters upon the parameter sensitivity is also discussed
Photovoltaic module parameters acquisition model
Energy Technology Data Exchange (ETDEWEB)
Cibira, Gabriel, E-mail: cibira@lm.uniza.sk; Koščová, Marcela, E-mail: mkoscova@lm.uniza.sk
2014-09-01
Highlights: • Photovoltaic five-parameter model is proposed using Matlab{sup ®} and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model.
Photovoltaic module parameters acquisition model
International Nuclear Information System (INIS)
Cibira, Gabriel; Koščová, Marcela
2014-01-01
Highlights: • Photovoltaic five-parameter model is proposed using Matlab ® and Simulink. • The model acquisits input sparse data matrix from stigmatic measurement. • Computer simulations lead to continuous I–V and P–V characteristics. • Extrapolated I–V and P–V characteristics are in hand. • The model allows us to predict photovoltaics exploitation in different conditions. - Abstract: This paper presents basic procedures for photovoltaic (PV) module parameters acquisition using MATLAB and Simulink modelling. In first step, MATLAB and Simulink theoretical model are set to calculate I–V and P–V characteristics for PV module based on equivalent electrical circuit. Then, limited I–V data string is obtained from examined PV module using standard measurement equipment at standard irradiation and temperature conditions and stated into MATLAB data matrix as a reference model. Next, the theoretical model is optimized to keep-up with the reference model and to learn its basic parameters relations, over sparse data matrix. Finally, PV module parameters are deliverable for acquisition at different realistic irradiation, temperature conditions as well as series resistance. Besides of output power characteristics and efficiency calculation for PV module or system, proposed model validates computing statistical deviation compared to reference model
Nuclear data adjustment methodology utilizing resonance parameter sensitivities and uncertainties
International Nuclear Information System (INIS)
Broadhead, B.L.
1983-01-01
This work presents the development and demonstration of a Nuclear Data Adjustment Method that allows inclusion of both energy and spatial self-shielding into the adjustment procedure. The resulting adjustments are for the basic parameters (i.e. resonance parameters) in the resonance regions and for the group cross sections elsewhere. The majority of this development effort concerns the production of resonance parameter sensitivity information which allows the linkage between the responses of interest and the basic parameters. The resonance parameter sensitivity methodology developed herein usually provides accurate results when compared to direct recalculations using existng and well-known cross section processing codes. However, it has been shown in several cases that self-shielded cross sections can be very non-linear functions of the basic parameters. For this reason caution must be used in any study which assumes that a linear relatonship exists between a given self-shielded group cross section and its corresponding basic data parameters. The study also has pointed out the need for more approximate techniques which will allow the required sensitivity information to be obtained in a more cost effective manner
Importance and sensitivity of parameters affecting the Zion Seismic Risk
International Nuclear Information System (INIS)
George, L.L.; O'Connell, W.J.
1985-06-01
This report presents the results of a study on the importance and sensitivity of structures, systems, equipment, components and design parameters used in the Zion Seismic Risk Calculations. This study is part of the Seismic Safety Margins Research Program (SSMRP) supported by the NRC Office of Nuclear Regulatory Research. The objective of this study is to provide the NRC with results on the importance and sensitivity of parameters used to evaluate seismic risk. These results can assist the NRC in making decisions dealing with the allocation of research resources on seismic issues. This study uses marginal analysis in addition to importance and sensitivity analysis to identify subject areas (input parameter areas) for improvements that reduce risk, estimate how much the improvement dfforts reduce risk, and rank the subject areas for improvements. Importance analysis identifies the systems, components, and parameters that are important to risk. Sensitivity analysis estimates the change in risk per unit improvement. Marginal analysis indicates the reduction in risk or uncertainty for improvement effort made in each subject area. The results described in this study were generated using the SEISIM (Systematic Evaluation of Important Safety Improvement Measures) and CHAIN computer codes. Part 1 of the SEISIM computer code generated the failure probabilities and risk values. Part 2 of SEISIM, along with the CHAIN computer code, generated the importance and sensitivity measures
Importance and sensitivity of parameters affecting the Zion Seismic Risk
Energy Technology Data Exchange (ETDEWEB)
George, L.L.; O' Connell, W.J.
1985-06-01
This report presents the results of a study on the importance and sensitivity of structures, systems, equipment, components and design parameters used in the Zion Seismic Risk Calculations. This study is part of the Seismic Safety Margins Research Program (SSMRP) supported by the NRC Office of Nuclear Regulatory Research. The objective of this study is to provide the NRC with results on the importance and sensitivity of parameters used to evaluate seismic risk. These results can assist the NRC in making decisions dealing with the allocation of research resources on seismic issues. This study uses marginal analysis in addition to importance and sensitivity analysis to identify subject areas (input parameter areas) for improvements that reduce risk, estimate how much the improvement dfforts reduce risk, and rank the subject areas for improvements. Importance analysis identifies the systems, components, and parameters that are important to risk. Sensitivity analysis estimates the change in risk per unit improvement. Marginal analysis indicates the reduction in risk or uncertainty for improvement effort made in each subject area. The results described in this study were generated using the SEISIM (Systematic Evaluation of Important Safety Improvement Measures) and CHAIN computer codes. Part 1 of the SEISIM computer code generated the failure probabilities and risk values. Part 2 of SEISIM, along with the CHAIN computer code, generated the importance and sensitivity measures.
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.
Deng, Dongdong; Murphy, Michael J.; Hakim, Joe B.; Franceschi, William H.; Zahid, Sohail; Pashakhanloo, Farhad; Trayanova, Natalia A.; Boyle, Patrick M.
2017-09-01
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, causing morbidity and mortality in millions worldwide. The atria of patients with persistent AF (PsAF) are characterized by the presence of extensive and distributed atrial fibrosis, which facilitates the formation of persistent reentrant drivers (RDs, i.e., spiral waves), which promote fibrillatory activity. Targeted catheter ablation of RD-harboring tissues has shown promise as a clinical treatment for PsAF, but the outcomes remain sub-par. Personalized computational modeling has been proposed as a means of non-invasively predicting optimal ablation targets in individual PsAF patients, but it remains unclear how RD localization dynamics are influenced by inter-patient variability in the spatial distribution of atrial fibrosis, action potential duration (APD), and conduction velocity (CV). Here, we conduct simulations in computational models of fibrotic atria derived from the clinical imaging of PsAF patients to characterize the sensitivity of RD locations to these three factors. We show that RDs consistently anchor to boundaries between fibrotic and non-fibrotic tissues, as delineated by late gadolinium-enhanced magnetic resonance imaging, but those changes in APD/CV can enhance or attenuate the likelihood that an RD will anchor to a specific site. These findings show that the level of uncertainty present in patient-specific atrial models reconstructed without any invasive measurements (i.e., incorporating each individual's unique distribution of fibrotic tissue from medical imaging alongside an average representation of AF-remodeled electrophysiology) is sufficiently high that a personalized ablation strategy based on targeting simulation-predicted RD trajectories alone may not produce the desired result.
Energy Technology Data Exchange (ETDEWEB)
Staudt, C.; Kaiser, J.C. Christian [Helmholtz Zentrum Muenchen, Deutsches Forschungszentrum fuer Gesundheit und Umwelt, Muenchen (Germany). Inst. fuer Strahlenschutz
2014-01-20
Radioecological models are used for the assessment of potential exposures of a population to radionuclides from final repositories for high level radioactive waste. Due to the long disposal time frame, changes in model relevant exposure pathways need to be accounted for. Especially climate change will result in changes of the modelled system. Reference biosphere models are used to asses climate related changes in the far field of a final repository. In this approach, model scenarios are developed for potential future climate states and defined by parameters derived from currently existing, similar climate regions. It is assumed, that habits and agricultural practices of a population will adapt to the new climate over long periods of time, until they mirror the habits of a contemporary population living in a similar climate. As an end point of the models, Biosphere Dose Conversion Factors (BDCF) are calculated. These radionuclide specific BDCF describe the exposure of a hypothetical population resulting from a standardized radionuclide contamination in near surface ground water. Model results are subject to uncertainties due to inherent uncertainties of assumed future developments, habits and empirically measured parameters. In addition to deterministic calculations, sensitivity analysis and probabilistic calculations were done for several model scenarios, to control the quality of the model and due to the high number of parameters used to define different climate states, soil types and consumption habits.
Sensitivity Analysis in Sequential Decision Models.
Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet
2017-02-01
Sequential decision problems are frequently encountered in medical decision making, which are commonly solved using Markov decision processes (MDPs). Modeling guidelines recommend conducting sensitivity analyses in decision-analytic models to assess the robustness of the model results against the uncertainty in model parameters. However, standard methods of conducting sensitivity analyses cannot be directly applied to sequential decision problems because this would require evaluating all possible decision sequences, typically in the order of trillions, which is not practically feasible. As a result, most MDP-based modeling studies do not examine confidence in their recommended policies. In this study, we provide an approach to estimate uncertainty and confidence in the results of sequential decision models. First, we provide a probabilistic univariate method to identify the most sensitive parameters in MDPs. Second, we present a probabilistic multivariate approach to estimate the overall confidence in the recommended optimal policy considering joint uncertainty in the model parameters. We provide a graphical representation, which we call a policy acceptability curve, to summarize the confidence in the optimal policy by incorporating stakeholders' willingness to accept the base case policy. For a cost-effectiveness analysis, we provide an approach to construct a cost-effectiveness acceptability frontier, which shows the most cost-effective policy as well as the confidence in that for a given willingness to pay threshold. We demonstrate our approach using a simple MDP case study. We developed a method to conduct sensitivity analysis in sequential decision models, which could increase the credibility of these models among stakeholders.
Sensitivity analysis of railpad parameters on vertical railway track dynamics
Oregui Echeverria-Berreyarza, M.; Nunez Vicencio, Alfredo; Dollevoet, R.P.B.J.; Li, Z.
2016-01-01
This paper presents a sensitivity analysis of railpad parameters on vertical railway track dynamics, incorporating the nonlinear behavior of the fastening (i.e., downward forces compress the railpad whereas upward forces are resisted by the clamps). For this purpose, solid railpads, rail-railpad
International Nuclear Information System (INIS)
Drakou, G.; Zerefos, C.; Ziomas, I.
2000-01-01
The indoor O 3 , NO, NO 2 concentrations and their corresponding indoor/outdoor (I/O) concentration ratios are predicted in this paper for some representative buildings, using the Nazaroff-Cass indoor air quality models. This paper presents and systemises the relationship between indoor and air pollution concentrations and the buildings' design, use and operation. The building parameters which are determined to be main factors affecting the air pollutant concentrations are: the physical dimensions of the building and the materials of construction, the buildings' air exchange rate with outdoors and the indoor air pollutant sources. Changes of ultraviolet photon fluxes, of temperatures and of relative humidity indoors, have little effect on indoor O 3 , NO and NO 2 concentrations, for air exchange rates above 0.5 ach. Special attention must be given when a building has a very low air exchange rate, under which conditions the effect of a small change in any of the factors determining the indoor air quality of the building will be much more noticeable than in a building with high air exchange rate. (Author)
International Nuclear Information System (INIS)
Greenspan, E.
1982-01-01
This chapter presents the mathematical basis for sensitivity functions, discusses their physical meaning and information they contain, and clarifies a number of issues concerning their application, including the definition of group sensitivities, the selection of sensitivity functions to be included in the analysis, and limitations of sensitivity theory. Examines the theoretical foundation; criticality reset sensitivities; group sensitivities and uncertainties; selection of sensitivities included in the analysis; and other uses and limitations of sensitivity functions. Gives the theoretical formulation of sensitivity functions pertaining to ''as-built'' designs for performance parameters of the form of ratios of linear flux functionals (such as reaction-rate ratios), linear adjoint functionals, bilinear functions (such as reactivity worth ratios), and for reactor reactivity. Offers a consistent procedure for reducing energy-dependent or fine-group sensitivities and uncertainties to broad group sensitivities and uncertainties. Provides illustrations of sensitivity functions as well as references to available compilations of such functions and of total sensitivities. Indicates limitations of sensitivity theory originating from the fact that this theory is based on a first-order perturbation theory
International Nuclear Information System (INIS)
Astudillo, Miguel F.; Vaillancourt, Kathleen; Pineau, Pierre-Olivier; Amor, Ben
2017-01-01
Highlights: •An energy system model of Quebec is combined with building simulation software. •Greenhouse gas emission reductions efforts increase annual electricity peak demand. •Alternative heating tech. And building envelopes can effectively reduce peak demand. •Denser urban developments massively reduced costs of global warming mitigation. •CO 2 emissions from hydropower reservoirs are relevant in global warming mitigation. -- Abstract: The transition to low carbon societies may increase peak electricity demand, which can be costly to supply with renewable energy, whose availability is uncertain. Buildings are often the main cause of peak demand, and they are believed to hold a large unrealised energy-efficiency potential. If realised, this potential could considerably mitigate the transition costs to low carbon societies, reducing average and peak electricity demands. We explore this potential in several cost-optimal global warming (GW) mitigation scenarios using a multi-sector TIMES energy system model of the province of Quebec for the period 2011–2050. Heating and conservation measures in the residential sector are modelled using building simulations and parameters’ values from the literature. The intra-annual availability of renewable energy and electricity imports is derived from time-series analysis. Additionally, the influence of key parameters such as the projections of primary energy demand and emissions from reservoir impoundment is evaluated. Finally, we discuss some of the barriers that could hamper the energy transition and how they can be overcome. Results indicate that peak demand would rise by 30% due to GW mitigation efforts, but it can be effectively reduced by interventions in the residential sector. Heat pumps are the most cost effective heating technology, despite their lower efficiencies in cold climates. Better-insulated building envelopes have an important role in new houses, reducing by 14% the GW mitigation costs and
Kim, Yeonho; Nabili, Marjan; Acharya, Priyanka; Lopez, Asis; Myers, Matthew R
2017-01-01
Safety analyses of transcranial therapeutic ultrasound procedures require knowledge of the dependence of the rupture probability and rupture time upon sonication parameters. As previous vessel-rupture studies have concentrated on a specific set of exposure conditions, there is a need for more comprehensive parametric studies. Probability of rupture and rupture times were measured by exposing the large blood vessel of a live earthworm to high-intensity focused ultrasound pulse trains of various characteristics. Pressures generated by the ultrasound transducers were estimated through numerical solutions to the KZK (Khokhlov-Zabolotskaya-Kuznetsov) equation. Three ultrasound frequencies (1.1, 2.5, and 3.3 MHz) were considered, as were three pulse repetition frequencies (1, 3, and 10 Hz), and two duty factors (0.0001, 0.001). The pressures produced ranged from 4 to 18 MPa. Exposures of up to 10 min in duration were employed. Trials were repeated an average of 11 times. No trends as a function of pulse repetition rate were identifiable, for either probability of rupture or rupture time. Rupture time was found to be a strong function of duty factor at the lower pressures; at 1.1 MHz the rupture time was an order of magnitude lower for the 0.001 duty factor than the 0.0001. At moderate pressures, the difference between the duty factors was less, and there was essentially no difference between duty factors at the highest pressure. Probability of rupture was not found to be a strong function of duty factor. Rupture thresholds were about 4 MPa for the 1.1 MHz frequency, 7 MPa at 3.3 MHz, and 11 MPa for the 2.5 MHz, though the pressure value at 2.5 MHz frequency will likely be reduced when steep-angle corrections are accounted for in the KZK model used to estimate pressures. Mechanical index provided a better collapse of the data (less separation of the curves pertaining to the different frequencies) than peak negative pressure, for both probability of rupture and
Hirota, Morihiko; Ashikaga, Takao; Kouzuki, Hirokazu
2018-04-01
It is important to predict the potential of cosmetic ingredients to cause skin sensitization, and in accordance with the European Union cosmetic directive for the replacement of animal tests, several in vitro tests based on the adverse outcome pathway have been developed for hazard identification, such as the direct peptide reactivity assay, KeratinoSens™ and the human cell line activation test. Here, we describe the development of an artificial neural network (ANN) prediction model for skin sensitization risk assessment based on the integrated testing strategy concept, using direct peptide reactivity assay, KeratinoSens™, human cell line activation test and an in silico or structure alert parameter. We first investigated the relationship between published murine local lymph node assay EC3 values, which represent skin sensitization potency, and in vitro test results using a panel of about 134 chemicals for which all the required data were available. Predictions based on ANN analysis using combinations of parameters from all three in vitro tests showed a good correlation with local lymph node assay EC3 values. However, when the ANN model was applied to a testing set of 28 chemicals that had not been included in the training set, predicted EC3s were overestimated for some chemicals. Incorporation of an additional in silico or structure alert descriptor (obtained with TIMES-M or Toxtree software) in the ANN model improved the results. Our findings suggest that the ANN model based on the integrated testing strategy concept could be useful for evaluating the skin sensitization potential. Copyright © 2017 John Wiley & Sons, Ltd.
Sensitivity of risk parameters to human errors for a PWR
International Nuclear Information System (INIS)
Samanta, P.; Hall, R.E.; Kerr, W.
1980-01-01
Sensitivities of the risk parameters, emergency safety system unavailabilities, accident sequence probabilities, release category probabilities and core melt probability were investigated for changes in the human error rates within the general methodological framework of the Reactor Safety Study for a Pressurized Water Reactor (PWR). Impact of individual human errors were assessed both in terms of their structural importance to core melt and reliability importance on core melt probability. The Human Error Sensitivity Assessment of a PWR (HESAP) computer code was written for the purpose of this study
Sensitivity calculation of the coolant temperature regarding the thermohydraulic parameters
International Nuclear Information System (INIS)
Andrade Lima, F.R. de; Silva, F.C. da; Thome Filho, Z.D.; Alvim, A.C.M.; Oliveira Barroso, A.C. de.
1985-01-01
It's studied the application of the Generalized Perturbation Theory (GPT) in the sensitivity calculation of thermalhydraulic problems, aiming at verifying the viability of the extension of the method. For this, the axial distribution, transient, of the coolant temperature in a PWR channel are considered. Perturbation expressions are developed using the GPT formalism, and a computer code (Tempera) is written, to calculate the channel temperature distribution and the associated importance function, as well as the effect of the thermalhydraulic parameters variations in the coolant temperature (sensitivity calculation). The results are compared with those from the direct calculation. (E.G.) [pt
Estimation of parameter sensitivities for stochastic reaction networks
Gupta, Ankit
2016-01-01
Quantification of the effects of parameter uncertainty is an important and challenging problem in Systems Biology. We consider this problem in the context of stochastic models of biochemical reaction networks where the dynamics is described as a
Calculation of coolant temperature sensitivity related to thermohydraulic parameters
International Nuclear Information System (INIS)
Silva, F.C. da; Andrade Lima, F.R. de
1985-01-01
It is verified the viability to apply the generalized Perturbation Theory (GPT) in the calculation of sensitivity for thermal-hydraulic problems. It was developed the TEMPERA code in FORTRAN-IV to transient calculations in the axial temperature distribution in a channel of PWR reactor and the associated importance function, as well as effects of variations of thermalhydraulic parameters in the coolant temperature. The results are compared with one which were obtained by direct calculation. (M.C.K.) [pt
DEFF Research Database (Denmark)
Sun, Shu; Rappaport, Theodore S.; Thomas, Timothy
2016-01-01
This paper compares three candidate large-scale propagation path loss models for use over the entire microwave and millimeter-wave (mmWave) radio spectrum: the alpha–beta–gamma (ABG) model, the close-in (CI) free-space reference distance model, and the CI model with a frequency-weighted path loss...... exponent (CIF). Each of these models has been recently studied for use in standards bodies such as 3rd Generation Partnership Project (3GPP) and for use in the design of fifth generation wireless systems in urban macrocell, urban microcell, and indoor office and shopping mall scenarios. Here, we compare...
Sensitivity of seismic design parameters to input variables
International Nuclear Information System (INIS)
Wium, D.J.W.
1987-01-01
The probabilistic method introduced by Cornell (1968) has been used to a large extent for this purpose. Due to its probabilistic approach, this technique provides a sound basis for studying the influence of the dominant parameters in such a model. Although the Southern African region is not well known for its seismicity, a number of events in the recent past has focussed the attention on some seismically active areas where special attention may be needed in defining the correct design parameters. The relatively sparse historical seismic data has been used to develop a mathematical model which represents this region. This paper briefly discusses this model, and uses it as a basis for evaluating the influence of the uncertainty in each of the principal parameters, being the seismicity of the region, the attenuation of seismic waves after an event, and models that can be used to arrive at engineering design values. (orig./HP)
Reliability analysis of a sensitive and independent stabilometry parameter set.
Nagymáté, Gergely; Orlovits, Zsanett; Kiss, Rita M
2018-01-01
Recent studies have suggested reduced independent and sensitive parameter sets for stabilometry measurements based on correlation and variance analyses. However, the reliability of these recommended parameter sets has not been studied in the literature or not in every stance type used in stabilometry assessments, for example, single leg stances. The goal of this study is to evaluate the test-retest reliability of different time-based and frequency-based parameters that are calculated from the center of pressure (CoP) during bipedal and single leg stance for 30- and 60-second measurement intervals. Thirty healthy subjects performed repeated standing trials in a bipedal stance with eyes open and eyes closed conditions and in a single leg stance with eyes open for 60 seconds. A force distribution measuring plate was used to record the CoP. The reliability of the CoP parameters was characterized by using the intraclass correlation coefficient (ICC), standard error of measurement (SEM), minimal detectable change (MDC), coefficient of variation (CV) and CV compliance rate (CVCR). Based on the ICC, SEM and MDC results, many parameters yielded fair to good reliability values, while the CoP path length yielded the highest reliability (smallest ICC > 0.67 (0.54-0.79), largest SEM% = 19.2%). Usually, frequency type parameters and extreme value parameters yielded poor reliability values. There were differences in the reliability of the maximum CoP velocity (better with 30 seconds) and mean power frequency (better with 60 seconds) parameters between the different sampling intervals.
Reliability analysis of a sensitive and independent stabilometry parameter set
Nagymáté, Gergely; Orlovits, Zsanett
2018-01-01
Recent studies have suggested reduced independent and sensitive parameter sets for stabilometry measurements based on correlation and variance analyses. However, the reliability of these recommended parameter sets has not been studied in the literature or not in every stance type used in stabilometry assessments, for example, single leg stances. The goal of this study is to evaluate the test-retest reliability of different time-based and frequency-based parameters that are calculated from the center of pressure (CoP) during bipedal and single leg stance for 30- and 60-second measurement intervals. Thirty healthy subjects performed repeated standing trials in a bipedal stance with eyes open and eyes closed conditions and in a single leg stance with eyes open for 60 seconds. A force distribution measuring plate was used to record the CoP. The reliability of the CoP parameters was characterized by using the intraclass correlation coefficient (ICC), standard error of measurement (SEM), minimal detectable change (MDC), coefficient of variation (CV) and CV compliance rate (CVCR). Based on the ICC, SEM and MDC results, many parameters yielded fair to good reliability values, while the CoP path length yielded the highest reliability (smallest ICC > 0.67 (0.54–0.79), largest SEM% = 19.2%). Usually, frequency type parameters and extreme value parameters yielded poor reliability values. There were differences in the reliability of the maximum CoP velocity (better with 30 seconds) and mean power frequency (better with 60 seconds) parameters between the different sampling intervals. PMID:29664938
Sensitivity Analysis of Simulation Models
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
Alberts, B.A.; Rutten, Wim; Wallinga, W.; Boom, H.B.K.
1988-01-01
A microscopic model of volume conduction was applied to examine the sensitivity of the single muscle fibre action potential to variations in parameters of the source and of the volume conductor, such as conduction velocity, intracellular conductivity and intracellular volume fraction. The model
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 ...
DEFF Research Database (Denmark)
Van Bockstal, Pieter-Jan; Mortier, Séverine Thérèse F.C.; Corver, Jos
2018-01-01
Pharmaceutical batch freeze-drying is commonly used to improve the stability of biological therapeutics. The primary drying step is regulated by the dynamic settings of the adaptable process variables, shelf temperature Ts and chamber pressure Pc. Mechanistic modelling of the primary drying step...
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.
Multi-parameters sensitivity analysis of natural vibration modal for steel arch bridge
Directory of Open Access Journals (Sweden)
WANG Ying
2014-02-01
Full Text Available Because of the vehicle loads and environmental factors,the behaviors of bridge structure in service is becoming deterioration.The modal parameters are important indexes of structure,so sensitivity analysis of natural vibration is an important way to evaluate the behavior of bridge structure.In this paper,using the finite element software Ansys,calculation model of a steel arch bridge was built,and the natural vibration modals were obtained.In order to compare the different sensitivity of material parameters which may affect the natural vibration modal,5 factors were chosen to perform the calculation.The results indicated that different 5 factors had different sensitivity.The leading factor was elastic modulus of arch rib,and the elastic modulus of suspender had little effect to the sensitivity.Another argument was the opposite sensitivity effect happened between the elastic modulus and density of the material.
Sensitivity and parameter-estimation precision for alternate LISA configurations
International Nuclear Information System (INIS)
Vallisneri, Michele; Crowder, Jeff; Tinto, Massimo
2008-01-01
We describe a simple framework to assess the LISA scientific performance (more specifically, its sensitivity and expected parameter-estimation precision for prescribed gravitational-wave signals) under the assumption of failure of one or two inter-spacecraft laser measurements (links) and of one to four intra-spacecraft laser measurements. We apply the framework to the simple case of measuring the LISA sensitivity to monochromatic circular binaries, and the LISA parameter-estimation precision for the gravitational-wave polarization angle of these systems. Compared to the six-link baseline configuration, the five-link case is characterized by a small loss in signal-to-noise ratio (SNR) in the high-frequency section of the LISA band; the four-link case shows a reduction by a factor of √2 at low frequencies, and by up to ∼2 at high frequencies. The uncertainty in the estimate of polarization, as computed in the Fisher-matrix formalism, also worsens when moving from six to five, and then to four links: this can be explained by the reduced SNR available in those configurations (except for observations shorter than three months, where five and six links do better than four even with the same SNR). In addition, we prove (for generic signals) that the SNR and Fisher matrix are invariant with respect to the choice of a basis of TDI observables; rather, they depend only on which inter-spacecraft and intra-spacecraft measurements are available
Parameter-free Locality Sensitive Hashing for Spherical Range Reporting
DEFF Research Database (Denmark)
Ahle, Thomas Dybdahl; Pagh, Rasmus; Aumüller, Martin
2017-01-01
We present a data structure for *spherical range reporting* on a point set S, i.e., reporting all points in S that lie within radius r of a given query point q. Our solution builds upon the Locality-Sensitive Hashing (LSH) framework of Indyk and Motwani, which represents the asymptotically best...... solutions to near neighbor problems in high dimensions. While traditional LSH data structures have several parameters whose optimal values depend on the distance distribution from q to the points of S, our data structure is parameter-free, except for the space usage, which is configurable by the user...... query time bounded by O(t(n/t)ρ), where t is the number of points to report and ρ∈(0,1) depends on the data distribution and the strength of the LSH family used. We further present a parameter-free way of using multi-probing, for LSH families that support it, and show that for many such families...
Wang, Xu; Bi, Fengrong; Du, Haiping
2018-05-01
This paper aims to develop an 5-degree-of-freedom driver and seating system model for optimal vibration control. A new method for identification of the driver seating system parameters from experimental vibration measurement has been developed. The parameter sensitivity analysis has been conducted considering the random excitation frequency and system parameter uncertainty. The most and least sensitive system parameters for the transmissibility ratio have been identified. The optimised PID controllers have been developed to reduce the driver's body vibration.
Sensitivity analysis approaches applied to systems biology models.
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.
A specialized ODE integrator for the efficient computation of parameter sensitivities
Directory of Open Access Journals (Sweden)
Gonnet Pedro
2012-05-01
Full Text Available Abstract Background Dynamic mathematical models in the form of systems of ordinary differential equations (ODEs play an important role in systems biology. For any sufficiently complex model, the speed and accuracy of solving the ODEs by numerical integration is critical. This applies especially to systems identification problems where the parameter sensitivities must be integrated alongside the system variables. Although several very good general purpose ODE solvers exist, few of them compute the parameter sensitivities automatically. Results We present a novel integration algorithm that is based on second derivatives and contains other unique features such as improved error estimates. These features allow the integrator to take larger time steps than other methods. In practical applications, i.e. systems biology models of different sizes and behaviors, the method competes well with established integrators in solving the system equations, and it outperforms them significantly when local parameter sensitivities are evaluated. For ease-of-use, the solver is embedded in a framework that automatically generates the integrator input from an SBML description of the system of interest. Conclusions For future applications, comparatively ‘cheap’ parameter sensitivities will enable advances in solving large, otherwise computationally expensive parameter estimation and optimization problems. More generally, we argue that substantially better computational performance can be achieved by exploiting characteristics specific to the problem domain; elements of our methods such as the error estimation could find broader use in other, more general numerical algorithms.
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...
Sensitivity of lumbar spine loading to anatomical parameters
DEFF Research Database (Denmark)
Putzer, Michael; Ehrlich, Ingo; Rasmussen, John
2016-01-01
Musculoskeletal simulations of lumbar spine loading rely on a geometrical representation of the anatomy. However, this data has an inherent inaccuracy. This study evaluates the in uence of dened geometrical parameters on lumbar spine loading utilizing ve parametrized musculoskeletal lumbar spine ...... lumbar spine model for a subject-specic approach with respect to bone geometry. Furthermore, degeneration processes could lead to computational problems and it is advised that stiffness properties of discs and ligaments should be individualized....
International Nuclear Information System (INIS)
Lange, Kyle J.; Anderson, W. Kyle
2010-01-01
The problem of applying sensitivity analysis to a one-dimensional atmospheric radio frequency plasma discharge simulation is considered. A fluid simulation is used to model an atmospheric pressure radio frequency helium discharge with a small nitrogen impurity. Sensitivity derivatives are computed for the peak electron density with respect to physical inputs to the simulation. These derivatives are verified using several different methods to compute sensitivity derivatives. It is then demonstrated how sensitivity derivatives can be used within a design cycle to change these physical inputs so as to increase the peak electron density. It is also shown how sensitivity analysis can be used in conjunction with experimental data to obtain better estimates for rate and transport parameters. Finally, it is described how sensitivity analysis could be used to compute an upper bound on the uncertainty for results from a simulation.
ENDF-6 File 30: Data covariances obtained from parameter covariances and sensitivities
International Nuclear Information System (INIS)
Muir, D.W.
1989-01-01
File 30 is provided as a means of describing the covariances of tabulated cross sections, multiplicities, and energy-angle distributions that result from propagating the covariances of a set of underlying parameters (for example, the input parameters of a nuclear-model code), using an evaluator-supplied set of parameter covariances and sensitivities. Whenever nuclear data are evaluated primarily through the application of nuclear models, the covariances of the resulting data can be described very adequately, and compactly, by specifying the covariance matrix for the underlying nuclear parameters, along with a set of sensitivity coefficients giving the rate of change of each nuclear datum of interest with respect to each of the model parameters. Although motivated primarily by these applications of nuclear theory, use of File 30 is not restricted to any one particular evaluation methodology. It can be used to describe data covariances of any origin, so long as they can be formally separated into a set of parameters with specified covariances and a set of data sensitivities
Sensitivity Analysis of WEC Array Layout Parameters Effect on the Power Performance
DEFF Research Database (Denmark)
Ruiz, Pau Mercadé; Ferri, Francesco; Kofoed, Jens Peter
2015-01-01
This study assesses the effect that the array layout choice has on the power performance. To this end, a sensitivity analysis is carried out with six array layout parameters, as the simulation inputs, the array power performance (q-factor), as the simulation output, and a simulation model special...
Sensitivity calculations of integral parameters by a generalyzed perturbation theory
International Nuclear Information System (INIS)
Santo, A.C.F. de.
1981-12-01
In this work, we first revise some concepts, concerning the neutron transport in nuclear systems. We derive the balance and importance equation. Then we discuss the neutron importance in subcritical, critical and supercritical systems. The adjoint flux is estabilished as the neutron importance for the fission process. The conventional perturbation theory is later presented. We developed a sistematic perturbative formulation in the first order variation in the distribution functions calculate the reactivity due to a system perturbation. We present in detail the flux difference and generalized functions methos. The above formulation is then extended for altered systems. We consider integral parameters of the type ratio of bilinear functionals (for which the reactivity is a particular case). We define sensitivity coeficients, for any integral parameter, corresponding to a especific system alterations. Possible aplication of the method are also discussed. In the last part of this work, we apply the perturbative formulation to the doppler reacitivity sensibility calculation, utilizing the generalized functions method. We describe in detail the compiler program written for this and some other possible aplications. (Author) [pt
The influence of model parameters on catchment-response
International Nuclear Information System (INIS)
Shah, S.M.S.; Gabriel, H.F.; Khan, A.A.
2002-01-01
This paper deals with the study of influence of influence of conceptual rainfall-runoff model parameters on catchment response (runoff). A conceptual modified watershed yield model is employed to study the effects of model-parameters on catchment-response, i.e. runoff. The model is calibrated, using manual parameter-fitting approach, also known as trial and error parameter-fitting. In all, there are twenty one (21) parameters that control the functioning of the model. A lumped parametric approach is used. The detailed analysis was performed on Ling River near Kahuta, having catchment area of 56 sq. miles. The model includes physical parameters like GWSM, PETS, PGWRO, etc. fitting coefficients like CINF, CGWS, etc. and initial estimates of the surface-water and groundwater storages i.e. srosp and gwsp. Sensitivity analysis offers a good way, without repetititious computations, the proper weight and consideration that must be taken when each of the influencing factor is evaluated. Sensitivity-analysis was performed to evaluate the influence of model-parameters on runoff. The sensitivity and relative contributions of model parameters influencing catchment-response are studied. (author)
Directory of Open Access Journals (Sweden)
Yun Zhang
2017-12-01
Full Text Available This paper mainly investigates the sensitive characteristics of lithium-ion batteries so as to provide scientific basises for simplifying the design of the state estimator that adapt to various environments. Three lithium-ion batteries are chosen as the experimental samples. The samples were tested at various temperatures (−20 ∘ C, −10 ∘ C, 0 ∘ C , 10 ∘ C , 25 ∘ C and various current rates (0.5C, 1C, 1.5C using a battery test bench. A physical equivalent circuit model is developed to capture the dynamic characteristics of the batteries. The experimental results show that all battery parameters are time-varying and have different sensitivity to temperature, current rate and state of charge (SOC. The sensitivity of battery to temperature, current rate and SOC increases the difficulty in battery modeling because of the change of parameters. The further simulation experiments show that the model output has a higher sensitivity to the change of ohmic resistance than that of other parameters. Based on the experimental and simulation results obtained here, it is expected that the adaptive parameter state estimator design could be simplified in the near future.
Parametric sensitivity analysis for techno-economic parameters in Indian power sector
International Nuclear Information System (INIS)
Mallah, Subhash; Bansal, N.K.
2011-01-01
Sensitivity analysis is a technique that evaluates the model response to changes in input assumptions. Due to uncertain prices of primary fuels in the world market, Government regulations for sustainability and various other technical parameters there is a need to analyze the techno-economic parameters which play an important role in policy formulations. This paper examines the variations in technical as well as economic parameters that can mostly affect the energy policy of India. MARKAL energy simulation model has been used to analyze the uncertainty in all techno-economic parameters. Various ranges of input parameters are adopted from previous studies. The results show that at lower discount rate coal is the least preferred technology and correspondingly carbon emission reduction. With increased gas and nuclear fuel prices they disappear from the allocations of energy mix.
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.
Sensitivity of viscosity Arrhenius parameters to polarity of liquids
Kacem, R. B. H.; Alzamel, N. O.; Ouerfelli, N.
2017-09-01
Several empirical and semi-empirical equations have been proposed in the literature to estimate the liquid viscosity upon temperature. In this context, this paper aims to study the effect of polarity of liquids on the modeling of the viscosity-temperature dependence, considering particularly the Arrhenius type equations. To achieve this purpose, the solvents are classified into three groups: nonpolar, borderline polar and polar solvents. Based on adequate statistical tests, we found that there is strong evidence that the polarity of solvents affects significantly the distribution of the Arrhenius-type equation parameters and consequently the modeling of the viscosity-temperature dependence. Thus, specific estimated values of parameters for each group of liquids are proposed in this paper. In addition, the comparison of the accuracy of approximation with and without classification of liquids, using the Wilcoxon signed-rank test, shows a significant discrepancy of the borderline polar solvents. For that, we suggested in this paper new specific coefficient values of the simplified Arrhenius-type equation for better estimation accuracy. This result is important given that the accuracy in the estimation of the viscosity-temperature dependence may affect considerably the design and the optimization of several industrial processes.
The sensitivity of the ESA DELTA model
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.
Sensitivity Analyses for Cross-Coupled Parameters in Automotive Powertrain Optimization
Directory of Open Access Journals (Sweden)
Pongpun Othaganont
2014-06-01
Full Text Available When vehicle manufacturers are developing new hybrid and electric vehicles, modeling and simulation are frequently used to predict the performance of the new vehicles from an early stage in the product lifecycle. Typically, models are used to predict the range, performance and energy consumption of their future planned production vehicle; they also allow the designer to optimize a vehicle’s configuration. Another use for the models is in performing sensitivity analysis, which helps us understand which parameters have the most influence on model predictions and real-world behaviors. There are various techniques for sensitivity analysis, some are numerical, but the greatest insights are obtained analytically with sensitivity defined in terms of partial derivatives. Existing methods in the literature give us a useful, quantified measure of parameter sensitivity, a first-order effect, but they do not consider second-order effects. Second-order effects could give us additional insights: for example, a first order analysis might tell us that a limiting factor is the efficiency of the vehicle’s prime-mover; our new second order analysis will tell us how quickly the efficiency of the powertrain will become of greater significance. In this paper, we develop a method based on formal optimization mathematics for rapid second-order sensitivity analyses and illustrate these through a case study on a C-segment electric vehicle.
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.
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.
Selection of body sway parameters according to their sensitivity and repeatability
Directory of Open Access Journals (Sweden)
Nejc Sarabon
2010-03-01
Full Text Available For the precise evaluation of body balance, static type of tests performed on a force plate are the most commonly used ones. In these tests, body sway characteristics are analyzed based on the model of inverted pendulum and looking at the center of pressure (COP movement in time. Human body engages different strategies to compensate for balance perturbations. For this reason, there is a need to identify parameters which are sensitive to specific balance changes and which enable us to identify balance sub-components. The aim of our study was to investigate intra-visit repeatability and sensibility of the 40 different body sway parameters. Twenty-nine subjects participated in the study. They performed three different balancing tasks of different levels of difficulty, three repetitions each. The hip-width parallel stance and the single leg stance, both with open eyes, were used as ways to compare different balance intensities due to biomechanical changes. Additionally, deprivation of vision was used in the third balance task to study sensitivity to sensory system changes. As shown by intraclass correlation coefficient (ICC, repeatability of cumulative parameters such as COP, maximal amplitude and frequency showed excellent repeatability (ICC>0,85. Other parameters describing sub-dynamics through single repetition proved to have unsatisfying repeatability. Parameters most sensitive to increased intensity of balancing tasks were common COP, COP in medio-lateral and in antero-posterior direction, and maximal amplitues in the same directions. Frequency of oscilations has proved to be sensitive only to deprivation of vision. As shown in our study, cumulative parameters describing the path which the center of pressure makes proved to be the most repeatable and sensitive to detect different increases of balancing tasks enabling future use in balance studies and in clinical practice.
Adjoint sensitivity of global cloud droplet number to aerosol and dynamical parameters
Directory of Open Access Journals (Sweden)
V. A. Karydis
2012-10-01
Full Text Available We present the development of the adjoint of a comprehensive cloud droplet formation parameterization for use in aerosol-cloud-climate interaction studies. The adjoint efficiently and accurately calculates the sensitivity of cloud droplet number concentration (CDNC to all parameterization inputs (e.g., updraft velocity, water uptake coefficient, aerosol number and hygroscopicity with a single execution. The adjoint is then integrated within three dimensional (3-D aerosol modeling frameworks to quantify the sensitivity of CDNC formation globally to each parameter. Sensitivities are computed for year-long executions of the NASA Global Modeling Initiative (GMI Chemical Transport Model (CTM, using wind fields computed with the Goddard Institute for Space Studies (GISS Global Circulation Model (GCM II', and the GEOS-Chem CTM, driven by meteorological input from the Goddard Earth Observing System (GEOS of the NASA Global Modeling and Assimilation Office (GMAO. We find that over polluted (pristine areas, CDNC is more sensitive to updraft velocity and uptake coefficient (aerosol number and hygroscopicity. Over the oceans of the Northern Hemisphere, addition of anthropogenic or biomass burning aerosol is predicted to increase CDNC in contrast to coarse-mode sea salt which tends to decrease CDNC. Over the Southern Oceans, CDNC is most sensitive to sea salt, which is the main aerosol component of the region. Globally, CDNC is predicted to be less sensitive to changes in the hygroscopicity of the aerosols than in their concentration with the exception of dust where CDNC is very sensitive to particle hydrophilicity over arid areas. Regionally, the sensitivities differ considerably between the two frameworks and quantitatively reveal why the models differ considerably in their indirect forcing estimates.
Sensitivity Analysis and Identification of Parameters to the Van Genuchten Equation
Directory of Open Access Journals (Sweden)
Guangzhou Chen
2016-01-01
Full Text Available Van Genuchten equation is the soil water characteristic curve equation used commonly, and identifying (estimating accurately its parameters plays an important role in the study on the movement of soil water. Selecting the desorption and absorption experimental data of silt loam from a northwest region in China as an instance, Monte-Carlo method was firstly applied to analyze sensitivity of the parameters and uncertainty of model so as to get the key parameters and posteriori parameter distribution to guide subsequent parameter identification. Then, the optimization model of the parameters was set up, and a new type of intelligent algorithm-difference search algorithm was employed to identify them. In order to overcome the fault that the base difference search algorithm needed more iterations and to further enhance the optimization performance, a hybrid algorithm, which coupled the difference search algorithm with simplex method, was employed to identification of the parameters. By comparison with other optimization algorithms, the results show that the difference search algorithm has the following characteristics: good optimization performance, the simple principle, easy implement, short program code, and less control parameters required to run the algorithm. In addition, the proposed hybrid algorithm outperforms the basic difference search algorithm on the comprehensive performance of algorithm.
Parameter Estimation of Partial Differential Equation Models.
Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab
2013-01-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.
Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation
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.
Quality assessment for radiological model parameters
International Nuclear Information System (INIS)
Funtowicz, S.O.
1989-01-01
A prototype framework for representing uncertainties in radiological model parameters is introduced. This follows earlier development in this journal of a corresponding framework for representing uncertainties in radiological data. Refinements and extensions to the earlier framework are needed in order to take account of the additional contextual factors consequent on using data entries to quantify model parameters. The parameter coding can in turn feed in to methods for evaluating uncertainties in calculated model outputs. (author)
Lutchen, K R
1990-08-01
A sensitivity analysis based on weighted least-squares regression is presented to evaluate alternative methods for fitting lumped-parameter models to respiratory impedance data. The goal is to maintain parameter accuracy simultaneously with practical experiment design. The analysis focuses on predicting parameter uncertainties using a linearized approximation for joint confidence regions. Applications are with four-element parallel and viscoelastic models for 0.125- to 4-Hz data and a six-element model with separate tissue and airway properties for input and transfer impedance data from 2-64 Hz. The criterion function form was evaluated by comparing parameter uncertainties when data are fit as magnitude and phase, dynamic resistance and compliance, or real and imaginary parts of input impedance. The proper choice of weighting can make all three criterion variables comparable. For the six-element model, parameter uncertainties were predicted when both input impedance and transfer impedance are acquired and fit simultaneously. A fit to both data sets from 4 to 64 Hz could reduce parameter estimate uncertainties considerably from those achievable by fitting either alone. For the four-element models, use of an independent, but noisy, measure of static compliance was assessed as a constraint on model parameters. This may allow acceptable parameter uncertainties for a minimum frequency of 0.275-0.375 Hz rather than 0.125 Hz. This reduces data acquisition requirements from a 16- to a 5.33- to 8-s breath holding period. These results are approximations, and the impact of using the linearized approximation for the confidence regions is discussed.
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.
Establishing statistical models of manufacturing parameters
International Nuclear Information System (INIS)
Senevat, J.; Pape, J.L.; Deshayes, J.F.
1991-01-01
This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature
Institute of Scientific and Technical Information of China (English)
李一哲; 张廷龙; 刘秋雨; 李英
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 with the spatial
Parameter Sensitivity Study for Typical Expander-Based Transcritical CO2 Refrigeration Cycles
Directory of Open Access Journals (Sweden)
Bo Zhang
2018-05-01
Full Text Available A sensitivity study was conducted for three typical expander-based transcritical CO2 cycles with the developed simulation model, and the sensitivities of the maximum coefficient of performance (COP to the key operating parameters, including the inlet pressure of gas cooler, the temperatures at evaporator inlet and gas cooler outlet, the inter-stage pressure and the isentropic efficiency of expander, were obtained. The results showed that the sensitivity to the gas cooler inlet pressure differs greatly before and after the optimal gas cooler inlet pressure. The sensitivity to the intercooler outlet temperature in the two-stage cycles increases sharply to near zero and then keeps almost constant at intercooler outlet temperature of higher than 45 °C. However, the sensitivity stabilizes near zero when the evaporator inlet temperature is very low of −26.1 °C. In two-stage compression with an intercooler and an expander assisting in driving the first-stage compressor (TEADFC cycle, an abrupt change in the sensitivity of maximum COP to the inter-stage pressure was observed, but disappeared after intercooler outlet temperature exceeds 50 °C. The sensitivity of maximum COP to the expander isentropic efficiency increases almost linearly with the expander isentropic efficiency.
Calculation of integral parameters sensitivity in fast reactors
International Nuclear Information System (INIS)
Renke, C.A.C.
1981-01-01
The variational formulation, incorporated to VARI-1D computer code is used the sensitivity calculations. At a first stage the direct method was also used with the objective of establishing a parallel between the two methods.(E.G.) [pt
Harshan, S.; Roth, M.; Velasco, E.
2014-12-01
Forecasting of the urban weather and climate is of great importance as our cities become more populated and considering the combined effects of global warming and local land use changes which make urban inhabitants more vulnerable to e.g. heat waves and flash floods. In meso/global scale models, urban parameterization schemes are used to represent the urban effects. However, these schemes require a large set of input parameters related to urban morphological and thermal properties. Obtaining all these parameters through direct measurements are usually not feasible. A number of studies have reported on parameter estimation and sensitivity analysis to adjust and determine the most influential parameters for land surface schemes in non-urban areas. Similar work for urban areas is scarce, in particular studies on urban parameterization schemes in tropical cities have so far not been reported. In order to address above issues, the town energy balance (TEB) urban parameterization scheme (part of the SURFEX land surface modeling system) was subjected to a sensitivity and optimization/parameter estimation experiment at a suburban site in, tropical Singapore. The sensitivity analysis was carried out as a screening test to identify the most sensitive or influential parameters. Thereafter, an optimization/parameter estimation experiment was performed to calibrate the input parameter. The sensitivity experiment was based on the "improved Sobol's global variance decomposition method" . The analysis showed that parameters related to road, roof and soil moisture have significant influence on the performance of the model. The optimization/parameter estimation experiment was performed using the AMALGM (a multi-algorithm genetically adaptive multi-objective method) evolutionary algorithm. The experiment showed a remarkable improvement compared to the simulations using the default parameter set. The calibrated parameters from this optimization experiment can be used for further model
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
Sensitivity analysis of physiochemical interaction model: which pair ...
African Journals Online (AJOL)
... of two model parameters at a time on the solution trajectory of physiochemical interaction over a time interval. Our aim is to use this powerful mathematical technique to select the important pair of parameters of this physical process which is cost-effective. Keywords: Passivation Rate, Sensitivity Analysis, ODE23, ODE45 ...
Energy Technology Data Exchange (ETDEWEB)
Garza, J. [University of Texas at San Antonio, Mechanical Engineering, 1 UTSA circle, EB 3.04.50, San Antonio, TX 78249 (United States); Millwater, H., E-mail: harry.millwater@utsa.edu [University of Texas at San Antonio, Mechanical Engineering, 1 UTSA circle, EB 3.04.50, San Antonio, TX 78249 (United States)
2012-04-15
A methodology has been developed and demonstrated that can be used to compute the sensitivity of the probability-of-failure (POF) with respect to the parameters of inspection processes that are simulated using probability of detection (POD) curves. The formulation is such that the probabilistic sensitivities can be obtained at negligible cost using sampling methods by reusing the samples used to compute the POF. As a result, the methodology can be implemented for negligible cost in a post-processing non-intrusive manner thereby facilitating implementation with existing or commercial codes. The formulation is generic and not limited to any specific random variables, fracture mechanics formulation, or any specific POD curve as long as the POD is modeled parametrically. Sensitivity estimates for the cases of different POD curves at multiple inspections, and the same POD curves at multiple inspections have been derived. Several numerical examples are presented and show excellent agreement with finite difference estimates with significant computational savings. - Highlights: Black-Right-Pointing-Pointer Sensitivity of the probability-of-failure with respect to the probability-of-detection curve. Black-Right-Pointing-Pointer The sensitivities are computed with negligible cost using Monte Carlo sampling. Black-Right-Pointing-Pointer The change in the POF due to a change in the POD curve parameters can be easily estimated.
International Nuclear Information System (INIS)
Garza, J.; Millwater, H.
2012-01-01
A methodology has been developed and demonstrated that can be used to compute the sensitivity of the probability-of-failure (POF) with respect to the parameters of inspection processes that are simulated using probability of detection (POD) curves. The formulation is such that the probabilistic sensitivities can be obtained at negligible cost using sampling methods by reusing the samples used to compute the POF. As a result, the methodology can be implemented for negligible cost in a post-processing non-intrusive manner thereby facilitating implementation with existing or commercial codes. The formulation is generic and not limited to any specific random variables, fracture mechanics formulation, or any specific POD curve as long as the POD is modeled parametrically. Sensitivity estimates for the cases of different POD curves at multiple inspections, and the same POD curves at multiple inspections have been derived. Several numerical examples are presented and show excellent agreement with finite difference estimates with significant computational savings. - Highlights: ► Sensitivity of the probability-of-failure with respect to the probability-of-detection curve. ►The sensitivities are computed with negligible cost using Monte Carlo sampling. ► The change in the POF due to a change in the POD curve parameters can be easily estimated.
A global sensitivity analysis approach for morphogenesis models
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.
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.
On parameter estimation in deformable models
DEFF Research Database (Denmark)
Fisker, Rune; Carstensen, Jens Michael
1998-01-01
Deformable templates have been intensively studied in image analysis through the last decade, but despite its significance the estimation of model parameters has received little attention. We present a method for supervised and unsupervised model parameter estimation using a general Bayesian form...
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
International Nuclear Information System (INIS)
Labadi, Karim; Saggadi, Samira; Amodeo, Lionel
2009-01-01
The dynamic behavior of a discrete event dynamic system can be significantly affected for some uncertain changes in its decision parameters. So, parameter sensitivity analysis would be a useful way in studying the effects of these changes on the system performance. In the past, the sensitivity analysis approaches are frequently based on simulation models. In recent years, formal methods based on stochastic process including Markov process are proposed in the literature. In this paper, we are interested in the parameter sensitivity analysis of discrete event dynamic systems by using stochastic Petri nets models as a tool for modelling and performance evaluation. A sensitivity analysis approach based on stochastic Petri nets, called PSA-SPN method, will be proposed with an application to a production line system.
Energy Technology Data Exchange (ETDEWEB)
Goldstein, Peter [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2014-01-24
This report describes the sensitivity of predicted nuclear fallout to a variety of model input parameters, including yield, height of burst, particle and activity size distribution parameters, wind speed, wind direction, topography, and precipitation. We investigate sensitivity over a wide but plausible range of model input parameters. In addition, we investigate a specific example with a relatively narrow range to illustrate the potential for evaluating uncertainties in predictions when there are more precise constraints on model parameters.
Sensitivity and uncertainty analyses for performance assessment modeling
International Nuclear Information System (INIS)
Doctor, P.G.
1988-08-01
Sensitivity and uncertainty analyses methods for computer models are being applied in performance assessment modeling in the geologic high level radioactive waste repository program. The models used in performance assessment tend to be complex physical/chemical models with large numbers of input variables. There are two basic approaches to sensitivity and uncertainty analyses: deterministic and statistical. The deterministic approach to sensitivity analysis involves numerical calculation or employs the adjoint form of a partial differential equation to compute partial derivatives; the uncertainty analysis is based on Taylor series expansions of the input variables propagated through the model to compute means and variances of the output variable. The statistical approach to sensitivity analysis involves a response surface approximation to the model with the sensitivity coefficients calculated from the response surface parameters; the uncertainty analysis is based on simulation. The methods each have strengths and weaknesses. 44 refs
Parameter identification in multinomial processing tree models
Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.
2010-01-01
Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei
2013-09-01
Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown and need to be estimated from the measurements of the dynamic system in the presence of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from long-range infrared light detection and ranging data. Supplementary materials for this article are available online. © 2013 American Statistical Association.
da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; Picanço, Marcelo Coutinho
2018-04-01
A sensitivity analysis can categorize levels of parameter influence on a model's output. Identifying parameters having the most influence facilitates establishing the best values for parameters of models, providing useful implications in species modelling of crops and associated insect pests. The aim of this study was to quantify the response of species models through a CLIMEX sensitivity analysis. Using open-field Solanum lycopersicum and Neoleucinodes elegantalis distribution records, and 17 fitting parameters, including growth and stress parameters, comparisons were made in model performance by altering one parameter value at a time, in comparison to the best-fit parameter values. Parameters that were found to have a greater effect on the model results are termed "sensitive". Through the use of two species, we show that even when the Ecoclimatic Index has a major change through upward or downward parameter value alterations, the effect on the species is dependent on the selection of suitability categories and regions of modelling. Two parameters were shown to have the greatest sensitivity, dependent on the suitability categories of each species in the study. Results enhance user understanding of which climatic factors had a greater impact on both species distributions in our model, in terms of suitability categories and areas, when parameter values were perturbed by higher or lower values, compared to the best-fit parameter values. Thus, the sensitivity analyses have the potential to provide additional information for end users, in terms of improving management, by identifying the climatic variables that are most sensitive.
Sensitivity coefficients of reactor parameters in fast critical assemblies and uncertainty analysis
International Nuclear Information System (INIS)
Aoyama, Takafumi; Suzuki, Takayuki; Takeda, Toshikazu; Hasegawa, Akira; Kikuchi, Yasuyuki.
1986-02-01
Sensitivity coefficients of reactor parameters in several fast critical assemblies to various cross sections were calculated in 16 group by means of SAGEP code based on the generalized perturbation theory. The sensitivity coefficients were tabulated and the difference of sensitivity coefficients was discussed. Furthermore, the uncertainty of calculated reactor parameters due to cross section uncertainty were estimated using the sensitivity coefficients and cross section covariance data. (author)
International Nuclear Information System (INIS)
Adelman, D.D.; Stansbury, J.
1997-01-01
The Resource Conservation and Recovery Act (RCRA) Subtitle C, Comprehensive Environmental Response, Compensation, And Liability Act (CERCLA), and subsequent amendments have formed a comprehensive framework to deal with hazardous wastes on the national level. Key to this waste management is guidance on design (e.g., cover and bottom leachate control systems) of hazardous waste landfills. The objective of this research was to investigate the sensitivity of leachate volume at hazardous waste disposal sites to climatic, soil cover, and vegetative cover (Leaf Area Index) conditions. The computer model HELP3 which has the capability to simulate double bottom liner systems as called for in hazardous waste disposal sites was used in the analysis. HELP3 was used to model 54 combinations of climatic conditions, disposal site soil surface curve numbers, and leaf area index values to investigate how sensitive disposal site leachate volume was to these three variables. Results showed that leachate volume from the bottom double liner system was not sensitive to these parameters. However, the cover liner system leachate volume was quite sensitive to climatic conditions and less sensitive to Leaf Area Index and curve number values. Since humid locations had considerably more cover liner system leachate volume than and locations, different design standards may be appropriate for humid conditions than for and conditions
PARAMETER ESTIMATION IN BREAD BAKING MODEL
Directory of Open Access Journals (Sweden)
Hadiyanto Hadiyanto
2012-05-01
Full Text Available Bread product quality is highly dependent to the baking process. A model for the development of product quality, which was obtained by using quantitative and qualitative relationships, was calibrated by experiments at a fixed baking temperature of 200°C alone and in combination with 100 W microwave powers. The model parameters were estimated in a stepwise procedure i.e. first, heat and mass transfer related parameters, then the parameters related to product transformations and finally product quality parameters. There was a fair agreement between the calibrated model results and the experimental data. The results showed that the applied simple qualitative relationships for quality performed above expectation. Furthermore, it was confirmed that the microwave input is most meaningful for the internal product properties and not for the surface properties as crispness and color. The model with adjusted parameters was applied in a quality driven food process design procedure to derive a dynamic operation pattern, which was subsequently tested experimentally to calibrate the model. Despite the limited calibration with fixed operation settings, the model predicted well on the behavior under dynamic convective operation and on combined convective and microwave operation. It was expected that the suitability between model and baking system could be improved further by performing calibration experiments at higher temperature and various microwave power levels. Abstrak PERKIRAAN PARAMETER DALAM MODEL UNTUK PROSES BAKING ROTI. Kualitas produk roti sangat tergantung pada proses baking yang digunakan. Suatu model yang telah dikembangkan dengan metode kualitatif dan kuantitaif telah dikalibrasi dengan percobaan pada temperatur 200oC dan dengan kombinasi dengan mikrowave pada 100 Watt. Parameter-parameter model diestimasi dengan prosedur bertahap yaitu pertama, parameter pada model perpindahan masa dan panas, parameter pada model transformasi, dan
On the role of modeling parameters in IMRT plan optimization
International Nuclear Information System (INIS)
Krause, Michael; Scherrer, Alexander; Thieke, Christian
2008-01-01
The formulation of optimization problems in intensity-modulated radiotherapy (IMRT) planning comprises the choice of various values such as function-specific parameters or constraint bounds. In current inverse planning programs that yield a single treatment plan for each optimization, it is often unclear how strongly these modeling parameters affect the resulting plan. This work investigates the mathematical concepts of elasticity and sensitivity to deal with this problem. An artificial planning case with a horse-shoe formed target with different opening angles surrounding a circular risk structure is studied. As evaluation functions the generalized equivalent uniform dose (EUD) and the average underdosage below and average overdosage beyond certain dose thresholds are used. A single IMRT plan is calculated for an exemplary parameter configuration. The elasticity and sensitivity of each parameter are then calculated without re-optimization, and the results are numerically verified. The results show the following. (1) elasticity can quantify the influence of a modeling parameter on the optimization result in terms of how strongly the objective function value varies under modifications of the parameter value. It also can describe how strongly the geometry of the involved planning structures affects the optimization result. (2) Based on the current parameter settings and corresponding treatment plan, sensitivity analysis can predict the optimization result for modified parameter values without re-optimization, and it can estimate the value intervals in which such predictions are valid. In conclusion, elasticity and sensitivity can provide helpful tools in inverse IMRT planning to identify the most critical parameters of an individual planning problem and to modify their values in an appropriate way
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...
International Nuclear Information System (INIS)
Sola, A.
1978-01-01
An analytical sensitivity analysis has been made of the effect of various parameters on the evaluation of fission product concentration. Such parameters include cross sections, decay constants, branching ratios, fission yields, flux and time. The formulae are applied to isotopes of the Tin, Antimony and Tellurium series. The agreement between analytically obtained data and that derived from a computer evaluated model is good, suggesting that the analytical representation includes all the important parameters useful to the evaluation of the fission product concentrations
Parameter identification in the logistic STAR model
DEFF Research Database (Denmark)
Ekner, Line Elvstrøm; Nejstgaard, Emil
We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th...
Sensitivity of Asteroid Impact Risk to Uncertainty in Asteroid Properties and Entry Parameters
Wheeler, Lorien; Mathias, Donovan; Dotson, Jessie L.; NASA Asteroid Threat Assessment Project
2017-10-01
A central challenge in assessing the threat posed by asteroids striking Earth is the large amount of uncertainty inherent throughout all aspects of the problem. Many asteroid properties are not well characterized and can range widely from strong, dense, monolithic irons to loosely bound, highly porous rubble piles. Even for an object of known properties, the specific entry velocity, angle, and impact location can swing the potential consequence from no damage to causing millions of casualties. Due to the extreme rarity of large asteroid strikes, there are also large uncertainties in how different types of asteroids will interact with the atmosphere during entry, how readily they may break up or ablate, and how much surface damage will be caused by the resulting airbursts or impacts.In this work, we use our Probabilistic Asteroid Impact Risk (PAIR) model to investigate the sensitivity of asteroid impact damage to uncertainties in key asteroid properties, entry parameters, or modeling assumptions. The PAIR model combines physics-based analytic models of asteroid entry and damage in a probabilistic Monte Carlo framework to assess the risk posed by a wide range of potential impacts. The model samples from uncertainty distributions of asteroid properties and entry parameters to generate millions of specific impact cases, and models the atmospheric entry and damage for each case, including blast overpressure, thermal radiation, tsunami inundation, and global effects. To assess the risk sensitivity, we alternately fix and vary the different input parameters and compare the effect on the resulting range of damage produced. The goal of these studies is to help guide future efforts in asteroid characterization and model refinement by determining which properties most significantly affect the potential risk.
Energy Technology Data Exchange (ETDEWEB)
McCarty, Rachael; Nima Mahmoodi, S., E-mail: nmahmoodi@eng.ua.edu [Department of Mechanical Engineering, The University of Alabama, Box 870276, Tuscaloosa, Alabama 35487 (United States)
2014-02-21
The equations of motion for a piezoelectric microcantilever are derived for a nonlinear contact force. The analytical expressions for natural frequencies and mode shapes are obtained. Then, the method of multiple scales is used to analyze the analytical frequency response of the piezoelectric probe. The effects of nonlinear excitation force on the microcantilever beam's frequency and amplitude are analytically studied. The results show a frequency shift in the response resulting from the force nonlinearities. This frequency shift during contact mode is an important consideration in the modeling of AFM mechanics for generation of more accurate imaging. Also, a sensitivity analysis of the system parameters on the nonlinearity effect is performed. The results of a sensitivity analysis show that it is possible to choose parameters such that the frequency shift minimizes. Certain parameters such as tip radius, microcantilever beam dimensions, and modulus of elasticity have more influence on the nonlinearity of the system than other parameters. By changing only three parameters—tip radius, thickness, and modulus of elasticity of the microbeam—a more than 70% reduction in nonlinearity effect was achieved.
CCP Sensitivity Analysis by Variation of Thermal-Hydraulic Parameters of Wolsong-3, 4
Energy Technology Data Exchange (ETDEWEB)
You, Sung Chang [KHNP, Daejeon (Korea, Republic of)
2016-10-15
The PHWRs are tendency that ROPT(Regional Overpower Protection Trip) setpoint is decreased with reduction of CCP(Critical Channel Power) due to aging effects. For this reason, Wolsong unit 3 and 4 has been operated less than 100% power due to the result of ROPT setpoint evaluation. Typically CCP for ROPT evaluation is derived at 100% PHTS(Primary Heat Transport System) boundary conditions - inlet header temperature, header to header different pressure and outlet header pressure. Therefore boundary conditions at 100% power were estimated to calculate the thermal-hydraulic model at 100% power condition. Actually thermal-hydraulic boundary condition data for Wolsong-3 and 4 cannot be taken at 100% power condition at aged reactor condition. Therefore, to create a single-phase thermal-hydraulic model with 80% data, the validity of the model was confirmed at 93.8%(W3), 94.2%(W4, in the two-phase). And thermal-hydraulic boundary conditions at 100% power were calculated to use this model. For this reason, the sensitivities by varying thermal-hydraulic parameters for CCP calculation were evaluated for Wolsong unit 3 and 4. For confirming the uncertainties by variation PHTS model, sensitivity calculations were performed by varying of pressure tube roughness, orifice degradation factor and SG fouling factor, etc. In conclusion, sensitivity calculation results were very similar and the linearity was constant.
Ambient pressure sensitivity of microbubbles investigated through a parameter study
DEFF Research Database (Denmark)
Andersen, Klaus Scheldrup; Jensen, Jørgen Arendt
2009-01-01
Measurements on microbubbles clearly indicate a relation between the ambient pressure and the acoustic behavior of the bubble. The purpose of this study was to optimize the sensitivity of ambient pressure measurements, using the subharmonic component, through microbubble response simulations....... The behavior of two microbubbles corresponding to two different contrast agents was investigated as a function of driving pulse and ambient overpressure, pov. Simulations of Levovist using a rectangular driving pulse show an almost linear reduction in the subharmonic component as pov is increased. For a 20...... found, although the reduction is not completely linear as a function of the ambient pressure....
Exploiting intrinsic fluctuations to identify model parameters.
Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen
2015-04-01
Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.
Setting Parameters for Biological Models With ANIMO
Schivo, Stefano; Scholma, Jetse; Karperien, Hermanus Bernardus Johannes; Post, Janine Nicole; van de Pol, Jan Cornelis; Langerak, Romanus; André, Étienne; Frehse, Goran
2014-01-01
ANIMO (Analysis of Networks with Interactive MOdeling) is a software for modeling biological networks, such as e.g. signaling, metabolic or gene networks. An ANIMO model is essentially the sum of a network topology and a number of interaction parameters. The topology describes the interactions
International Nuclear Information System (INIS)
Heo, Jaeseok; Kim, Kyung Doo
2015-01-01
Highlights: • We developed an interface between an engineering simulation code and statistical analysis software. • Multiple packages of the sensitivity analysis, uncertainty quantification, and parameter estimation algorithms are implemented in the framework. • Parallel computing algorithms are also implemented in the framework to solve multiple computational problems simultaneously. - Abstract: This paper introduces a statistical data analysis toolkit, PAPIRUS, designed to perform the model calibration, uncertainty propagation, Chi-square linearity test, and sensitivity analysis for both linear and nonlinear problems. The PAPIRUS was developed by implementing multiple packages of methodologies, and building an interface between an engineering simulation code and the statistical analysis algorithms. A parallel computing framework is implemented in the PAPIRUS with multiple computing resources and proper communications between the server and the clients of each processor. It was shown that even though a large amount of data is considered for the engineering calculation, the distributions of the model parameters and the calculation results can be quantified accurately with significant reductions in computational effort. A general description about the PAPIRUS with a graphical user interface is presented in Section 2. Sections 2.1–2.5 present the methodologies of data assimilation, uncertainty propagation, Chi-square linearity test, and sensitivity analysis implemented in the toolkit with some results obtained by each module of the software. Parallel computing algorithms adopted in the framework to solve multiple computational problems simultaneously are also summarized in the paper
Energy Technology Data Exchange (ETDEWEB)
Heo, Jaeseok, E-mail: jheo@kaeri.re.kr; Kim, Kyung Doo, E-mail: kdkim@kaeri.re.kr
2015-10-15
Highlights: • We developed an interface between an engineering simulation code and statistical analysis software. • Multiple packages of the sensitivity analysis, uncertainty quantification, and parameter estimation algorithms are implemented in the framework. • Parallel computing algorithms are also implemented in the framework to solve multiple computational problems simultaneously. - Abstract: This paper introduces a statistical data analysis toolkit, PAPIRUS, designed to perform the model calibration, uncertainty propagation, Chi-square linearity test, and sensitivity analysis for both linear and nonlinear problems. The PAPIRUS was developed by implementing multiple packages of methodologies, and building an interface between an engineering simulation code and the statistical analysis algorithms. A parallel computing framework is implemented in the PAPIRUS with multiple computing resources and proper communications between the server and the clients of each processor. It was shown that even though a large amount of data is considered for the engineering calculation, the distributions of the model parameters and the calculation results can be quantified accurately with significant reductions in computational effort. A general description about the PAPIRUS with a graphical user interface is presented in Section 2. Sections 2.1–2.5 present the methodologies of data assimilation, uncertainty propagation, Chi-square linearity test, and sensitivity analysis implemented in the toolkit with some results obtained by each module of the software. Parallel computing algorithms adopted in the framework to solve multiple computational problems simultaneously are also summarized in the paper.
Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue
2009-01-01
We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.
Parameters and error of a theoretical model
International Nuclear Information System (INIS)
Moeller, P.; Nix, J.R.; Swiatecki, W.
1986-09-01
We propose a definition for the error of a theoretical model of the type whose parameters are determined from adjustment to experimental data. By applying a standard statistical method, the maximum-likelihoodlmethod, we derive expressions for both the parameters of the theoretical model and its error. We investigate the derived equations by solving them for simulated experimental and theoretical quantities generated by use of random number generators. 2 refs., 4 tabs
Parameter Estimation of Nonlinear Models in Forestry.
Fekedulegn, Desta; Mac Siúrtáin, Máirtín Pádraig; Colbert, Jim J.
1999-01-01
Partial derivatives of the negative exponential, monomolecular, Mitcherlich, Gompertz, logistic, Chapman-Richards, von Bertalanffy, Weibull and the Richard’s nonlinear growth models are presented. The application of these partial derivatives in estimating the model parameters is illustrated. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating top height to age of Norway spruce (Picea abies L.) from the Bowmont Norway Spruce Thinnin...
Masterlark, Timothy; Donovan, Theodore; Feigl, Kurt L.; Haney, Matt; Thurber, Clifford H.; Tung, Sui
2016-01-01
The eruption cycle of a volcano is controlled in part by the upward migration of magma. The characteristics of the magma flux produce a deformation signature at the Earth's surface. Inverse analyses use geodetic data to estimate strategic controlling parameters that describe the position and pressurization of a magma chamber at depth. The specific distribution of material properties controls how observed surface deformation translates to source parameter estimates. Seismic tomography models describe the spatial distributions of material properties that are necessary for accurate models of volcano deformation. This study investigates how uncertainties in seismic tomography models propagate into variations in the estimates of volcano deformation source parameters inverted from geodetic data. We conduct finite element model-based nonlinear inverse analyses of interferometric synthetic aperture radar (InSAR) data for Okmok volcano, Alaska, as an example. We then analyze the estimated parameters and their uncertainties to characterize the magma chamber. Analyses are performed separately for models simulating a pressurized chamber embedded in a homogeneous domain as well as for a domain having a heterogeneous distribution of material properties according to seismic tomography. The estimated depth of the source is sensitive to the distribution of material properties. The estimated depths for the homogeneous and heterogeneous domains are 2666 ± 42 and 3527 ± 56 m below mean sea level, respectively (99% confidence). A Monte Carlo analysis indicates that uncertainties of the seismic tomography cannot account for this discrepancy at the 99% confidence level. Accounting for the spatial distribution of elastic properties according to seismic tomography significantly improves the fit of the deformation model predictions and significantly influences estimates for parameters that describe the location of a pressurized magma chamber.
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 ...
Determining extreme parameter correlation in ground water models
DEFF Research Database (Denmark)
Hill, Mary Cole; Østerby, Ole
2003-01-01
can go undetected even by experienced modelers. Extreme parameter correlation can be detected using parameter correlation coefficients, but their utility depends on the presence of sufficient, but not excessive, numerical imprecision of the sensitivities, such as round-off error. This work...... investigates the information that can be obtained from parameter correlation coefficients in the presence of different levels of numerical imprecision, and compares it to the information provided by an alternative method called the singular value decomposition (SVD). Results suggest that (1) calculated...... correlation coefficients with absolute values that round to 1.00 were good indicators of extreme parameter correlation, but smaller values were not necessarily good indicators of lack of correlation and resulting unique parameter estimates; (2) the SVD may be more difficult to interpret than parameter...
Sensitivity Analysis of an Agent-Based Model of Culture's Consequences for Trade
Burgers, S.L.G.E.; Jonker, C.M.; Hofstede, G.J.; Verwaart, D.
2010-01-01
This paper describes the analysis of an agent-based model’s sensitivity to changes in parameters that describe the agents’ cultural background, relational parameters, and parameters of the decision functions. As agent-based models may be very sensitive to small changes in parameter values, it is of
Yu, Tao; Kang, Chao; Zhao, Pan
2018-01-01
The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048
van Hirtum, Annemie; Lopez, Ines; Hirschberg, Abraham; Pelorson, Xavier
2003-01-01
In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is
Hirtum, van A.; Lopez Arteaga, I.; Hirschberg, A.; Pelorson, X.
2003-01-01
In this paper the sensitivity of the two-mass model with acoustical coupling to the model input-parameters is assessed. The model-output or the glottal volume air flow is characterised by signal-parameters in the time-domain. The influence of changing input-parameters on the signal-parameters is
International Nuclear Information System (INIS)
Grishchenko, Dmitry; Basso, Simone; Kudinov, Pavel; Bechta, Sevostian
2014-01-01
Release of core melt from failed reactor vessel into a pool of water is adopted in several existing designs of light water reactors (LWRs) as an element of severe accident mitigation strategy. Corium melt is expected to fragment, solidify and form a debris bed coolable by natural circulation. However, steam explosion can occur upon melt release threatening containment integrity and potentially leading to large early release of radioactive products to the environment. There are many factors and parameters that could be considered for prediction of the fuel-coolant interaction (FCI) energetics, but it is not clear which of them are the most influential and should be addressed in risk analysis. The goal of this work is to assess importance of different uncertain input parameters used in FCI code TEXAS-V for prediction of the steam explosion energetics. Both aleatory uncertainty in characteristics of melt release scenarios and water pool conditions, and epistemic uncertainty in modeling are considered. Ranges of the uncertain parameters are selected based on the available information about prototypic severe accident conditions in a reference design of a Nordic BWR. Sensitivity analysis with Morris method is implemented using coupled TEXAS-V and DAKOTA codes. In total 12 input parameters were studied and 2 melt release scenarios were considered. Each scenario is based on 60,000 of TEXAS-V runs. Sensitivity study identified the most influential input parameters, and those which have no statistically significant effect on the explosion energetics. Details of approach to robust usage of TEXAS-V input, statistical enveloping of TEXAS-V output and interpretation of the results are discussed in the paper. We also provide probability density function (PDF) of steam explosion impulse estimated using TEXAS-V for reference Nordic BWR. It can be used for assessment of the uncertainty ranges of steam explosion loads for given ranges of input parameters. (author)
Sensitivity analysis on parameters and processes affecting vapor intrusion risk
Picone, Sara; Valstar, Johan; van Gaans, Pauline; Grotenhuis, Tim; Rijnaarts, Huub
2012-01-01
the ventilated crawl space of a house. In contrast to the vast majority of previous studies, this model accounts for vertical variation of soil water saturation and includes aerobic biodegradation. The attenuation factor (ratio between concentration in the crawl
Wind Farm Decentralized Dynamic Modeling With Parameters
DEFF Research Database (Denmark)
Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran
2010-01-01
Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...
Parameter Estimation for Thurstone Choice Models
Energy Technology Data Exchange (ETDEWEB)
Vojnovic, Milan [London School of Economics (United Kingdom); Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-04-24
We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one or more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.
Systematic parameter inference in stochastic mesoscopic modeling
Energy Technology Data Exchange (ETDEWEB)
Lei, Huan; Yang, Xiu [Pacific Northwest National Laboratory, Richland, WA 99352 (United States); Li, Zhen [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States); Karniadakis, George Em, E-mail: george_karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, RI 02912 (United States)
2017-02-01
We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.
Directory of Open Access Journals (Sweden)
Sankar N. Bhattacharya
2015-11-01
Full Text Available Sensitivity kernels or partial derivatives of phase velocity (c and group velocity (U with respect to medium parameters are useful to interpret a given set of observed surface wave velocity data. In addition to phase velocities, group velocities are also being observed to find the radial anisotropy of the crust and mantle. However, sensitivities of group velocity for a radially anisotropic Earth have rarely been studied. Here we show sensitivities of group velocity along with those of phase velocity to the medium parameters VSV, VSH , VPV, VPH , h and density in a radially anisotropic spherical Earth. The peak sensitivities for U are generally twice of those for c; thus U is more efficient than c to explore anisotropic nature of the medium. Love waves mainly depends on VSH while Rayleigh waves is nearly independent of VSH . The sensitivities show that there are trade-offs among these parameters during inversion and there is a need to reduce the number of parameters to be evaluated independently. It is suggested to use a nonlinear inversion jointly for Rayleigh and Love waves; in such a nonlinear inversion best solutions are obtained among the model parameters within prescribed limits for each parameter. We first choose VSH, VSV and VPH within their corresponding limits; VPV and h can be evaluated from empirical relations among the parameters. The density has small effect on surface wave velocities and it can be considered from other studies or from empirical relation of density to average P-wave velocity.
Parameters influencing deposit estimation when using water sensitive papers
Directory of Open Access Journals (Sweden)
Emanuele Cerruto
2013-10-01
Full Text Available The aim of the study was to assess the possibility of using water sensitive papers (WSP to estimate the amount of deposit on the target when varying the spray characteristics. To identify the main quantities influencing the deposit, some simplifying hypotheses were applied to simulate WSP behaviour: log-normal distribution of the diameters of the drops and circular stains randomly placed on the images. A very large number (4704 of images of WSPs were produced by means of simulation. The images were obtained by simulating drops of different arithmetic mean diameter (40-300 μm, different coefficient of variation (0.1-1.5, and different percentage of covered surface (2-100%, not considering overlaps. These images were considered to be effective WSP images and then analysed using image processing software in order to measure the percentage of covered surface, the number of particles, and the area of each particle; the deposit was then calculated. These data were correlated with those used to produce the images, varying the spray characteristics. As far as the drop populations are concerned, a classification based on the volume median diameter only should be avoided, especially in case of high variability. This, in fact, results in classifying sprays with very low arithmetic mean diameter as extremely or ultra coarse. The WSP image analysis shows that the relation between simulated and computed percentage of covered surface is independent of the type of spray, whereas impact density and unitary deposit can be estimated from the computed percentage of covered surface only if the spray characteristics (arithmetic mean and coefficient of variation of the drop diameters are known. These data can be estimated by analysing the particles on the WSP images. The results of a validation test show good agreement between simulated and computed deposits, testified by a high (0.93 coefficient of determination.
Application of lumped-parameter models
DEFF Research Database (Denmark)
Ibsen, Lars Bo; Liingaard, Morten
This technical report concerns the lumped-parameter models for a suction caisson with a ratio between skirt length and foundation diameter equal to 1/2, embedded into an viscoelastic soil. The models are presented for three different values of the shear modulus of the subsoil (section 1.1). Subse...
Models and parameters for environmental radiological assessments
International Nuclear Information System (INIS)
Miller, C.W.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base
WINKLER'S SINGLE-PARAMETER SUBGRADE MODEL FROM ...
African Journals Online (AJOL)
Preferred Customer
Page 1 ... corresponding single-parameter Winkler model presented in this work. Keywords: Heterogeneous subgrade, Reissner's simplified continuum, Shear interaction, Simplified continuum, Winkler ... model in practical applications and its long time familiarity among practical engineers, its usage has endured to this date ...
Models and parameters for environmental radiological assessments
Energy Technology Data Exchange (ETDEWEB)
Miller, C W [ed.
1984-01-01
This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base. (ACR)
Consistent Stochastic Modelling of Meteocean Design Parameters
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Sterndorff, M. J.
2000-01-01
Consistent stochastic models of metocean design parameters and their directional dependencies are essential for reliability assessment of offshore structures. In this paper a stochastic model for the annual maximum values of the significant wave height, and the associated wind velocity, current...
Models and parameters for environmental radiological assessments
International Nuclear Information System (INIS)
Miller, C.W.
1983-01-01
This article reviews the forthcoming book Models and Parameters for Environmental Radiological Assessments, which presents a unified compilation of models and parameters for assessing the impact on man of radioactive discharges, both routine and accidental, into the environment. Models presented in this book include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Summaries are presented for each of the transport and dosimetry areas previously for each of the transport and dosimetry areas previously mentioned, and details are available in the literature cited. A chapter of example problems illustrates many of the methodologies presented throughout the text. Models and parameters presented are based on the results of extensive literature reviews and evaluations performed primarily by the staff of the Health and Safety Research Division of Oak Ridge National Laboratory
Lumped-parameters equivalent circuit for condenser microphones modeling.
Esteves, Josué; Rufer, Libor; Ekeom, Didace; Basrour, Skandar
2017-10-01
This work presents a lumped parameters equivalent model of condenser microphone based on analogies between acoustic, mechanical, fluidic, and electrical domains. Parameters of the model were determined mainly through analytical relations and/or finite element method (FEM) simulations. Special attention was paid to the air gap modeling and to the use of proper boundary condition. Corresponding lumped-parameters were obtained as results of FEM simulations. Because of its simplicity, the model allows a fast simulation and is readily usable for microphone design. This work shows the validation of the equivalent circuit on three real cases of capacitive microphones, including both traditional and Micro-Electro-Mechanical Systems structures. In all cases, it has been demonstrated that the sensitivity and other related data obtained from the equivalent circuit are in very good agreement with available measurement data.
Source term modelling parameters for Project-90
International Nuclear Information System (INIS)
Shaw, W.; Smith, G.; Worgan, K.; Hodgkinson, D.; Andersson, K.
1992-04-01
This document summarises the input parameters for the source term modelling within Project-90. In the first place, the parameters relate to the CALIBRE near-field code which was developed for the Swedish Nuclear Power Inspectorate's (SKI) Project-90 reference repository safety assessment exercise. An attempt has been made to give best estimate values and, where appropriate, a range which is related to variations around base cases. It should be noted that the data sets contain amendments to those considered by KBS-3. In particular, a completely new set of inventory data has been incorporated. The information given here does not constitute a complete set of parameter values for all parts of the CALIBRE code. Rather, it gives the key parameter values which are used in the constituent models within CALIBRE and the associated studies. For example, the inventory data acts as an input to the calculation of the oxidant production rates, which influence the generation of a redox front. The same data is also an initial value data set for the radionuclide migration component of CALIBRE. Similarly, the geometrical parameters of the near-field are common to both sub-models. The principal common parameters are gathered here for ease of reference and avoidance of unnecessary duplication and transcription errors. (au)
Directory of Open Access Journals (Sweden)
V. Shutyaev
2018-06-01
Full Text Available The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find unknown parameters of the model. The observation data, and hence the optimal solution, may contain uncertainties. A response function is considered as a functional of the optimal solution after assimilation. Based on the second-order adjoint techniques, the sensitivity of the response function to the observation data is studied. The gradient of the response function is related to the solution of a nonstandard problem involving the coupled system of direct and adjoint equations. The nonstandard problem is studied, based on the Hessian of the original cost function. An algorithm to compute the gradient of the response function with respect to observations is presented. A numerical example is given for the variational data assimilation problem related to sea surface temperature for the Baltic Sea thermodynamics model.
International Nuclear Information System (INIS)
Tonk, Elisa C.M.; Verhoef, Aart; Gremmer, Eric R.; Loveren, Henk van; Piersma, Aldert H.
2012-01-01
The developing immune system displays a relatively high sensitivity as compared to both general toxicity parameters and to the adult immune system. In this study we have performed such comparisons using di(2-ethylhexyl) phthalate (DEHP) as a model compound. DEHP is the most abundant phthalate in the environment and perinatal exposure to DEHP has been shown to disrupt male sexual differentiation. In addition, phthalate exposure has been associated with immune dysfunction as evidenced by effects on the expression of allergy. Male wistar rats were dosed with corn oil or DEHP by gavage from postnatal day (PND) 10–50 or PND 50–90 at doses between 1 and 1000 mg/kg/day. Androgen-dependent organ weights showed effects at lower dose levels in juvenile versus adult animals. Immune parameters affected included TDAR parameters in both age groups, NK activity in juvenile animals and TNF-α production by adherent splenocytes in adult animals. Immune parameters were affected at lower dose levels compared to developmental parameters. Overall, more immune parameters were affected in juvenile animals compared to adult animals and effects were observed at lower dose levels. The results of this study show a relatively higher sensitivity of juvenile versus adult rats. Furthermore, they illustrate the relative sensitivity of the developing immune system in juvenile animals as compared to general toxicity and developmental parameters. This study therefore provides further argumentation for performing dedicated developmental immune toxicity testing as a default in regulatory toxicology. -- Highlights: ► In this study we evaluate the relative sensitivities for DEHP induced effects. ► Results of this study demonstrate the age-dependency of DEHP toxicity. ► Functional immune parameters were more sensitive than structural immune parameters. ► Immune parameters were affected at lower dose levels than developmental parameters. ► Findings demonstrate the susceptibility of the
Energy Technology Data Exchange (ETDEWEB)
Tonk, Elisa C.M., E-mail: ilse.tonk@rivm.nl [Department of Toxicogenomics, Maastricht University, Maastricht (Netherlands); Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Verhoef, Aart; Gremmer, Eric R. [Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Loveren, Henk van [Department of Toxicogenomics, Maastricht University, Maastricht (Netherlands); Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Piersma, Aldert H. [Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven (Netherlands); Institute for Risk Assessment Sciences, Veterinary Faculty, Utrecht University, Utrecht (Netherlands)
2012-04-01
The developing immune system displays a relatively high sensitivity as compared to both general toxicity parameters and to the adult immune system. In this study we have performed such comparisons using di(2-ethylhexyl) phthalate (DEHP) as a model compound. DEHP is the most abundant phthalate in the environment and perinatal exposure to DEHP has been shown to disrupt male sexual differentiation. In addition, phthalate exposure has been associated with immune dysfunction as evidenced by effects on the expression of allergy. Male wistar rats were dosed with corn oil or DEHP by gavage from postnatal day (PND) 10–50 or PND 50–90 at doses between 1 and 1000 mg/kg/day. Androgen-dependent organ weights showed effects at lower dose levels in juvenile versus adult animals. Immune parameters affected included TDAR parameters in both age groups, NK activity in juvenile animals and TNF-α production by adherent splenocytes in adult animals. Immune parameters were affected at lower dose levels compared to developmental parameters. Overall, more immune parameters were affected in juvenile animals compared to adult animals and effects were observed at lower dose levels. The results of this study show a relatively higher sensitivity of juvenile versus adult rats. Furthermore, they illustrate the relative sensitivity of the developing immune system in juvenile animals as compared to general toxicity and developmental parameters. This study therefore provides further argumentation for performing dedicated developmental immune toxicity testing as a default in regulatory toxicology. -- Highlights: ► In this study we evaluate the relative sensitivities for DEHP induced effects. ► Results of this study demonstrate the age-dependency of DEHP toxicity. ► Functional immune parameters were more sensitive than structural immune parameters. ► Immune parameters were affected at lower dose levels than developmental parameters. ► Findings demonstrate the susceptibility of the
Xu, Mengchen; Lerner, Amy L; Funkenbusch, Paul D; Richhariya, Ashutosh; Yoon, Geunyoung
2018-02-01
The optical performance of the human cornea under intraocular pressure (IOP) is the result of complex material properties and their interactions. The measurement of the numerous material parameters that define this material behavior may be key in the refinement of patient-specific models. The goal of this study was to investigate the relative contribution of these parameters to the biomechanical and optical responses of human cornea predicted by a widely accepted anisotropic hyperelastic finite element model, with regional variations in the alignment of fibers. Design of experiments methods were used to quantify the relative importance of material properties including matrix stiffness, fiber stiffness, fiber nonlinearity and fiber dispersion under physiological IOP. Our sensitivity results showed that corneal apical displacement was influenced nearly evenly by matrix stiffness, fiber stiffness and nonlinearity. However, the variations in corneal optical aberrations (refractive power and spherical aberration) were primarily dependent on the value of the matrix stiffness. The optical aberrations predicted by variations in this material parameter were sufficiently large to predict clinically important changes in retinal image quality. Therefore, well-characterized individual variations in matrix stiffness could be critical in cornea modeling in order to reliably predict optical behavior under different IOPs or after corneal surgery.
Becker, Roland; Vexler, Boris
2005-06-01
We consider the calibration of parameters in physical models described by partial differential equations. This task is formulated as a constrained optimization problem with a cost functional of least squares type using information obtained from measurements. An important issue in the numerical solution of this type of problem is the control of the errors introduced, first, by discretization of the equations describing the physical model, and second, by measurement errors or other perturbations. Our strategy is as follows: we suppose that the user defines an interest functional I, which might depend on both the state variable and the parameters and which represents the goal of the computation. First, we propose an a posteriori error estimator which measures the error with respect to this functional. This error estimator is used in an adaptive algorithm to construct economic meshes by local mesh refinement. The proposed estimator requires the solution of an auxiliary linear equation. Second, we address the question of sensitivity. Applying similar techniques as before, we derive quantities which describe the influence of small changes in the measurements on the value of the interest functional. These numbers, which we call relative condition numbers, give additional information on the problem under consideration. They can be computed by means of the solution of the auxiliary problem determined before. Finally, we demonstrate our approach at hand of a parameter calibration problem for a model flow problem.
Sensitivity analysis of reactor safety parameters with automated adjoint function generation
International Nuclear Information System (INIS)
Kallfelz, J.M.; Horwedel, J.E.; Worley, B.A.
1992-01-01
A project at the Paul Scherrer Institute (PSI) involves the development of simulation models for the transient analysis of the reactors in Switzerland (STARS). This project, funded in part by the Swiss Federal Nuclear Safety Inspectorate, also involves the calculation and evaluation of certain transients for Swiss light water reactors (LWRs). For best-estimate analyses, a key element in quantifying reactor safety margins is uncertainty evaluation to determine the uncertainty in calculated integral values (responses) caused by modeling, calculational methodology, and input data (parameters). The work reported in this paper is a joint PSI/Oak Ridge National Laboratory (ORNL) application to a core transient analysis code of an ORNL software system for automated sensitivity analysis. The Gradient-Enhanced Software System (GRESS) is a software package that can in principle enhance any code so that it can calculate the sensitivity (derivative) to input parameters of any integral value (response) calculated in the original code. The studies reported are the first application of the GRESS capability to core neutronics and safety codes
Coupled 1D-2D hydrodynamic inundation model for sewer overflow: Influence of modeling parameters
Directory of Open Access Journals (Sweden)
Adeniyi Ganiyu Adeogun
2015-10-01
Full Text Available This paper presents outcome of our investigation on the influence of modeling parameters on 1D-2D hydrodynamic inundation model for sewer overflow, developed through coupling of an existing 1D sewer network model (SWMM and 2D inundation model (BREZO. The 1D-2D hydrodynamic model was developed for the purpose of examining flood incidence due to surcharged water on overland surface. The investigation was carried out by performing sensitivity analysis on the developed model. For the sensitivity analysis, modeling parameters, such as mesh resolution Digital Elevation Model (DEM resolution and roughness were considered. The outcome of the study shows the model is sensitive to changes in these parameters. The performance of the model is significantly influenced, by the Manning's friction value, the DEM resolution and the area of the triangular mesh. Also, changes in the aforementioned modeling parameters influence the Flood characteristics, such as the inundation extent, the flow depth and the velocity across the model domain. Keywords: Inundation, DEM, Sensitivity analysis, Model coupling, Flooding
Analysis of Modeling Parameters on Threaded Screws.
Energy Technology Data Exchange (ETDEWEB)
Vigil, Miquela S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Brake, Matthew Robert [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vangoethem, Douglas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-06-01
Assembled mechanical systems often contain a large number of bolted connections. These bolted connections (joints) are integral aspects of the load path for structural dynamics, and, consequently, are paramount for calculating a structure's stiffness and energy dissipation prop- erties. However, analysts have not found the optimal method to model appropriately these bolted joints. The complexity of the screw geometry cause issues when generating a mesh of the model. This paper will explore different approaches to model a screw-substrate connec- tion. Model parameters such as mesh continuity, node alignment, wedge angles, and thread to body element size ratios are examined. The results of this study will give analysts a better understanding of the influences of these parameters and will aide in finding the optimal method to model bolted connections.
INFERENCE AND SENSITIVITY IN STOCHASTIC WIND POWER FORECAST MODELS.
Elkantassi, Soumaya
2017-10-03
Reliable forecasting of wind power generation is crucial to optimal control of costs in generation of electricity with respect to the electricity demand. Here, we propose and analyze stochastic wind power forecast models described by parametrized stochastic differential equations, which introduce appropriate fluctuations in numerical forecast outputs. We use an approximate maximum likelihood method to infer the model parameters taking into account the time correlated sets of data. Furthermore, we study the validity and sensitivity of the parameters for each model. We applied our models to Uruguayan wind power production as determined by historical data and corresponding numerical forecasts for the period of March 1 to May 31, 2016.
INFERENCE AND SENSITIVITY IN STOCHASTIC WIND POWER FORECAST MODELS.
Elkantassi, Soumaya; Kalligiannaki, Evangelia; Tempone, Raul
2017-01-01
Reliable forecasting of wind power generation is crucial to optimal control of costs in generation of electricity with respect to the electricity demand. Here, we propose and analyze stochastic wind power forecast models described by parametrized stochastic differential equations, which introduce appropriate fluctuations in numerical forecast outputs. We use an approximate maximum likelihood method to infer the model parameters taking into account the time correlated sets of data. Furthermore, we study the validity and sensitivity of the parameters for each model. We applied our models to Uruguayan wind power production as determined by historical data and corresponding numerical forecasts for the period of March 1 to May 31, 2016.
Geramizadeh, Maryam; Katoozian, Hamidreza; Amid, Reza; Kadkhodazadeh, Mahdi
2018-04-01
This study aimed to optimize the thread depth and pitch of a recently designed dental implant to provide uniform stress distribution by means of a response surface optimization method available in finite element (FE) software. The sensitivity of simulation to different mechanical parameters was also evaluated. A three-dimensional model of a tapered dental implant with micro-threads in the upper area and V-shaped threads in the rest of the body was modeled and analyzed using finite element analysis (FEA). An axial load of 100 N was applied to the top of the implants. The model was optimized for thread depth and pitch to determine the optimal stress distribution. In this analysis, micro-threads had 0.25 to 0.3 mm depth and 0.27 to 0.33 mm pitch, and V-shaped threads had 0.405 to 0.495 mm depth and 0.66 to 0.8 mm pitch. The optimized depth and pitch were 0.307 and 0.286 mm for micro-threads and 0.405 and 0.808 mm for V-shaped threads, respectively. In this design, the most effective parameters on stress distribution were the depth and pitch of the micro-threads based on sensitivity analysis results. Based on the results of this study, the optimal implant design has micro-threads with 0.307 and 0.286 mm depth and pitch, respectively, in the upper area and V-shaped threads with 0.405 and 0.808 mm depth and pitch in the rest of the body. These results indicate that micro-thread parameters have a greater effect on stress and strain values.
Parameter Estimation of Spacecraft Fuel Slosh Model
Gangadharan, Sathya; Sudermann, James; Marlowe, Andrea; Njengam Charles
2004-01-01
Fuel slosh in the upper stages of a spinning spacecraft during launch has been a long standing concern for the success of a space mission. Energy loss through the movement of the liquid fuel in the fuel tank affects the gyroscopic stability of the spacecraft and leads to nutation (wobble) which can cause devastating control issues. The rate at which nutation develops (defined by Nutation Time Constant (NTC can be tedious to calculate and largely inaccurate if done during the early stages of spacecraft design. Pure analytical means of predicting the influence of onboard liquids have generally failed. A strong need exists to identify and model the conditions of resonance between nutation motion and liquid modes and to understand the general characteristics of the liquid motion that causes the problem in spinning spacecraft. A 3-D computerized model of the fuel slosh that accounts for any resonant modes found in the experimental testing will allow for increased accuracy in the overall modeling process. Development of a more accurate model of the fuel slosh currently lies in a more generalized 3-D computerized model incorporating masses, springs and dampers. Parameters describing the model include the inertia tensor of the fuel, spring constants, and damper coefficients. Refinement and understanding the effects of these parameters allow for a more accurate simulation of fuel slosh. The current research will focus on developing models of different complexity and estimating the model parameters that will ultimately provide a more realistic prediction of Nutation Time Constant obtained through simulation.
Iterative integral parameter identification of a respiratory mechanics model.
Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey
2012-07-18
Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
Iterative integral parameter identification of a respiratory mechanics model
Directory of Open Access Journals (Sweden)
Schranz Christoph
2012-07-01
Full Text Available Abstract Background Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual’s model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. Methods An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS patients. Results The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. Conclusion These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.
Therapeutic Implications from Sensitivity Analysis of Tumor Angiogenesis Models
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
Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean
Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.
2011-12-01
Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling
Sensitivity analysis on various parameters for lattice analysis of DUPIC fuel with WIMS-AECL code
Energy Technology Data Exchange (ETDEWEB)
Roh, Gyu Hong; Choi, Hang Bok; Park, Jee Won [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)
1997-12-31
The code WIMS-AECL has been used for the lattice analysis of DUPIC fuel. The lattice parameters calculated by the code is sensitive to the choice of number of parameters, such as the number of tracking lines, number of condensed groups, mesh spacing in the moderator region, other parameters vital to the calculation of probabilities and burnup analysis. We have studied this sensitivity with respect to these parameters and recommend their proper values which are necessary for carrying out the lattice analysis of DUPIC fuel.
Sensitivity analysis on various parameters for lattice analysis of DUPIC fuel with WIMS-AECL code
Energy Technology Data Exchange (ETDEWEB)
Roh, Gyu Hong; Choi, Hang Bok; Park, Jee Won [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)
1998-12-31
The code WIMS-AECL has been used for the lattice analysis of DUPIC fuel. The lattice parameters calculated by the code is sensitive to the choice of number of parameters, such as the number of tracking lines, number of condensed groups, mesh spacing in the moderator region, other parameters vital to the calculation of probabilities and burnup analysis. We have studied this sensitivity with respect to these parameters and recommend their proper values which are necessary for carrying out the lattice analysis of DUPIC fuel.
Model comparisons and genetic and environmental parameter ...
African Journals Online (AJOL)
arc
Model comparisons and genetic and environmental parameter estimates of growth and the ... breeding strategies and for accurate breeding value estimation. The objectives ...... Sci. 23, 72-76. Van Wyk, J.B., Fair, M.D. & Cloete, S.W.P., 2003.
The rho-parameter in supersymmetric models
International Nuclear Information System (INIS)
Lim, C.S.; Inami, T.; Sakai, N.
1983-10-01
The electroweak rho-parameter is examined in a general class of supersymmetric models. Formulae are given for one-loop contributions to Δrho from scalar quarks and leptons, gauge-Higgs fermions and an extra doublet of Higgs scalars. Mass differences between members of isodoublet scalar quarks and leptons are constrained to be less than about 200 GeV. (author)
Lumped-parameter fuel rod model for rapid thermal transients
International Nuclear Information System (INIS)
Perkins, K.R.; Ramshaw, J.D.
1975-07-01
The thermal behavior of fuel rods during simulated accident conditions is extremely sensitive to the heat transfer coefficient which is, in turn, very sensitive to the cladding surface temperature and the fluid conditions. The development of a semianalytical, lumped-parameter fuel rod model which is intended to provide accurate calculations, in a minimum amount of computer time, of the thermal response of fuel rods during a simulated loss-of-coolant accident is described. The results show good agreement with calculations from a comprehensive fuel-rod code (FRAP-T) currently in use at Aerojet Nuclear Company
A lumped parameter model of plasma focus
International Nuclear Information System (INIS)
Gonzalez, Jose H.; Florido, Pablo C.; Bruzzone, H.; Clausse, Alejandro
1999-01-01
A lumped parameter model to estimate neutron emission of a plasma focus (PF) device is developed. The dynamic of the current sheet is calculated using a snowplow model, and the neutron production with the thermal fusion cross section for a deuterium filling gas. The results were contrasted as a function of the filling pressure with experimental measurements of a 3.68 KJ Mather-type PF. (author)
One parameter model potential for noble metals
International Nuclear Information System (INIS)
Idrees, M.; Khwaja, F.A.; Razmi, M.S.K.
1981-08-01
A phenomenological one parameter model potential which includes s-d hybridization and core-core exchange contributions is proposed for noble metals. A number of interesting properties like liquid metal resistivities, band gaps, thermoelectric powers and ion-ion interaction potentials are calculated for Cu, Ag and Au. The results obtained are in better agreement with experiment than the ones predicted by the other model potentials in the literature. (author)
How often do sensitivity analyses for economic parameters change cost-utility analysis conclusions?
Schackman, Bruce R; Gold, Heather Taffet; Stone, Patricia W; Neumann, Peter J
2004-01-01
There is limited evidence about the extent to which sensitivity analysis has been used in the cost-effectiveness literature. Sensitivity analyses for health-related QOL (HR-QOL), cost and discount rate economic parameters are of particular interest because they measure the effects of methodological and estimation uncertainties. To investigate the use of sensitivity analyses in the pharmaceutical cost-utility literature in order to test whether a change in economic parameters could result in a different conclusion regarding the cost effectiveness of the intervention analysed. Cost-utility analyses of pharmaceuticals identified in a prior comprehensive audit (70 articles) were reviewed and further audited. For each base case for which sensitivity analyses were reported (n = 122), up to two sensitivity analyses for HR-QOL (n = 133), cost (n = 99), and discount rate (n = 128) were examined. Article mentions of thresholds for acceptable cost-utility ratios were recorded (total 36). Cost-utility ratios were denominated in US dollars for the year reported in each of the original articles in order to determine whether a different conclusion would have been indicated at the time the article was published. Quality ratings from the original audit for articles where sensitivity analysis results crossed the cost-utility ratio threshold above the base-case result were compared with those that did not. The most frequently mentioned cost-utility thresholds were $US20,000/QALY, $US50,000/QALY, and $US100,000/QALY. The proportions of sensitivity analyses reporting quantitative results that crossed the threshold above the base-case results (or where the sensitivity analysis result was dominated) were 31% for HR-QOL sensitivity analyses, 20% for cost-sensitivity analyses, and 15% for discount-rate sensitivity analyses. Almost half of the discount-rate sensitivity analyses did not report quantitative results. Articles that reported sensitivity analyses where results crossed the cost
Calibration of discrete element model parameters: soybeans
Ghodki, Bhupendra M.; Patel, Manish; Namdeo, Rohit; Carpenter, Gopal
2018-05-01
Discrete element method (DEM) simulations are broadly used to get an insight of flow characteristics of granular materials in complex particulate systems. DEM input parameters for a model are the critical prerequisite for an efficient simulation. Thus, the present investigation aims to determine DEM input parameters for Hertz-Mindlin model using soybeans as a granular material. To achieve this aim, widely acceptable calibration approach was used having standard box-type apparatus. Further, qualitative and quantitative findings such as particle profile, height of kernels retaining the acrylic wall, and angle of repose of experiments and numerical simulations were compared to get the parameters. The calibrated set of DEM input parameters includes the following (a) material properties: particle geometric mean diameter (6.24 mm); spherical shape; particle density (1220 kg m^{-3} ), and (b) interaction parameters such as particle-particle: coefficient of restitution (0.17); coefficient of static friction (0.26); coefficient of rolling friction (0.08), and particle-wall: coefficient of restitution (0.35); coefficient of static friction (0.30); coefficient of rolling friction (0.08). The results may adequately be used to simulate particle scale mechanics (grain commingling, flow/motion, forces, etc) of soybeans in post-harvest machinery and devices.
Tonk, E.C.M.; Verhoef, A.; Gremmer, E.R.; van Loveren, H.; Piersma, A.H.
2012-01-01
The developing immune system displays a relatively high sensitivity as compared to both general toxicity parameters and to the adult immune system. In this study we have performed such comparisons using di(2-ethylhexyl) phthalate (DEHP) as a model compound. DEHP is the most abundant phthalate in the
Parameter optimization for surface flux transport models
Whitbread, T.; Yeates, A. R.; Muñoz-Jaramillo, A.; Petrie, G. J. D.
2017-11-01
Accurate prediction of solar activity calls for precise calibration of solar cycle models. Consequently we aim to find optimal parameters for models which describe the physical processes on the solar surface, which in turn act as proxies for what occurs in the interior and provide source terms for coronal models. We use a genetic algorithm to optimize surface flux transport models using National Solar Observatory (NSO) magnetogram data for Solar Cycle 23. This is applied to both a 1D model that inserts new magnetic flux in the form of idealized bipolar magnetic regions, and also to a 2D model that assimilates specific shapes of real active regions. The genetic algorithm searches for parameter sets (meridional flow speed and profile, supergranular diffusivity, initial magnetic field, and radial decay time) that produce the best fit between observed and simulated butterfly diagrams, weighted by a latitude-dependent error structure which reflects uncertainty in observations. Due to the easily adaptable nature of the 2D model, the optimization process is repeated for Cycles 21, 22, and 24 in order to analyse cycle-to-cycle variation of the optimal solution. We find that the ranges and optimal solutions for the various regimes are in reasonable agreement with results from the literature, both theoretical and observational. The optimal meridional flow profiles for each regime are almost entirely within observational bounds determined by magnetic feature tracking, with the 2D model being able to accommodate the mean observed profile more successfully. Differences between models appear to be important in deciding values for the diffusive and decay terms. In like fashion, differences in the behaviours of different solar cycles lead to contrasts in parameters defining the meridional flow and initial field strength.
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
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 of the optimal parameter settings for a LTE packet scheduler
Fernandez-Diaz, I.; Litjens, R.; van den Berg, C.A.; Dimitrova, D.C.; Spaey, K.
Advanced packet scheduling schemes in 3G/3G+ mobile networks provide one or more parameters to optimise the trade-off between QoS and resource efficiency. In this paper we study the sensitivity of the optimal parameter setting for packet scheduling in LTE radio networks with respect to various
Sensitivity Analysis of Unsaturated Flow and Contaminant Transport with Correlated Parameters
Relative contributions from uncertainties in input parameters to the predictive uncertainties in unsaturated flow and contaminant transport are investigated in this study. The objectives are to: (1) examine the effects of input parameter correlations on the sensitivity of unsaturated flow and conta...
Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model
Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.
2012-12-01
Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root
Futamure, Sumire; Bonnet, Vincent; Dumas, Raphael; Venture, Gentiane
2017-11-07
This paper presents a method allowing a simple and efficient sensitivity analysis of dynamics parameters of complex whole-body human model. The proposed method is based on the ground reaction and joint moment regressor matrices, developed initially in robotics system identification theory, and involved in the equations of motion of the human body. The regressor matrices are linear relatively to the segment inertial parameters allowing us to use simple sensitivity analysis methods. The sensitivity analysis method was applied over gait dynamics and kinematics data of nine subjects and with a 15 segments 3D model of the locomotor apparatus. According to the proposed sensitivity indices, 76 segments inertial parameters out the 150 of the mechanical model were considered as not influent for gait. The main findings were that the segment masses were influent and that, at the exception of the trunk, moment of inertia were not influent for the computation of the ground reaction forces and moments and the joint moments. The same method also shows numerically that at least 90% of the lower-limb joint moments during the stance phase can be estimated only from a force-plate and kinematics data without knowing any of the segment inertial parameters. Copyright © 2017 Elsevier Ltd. All rights reserved.
Sun, Y.; Hou, Z.; Huang, M.; Tian, F.; Leung, L. Ruby
2013-12-01
This study demonstrates the possibility of inverting hydrologic parameters using surface flux and runoff observations in version 4 of the Community Land Model (CLM4). Previous studies showed that surface flux and runoff calculations are sensitive to major hydrologic parameters in CLM4 over different watersheds, and illustrated the necessity and possibility of parameter calibration. Both deterministic least-square fitting and stochastic Markov-chain Monte Carlo (MCMC)-Bayesian inversion approaches are evaluated by applying them to CLM4 at selected sites with different climate and soil conditions. The unknowns to be estimated include surface and subsurface runoff generation parameters and vadose zone soil water parameters. We find that using model parameters calibrated by the sampling-based stochastic inversion approaches provides significant improvements in the model simulations compared to using default CLM4 parameter values, and that as more information comes in, the predictive intervals (ranges of posterior distributions) of the calibrated parameters become narrower. In general, parameters that are identified to be significant through sensitivity analyses and statistical tests are better calibrated than those with weak or nonlinear impacts on flux or runoff observations. Temporal resolution of observations has larger impacts on the results of inverse modeling using heat flux data than runoff data. Soil and vegetation cover have important impacts on parameter sensitivities, leading to different patterns of posterior distributions of parameters at different sites. Overall, the MCMC-Bayesian inversion approach effectively and reliably improves the simulation of CLM under different climates and environmental conditions. Bayesian model averaging of the posterior estimates with different reference acceptance probabilities can smooth the posterior distribution and provide more reliable parameter estimates, but at the expense of wider uncertainty bounds.
Anderson, B. J.; Gaddipati, M.; Nyayapathi, L.
2008-12-01
This paper presents a parametric study on production rates of natural gas from gas hydrates by the method of depressurization, using CMG STARS. Seven factors/parameters were considered as perturbations from a base-case hydrate reservoir description based on Problem 7 of the International Methane Hydrate Reservoir Simulator Code Comparison Study led by the Department of Energy and the USGS. This reservoir is modeled after the inferred properties of the hydrate deposit at the Prudhoe Bay L-106 site. The included sensitivity variables were hydrate saturation, pressure (depth), temperature, bottom-hole pressure of the production well, free water saturation, intrinsic rock permeability, and porosity. A two-level (L=2) Plackett-Burman experimental design was used to study the relative effects of these factors. The measured variable was the discounted cumulative gas production. The discount rate chosen was 15%, resulting in the gas contribution to the net present value of a reservoir. Eight different designs were developed for conducting sensitivity analysis and the effects of the parameters on the real and discounted production rates will be discussed. The breakeven price in various cases and the dependence of the breakeven price on the production parameters is given in the paper. As expected, initial reservoir temperature has the strongest positive effect on the productivity of a hydrate deposit and the bottom-hole pressure in the production well has the strongest negative dependence. Also resulting in a positive correlation is the intrinsic permeability and the initial free water of the formation. Negative effects were found for initial hydrate saturation (at saturations greater than 50% of the pore space) and the reservoir porosity. These negative effects are related to the available sensible heat of the reservoir, with decreasing productivity due to decreasing available sensible heat. Finally, we conclude that for the base case reservoir, the break-even price (BEP
Constant-parameter capture-recapture models
Brownie, C.; Hines, J.E.; Nichols, J.D.
1986-01-01
Jolly (1982, Biometrics 38, 301-321) presented modifications of the Jolly-Seber model for capture-recapture data, which assume constant survival and/or capture rates. Where appropriate, because of the reduced number of parameters, these models lead to more efficient estimators than the Jolly-Seber model. The tests to compare models given by Jolly do not make complete use of the data, and we present here the appropriate modifications, and also indicate how to carry out goodness-of-fit tests which utilize individual capture history information. We also describe analogous models for the case where young and adult animals are tagged. The availability of computer programs to perform the analysis is noted, and examples are given using output from these programs.
Sensitivity analysis of Smith's AMRV model
International Nuclear Information System (INIS)
Ho, Chih-Hsiang
1995-01-01
Multiple-expert hazard/risk assessments have considerable precedent, particularly in the Yucca Mountain site characterization studies. In this paper, we present a Bayesian approach to statistical modeling in volcanic hazard assessment for the Yucca Mountain site. Specifically, we show that the expert opinion on the site disruption parameter p is elicited on the prior distribution, π (p), based on geological information that is available. Moreover, π (p) can combine all available geological information motivated by conflicting but realistic arguments (e.g., simulation, cluster analysis, structural control, etc.). The incorporated uncertainties about the probability of repository disruption p, win eventually be averaged out by taking the expectation over π (p). We use the following priors in the analysis: priors chosen for mathematical convenience: Beta (r, s) for (r, s) = (2, 2), (3, 3), (5, 5), (2, 1), (2, 8), (8, 2), and (1, 1); and three priors motivated by expert knowledge. Sensitivity analysis is performed for each prior distribution. Estimated values of hazard based on the priors chosen for mathematical simplicity are uniformly higher than those obtained based on the priors motivated by expert knowledge. And, the model using the prior, Beta (8,2), yields the highest hazard (= 2.97 X 10 -2 ). The minimum hazard is produced by the open-quotes three-expert priorclose quotes (i.e., values of p are equally likely at 10 -3 10 -2 , and 10 -1 ). The estimate of the hazard is 1.39 x which is only about one order of magnitude smaller than the maximum value. The term, open-quotes hazardclose quotes, is defined as the probability of at least one disruption of a repository at the Yucca Mountain site by basaltic volcanism for the next 10,000 years
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.)
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
Sensitivity of storage field performance to geologic and cavern design parameters in salt domes.
Energy Technology Data Exchange (ETDEWEB)
Ehgartner, Brian L. (Sandia National Laboratories, Albuquerque, NM); Park, Byoung Yoon
2009-03-01
A sensitivity study was performed utilizing a three dimensional finite element model to assess allowable cavern field sizes for strategic petroleum reserve salt domes. A potential exists for tensile fracturing and dilatancy damage to salt that can compromise the integrity of a cavern field in situations where high extraction ratios exist. The effects of salt creep rate, depth of salt dome top, dome size, caprock thickness, elastic moduli of caprock and surrounding rock, lateral stress ratio of surrounding rock, cavern size, depth of cavern, and number of caverns are examined numerically. As a result, a correlation table between the parameters and the impact on the performance of storage field was established. In general, slower salt creep rates, deeper depth of salt dome top, larger elastic moduli of caprock and surrounding rock, and a smaller radius of cavern are better for structural performance of the salt dome.
Analytic uncertainty and sensitivity analysis of models with input correlations
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.
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)
Assessment of Wind Parameter Sensitivity on Extreme and Fatigue Wind Turbine Loads
Energy Technology Data Exchange (ETDEWEB)
Robertson, Amy N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sethuraman, Latha [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jonkman, Jason [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2018-01-12
Wind turbines are designed using a set of simulations to ascertain the structural loads that the turbine could encounter. While mean hub-height wind speed is considered to vary, other wind parameters such as turbulence spectra, sheer, veer, spatial coherence, and component correlation are fixed or conditional values that, in reality, could have different characteristics at different sites and have a significant effect on the resulting loads. This paper therefore seeks to assess the sensitivity of different wind parameters on the resulting ultimate and fatigue loads on the turbine during normal operational conditions. Eighteen different wind parameters are screened using an Elementary Effects approach with radial points. As expected, the results show a high sensitivity of the loads to the turbulence standard deviation in the primary wind direction, but the sensitivity to wind shear is often much greater. To a lesser extent, other wind parameters that drive loads include the coherence in the primary wind direction and veer.
Assessment of Wind Parameter Sensitivity on Ultimate and Fatigue Wind Turbine Loads: Preprint
Energy Technology Data Exchange (ETDEWEB)
Robertson, Amy N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sethuraman, Latha [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Jonkman, Jason [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2018-02-13
Wind turbines are designed using a set of simulations to ascertain the structural loads that the turbine could encounter. While mean hub-height wind speed is considered to vary, other wind parameters such as turbulence spectra, sheer, veer, spatial coherence, and component correlation are fixed or conditional values that, in reality, could have different characteristics at different sites and have a significant effect on the resulting loads. This paper therefore seeks to assess the sensitivity of different wind parameters on the resulting ultimate and fatigue loads on the turbine during normal operational conditions. Eighteen different wind parameters are screened using an Elementary Effects approach with radial points. As expected, the results show a high sensitivity of the loads to the turbulence standard deviation in the primary wind direction, but the sensitivity to wind shear is often much greater. To a lesser extent, other wind parameters that drive loads include the coherence in the primary wind direction and veer.
Modelling tourists arrival using time varying parameter
Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.
2017-06-01
The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.
Sensitivity analysis of the terrestrial food chain model FOOD III
International Nuclear Information System (INIS)
Zach, Reto.
1980-10-01
As a first step in constructing a terrestrial food chain model suitable for long-term waste management situations, a numerical sensitivity analysis of FOOD III was carried out to identify important model parameters. The analysis involved 42 radionuclides, four pathways, 14 food types, 93 parameters and three percentages of parameter variation. We also investigated the importance of radionuclides, pathways and food types. The analysis involved a simple contamination model to render results from individual pathways comparable. The analysis showed that radionuclides vary greatly in their dose contribution to each of the four pathways, but relative contributions to each pathway are very similar. Man's and animals' drinking water pathways are much more important than the leaf and root pathways. However, this result depends on the contamination model used. All the pathways contain unimportant food types. Considering the number of parameters involved, FOOD III has too many different food types. Many of the parameters of the leaf and root pathway are important. However, this is true for only a few of the parameters of animals' drinking water pathway, and for neither of the two parameters of mans' drinking water pathway. The radiological decay constant increases the variability of these results. The dose factor is consistently the most important variable, and it explains most of the variability of radionuclide doses within pathways. Consideration of the variability of dose factors is important in contemporary as well as long-term waste management assessment models, if realistic estimates are to be made. (auth)
Directory of Open Access Journals (Sweden)
Lubomir Ivanek
2017-01-01
Full Text Available This paper deals with the sensitivity of the input impedance of an open track circuit in the event that the parameters of the track are changed. Weather conditions and the state of pollution are the most common reasons for parameter changes. The results were obtained from the measured values of the parameters R (resistance, G (conductance, L (inductance, and C (capacitance of a rail superstructure depending on the frequency. Measurements were performed on a railway siding in Orlova. The results are used to design a predictor of occupancy of a track section. In particular, we were interested in the frequencies of 75 and 275 Hz for this purpose. Many parameter values of track substructures have already been solved in different works in literature. At first, we had planned to use the parameter values from these sources when we designed the predictor. Deviations between them, however, are large and often differ by three orders of magnitude (see Tab.8. From this perspective, this article presents data that have been updated using modern measurement devices and computer technology. And above all, it shows a transmission (cascade matrix used to determine the parameters.
Maina, Fadji Zaouna; Guadagnini, Alberto
2018-01-01
We study the contribution of typically uncertain subsurface flow parameters to gravity changes that can be recorded during pumping tests in unconfined aquifers. We do so in the framework of a Global Sensitivity Analysis and quantify the effects of uncertainty of such parameters on the first four statistical moments of the probability distribution of gravimetric variations induced by the operation of the well. System parameters are grouped into two main categories, respectively, governing groundwater flow in the unsaturated and saturated portions of the domain. We ground our work on the three-dimensional analytical model proposed by Mishra and Neuman (2011), which fully takes into account the richness of the physical process taking place across the unsaturated and saturated zones and storage effects in a finite radius pumping well. The relative influence of model parameter uncertainties on drawdown, moisture content, and gravity changes are quantified through (a) the Sobol' indices, derived from a classical decomposition of variance and (b) recently developed indices quantifying the relative contribution of each uncertain model parameter to the (ensemble) mean, skewness, and kurtosis of the model output. Our results document (i) the importance of the effects of the parameters governing the unsaturated flow dynamics on the mean and variance of local drawdown and gravity changes; (ii) the marked sensitivity (as expressed in terms of the statistical moments analyzed) of gravity changes to the employed water retention curve model parameter, specific yield, and storage, and (iii) the influential role of hydraulic conductivity of the unsaturated and saturated zones to the skewness and kurtosis of gravimetric variation distributions. The observed temporal dynamics of the strength of the relative contribution of system parameters to gravimetric variations suggest that gravity data have a clear potential to provide useful information for estimating the key hydraulic
Are LOD and LOQ Reliable Parameters for Sensitivity Evaluation of Spectroscopic Methods?
Ershadi, Saba; Shayanfar, Ali
2018-03-22
The limit of detection (LOD) and the limit of quantification (LOQ) are common parameters to assess the sensitivity of analytical methods. In this study, the LOD and LOQ of previously reported terbium sensitized analysis methods were calculated by different methods, and the results were compared with sensitivity parameters [lower limit of quantification (LLOQ)] of U.S. Food and Drug Administration guidelines. The details of the calibration curve and standard deviation of blank samples of three different terbium-sensitized luminescence methods for the quantification of mycophenolic acid, enrofloxacin, and silibinin were used for the calculation of LOD and LOQ. A comparison of LOD and LOQ values calculated by various methods and LLOQ shows a considerable difference. The significant difference of the calculated LOD and LOQ with various methods and LLOQ should be considered in the sensitivity evaluation of spectroscopic methods.
On the effect of model parameters on forecast objects
Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott
2018-04-01
Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.
Influential input parameters for reflood model of MARS code
Energy Technology Data Exchange (ETDEWEB)
Oh, Deog Yeon; Bang, Young Seok [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)
2012-10-15
Best Estimate (BE) calculation has been more broadly used in nuclear industries and regulations to reduce the significant conservatism for evaluating Loss of Coolant Accident (LOCA). Reflood model has been identified as one of the problems in BE calculation. The objective of the Post BEMUSE Reflood Model Input Uncertainty Methods (PREMIUM) program of OECD/NEA is to make progress the issue of the quantification of the uncertainty of the physical models in system thermal hydraulic codes, by considering an experimental result especially for reflood. It is important to establish a methodology to identify and select the parameters influential to the response of reflood phenomena following Large Break LOCA. For this aspect, a reference calculation and sensitivity analysis to select the dominant influential parameters for FEBA experiment are performed.
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
Application of parameters space analysis tools for empirical model validation
Energy Technology Data Exchange (ETDEWEB)
Paloma del Barrio, E. [LEPT-ENSAM UMR 8508, Talence (France); Guyon, G. [Electricite de France, Moret-sur-Loing (France)
2004-01-01
A new methodology for empirical model validation has been proposed in the framework of the Task 22 (Building Energy Analysis Tools) of the International Energy Agency. It involves two main steps: checking model validity and diagnosis. Both steps, as well as the underlying methods, have been presented in the first part of the paper. In this part, they are applied for testing modelling hypothesis in the framework of the thermal analysis of an actual building. Sensitivity analysis tools have been first used to identify the parts of the model that can be really tested on the available data. A preliminary diagnosis is then supplied by principal components analysis. Useful information for model behaviour improvement has been finally obtained by optimisation techniques. This example of application shows how model parameters space analysis is a powerful tool for empirical validation. In particular, diagnosis possibilities are largely increased in comparison with residuals analysis techniques. (author)
Directory of Open Access Journals (Sweden)
Anne Schützenberger
2016-01-01
Full Text Available The current use of laryngeal high-speed videoendoscopy in clinic settings involves subjective visual assessment of vocal fold vibratory characteristics. However, objective quantification of vocal fold vibrations for evidence-based diagnosis and therapy is desired, and objective parameters assessing laryngeal dynamics have therefore been suggested. This study investigated the sensitivity of the objective parameters and their dependence on recording frame rate. A total of 300 endoscopic high-speed videos with recording frame rates between 1000 and 15 000 fps were analyzed for a vocally healthy female subject during sustained phonation. Twenty parameters, representing laryngeal dynamics, were computed. Four different parameter characteristics were found: parameters showing no change with increasing frame rate; parameters changing up to a certain frame rate, but then remaining constant; parameters remaining constant within a particular range of recording frame rates; and parameters changing with nearly every frame rate. The results suggest that (1 parameter values are influenced by recording frame rates and different parameters have varying sensitivities to recording frame rate; (2 normative values should be determined based on recording frame rates; and (3 the typically used recording frame rate of 4000 fps seems to be too low to distinguish accurately certain characteristics of the human phonation process in detail.
Pant, Sanjay
2018-05-01
A new class of functions, called the 'information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Bayesian and information-theoretic approaches. While marginal information gain is quantified by decrease in differential entropy, correlations between arbitrary sets of parameters are assessed through mutual information. For individual parameters, these information gains are also presented as marginal posterior variances, and, to assess the effect of correlations, as conditional variances when other parameters are given. The easy to interpret ISFs can be used to (a) identify time intervals or regions in dynamical system behaviour where information about the parameters is concentrated; (b) assess the effect of measurement noise on the information gain for the parameters; (c) assess whether sufficient information in an experimental protocol (input, measurements and their frequency) is available to identify the parameters; (d) assess correlation in the posterior distribution of the parameters to identify the sets of parameters that are likely to be indistinguishable; and (e) assess identifiability problems for particular sets of parameters. © 2018 The Authors.
A sensitivity analysis of regional and small watershed hydrologic models
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.
Sensitivities and uncertainties of modeled ground temperatures in mountain environments
Directory of Open Access Journals (Sweden)
S. Gubler
2013-08-01
discretization parameters. We show that the temporal resolution should be at least 1 h to ensure errors less than 0.2 °C in modeled MAGT, and the uppermost ground layer should at most be 20 mm thick. Within the topographic setting, the total parametric output uncertainties expressed as the length of the 95% uncertainty interval of the Monte Carlo simulations range from 0.5 to 1.5 °C for clay and silt, and ranges from 0.5 to around 2.4 °C for peat, sand, gravel and rock. These uncertainties are comparable to the variability of ground surface temperatures measured within 10 m × 10 m grids in Switzerland. The increased uncertainties for sand, peat and gravel are largely due to their sensitivity to the hydraulic conductivity.
The lumped parameter model for fuel pins
Energy Technology Data Exchange (ETDEWEB)
Liu, W S [Ontario Hydro, Toronto, ON (Canada)
1996-12-31
The use of a lumped fuel-pin model in a thermal-hydraulic code is advantageous because of computational simplicity and efficiency. The model uses an averaging approach over the fuel cross section and makes some simplifying assumptions to describe the transient equations for the averaged fuel, fuel centerline and sheath temperatures. It is shown that by introducing a factor in the effective fuel conductivity, the analytical solution of the mean fuel temperature can be modified to simulate the effects of the flux depression in the heat generation rate and the variation in fuel thermal conductivity. The simplified analytical method used in the transient equation is presented. The accuracy of the lumped parameter model has been compared with the results from the finite difference method. (author). 4 refs., 2 tabs., 4 figs.
Pouget, J; Trefouret, S; Attarian, S
2000-06-01
Owing to the low sensitivity of clinical signs in assessing upper motor neuron (UMN) involvement in ALS, there is a need for investigative tools capable of detecting abnormal function of the pyramidal tract. Transcranial magnetic stimulation (TMS) may contribute to the diagnosis by reflecting a UMN dysfunction that is not clinically detectable. Several parameters for the motor responses to TMS can be evaluated with different levels of significance in healthy subjects compared with ALS patients. The central motor conduction time, however, is not sensitive in detecting subclinical UMN defects in individual ALS patients. The amplitude of the motor evoked potential (MEP), expressed as the percentage of the maximum wave, also has a low sensitivity. In some cases, the corticomotor threshold is decreased early in the disease course as a result of corticomotor neuron hyperexcitability induced by glutamate. Later, the threshold increases, indicating a loss of UMN. In our experience, a decreased silent period duration appears to be the most sensitive parameter when using motor TMS in ALS. TMS is also a sensitive technique for investigating the corticobulbar tract, which is difficult to study by other methods. TMS is a widely available, painless and safe technique with a good sensitivity that can visualize both corticospinal and corticobulbar tract abnormalities. The sensitivity can be improved further by taking into account the several MEP parameters, including latency and cortical silent period decreased duration.
International Nuclear Information System (INIS)
Wang, Pan; Lu, Zhenzhou; Ren, Bo; Cheng, Lei
2013-01-01
The output variance is an important measure for the performance of a structural system, and it is always influenced by the distribution parameters of inputs. In order to identify the influential distribution parameters and make it clear that how those distribution parameters influence the output variance, this work presents the derivative based variance sensitivity decomposition according to Sobol′s variance decomposition, and proposes the derivative based main and total sensitivity indices. By transforming the derivatives of various orders variance contributions into the form of expectation via kernel function, the proposed main and total sensitivity indices can be seen as the “by-product” of Sobol′s variance based sensitivity analysis without any additional output evaluation. Since Sobol′s variance based sensitivity indices have been computed efficiently by the sparse grid integration method, this work also employs the sparse grid integration method to compute the derivative based main and total sensitivity indices. Several examples are used to demonstrate the rationality of the proposed sensitivity indices and the accuracy of the applied method
Heat and Mass Transfer of Vacuum Cooling for Porous Foods-Parameter Sensitivity Analysis
Directory of Open Access Journals (Sweden)
Zhijun Zhang
2014-01-01
Full Text Available Based on the theory of heat and mass transfer, a coupled model for the porous food vacuum cooling process is constructed. Sensitivity analyses of the process to food density, thermal conductivity, specific heat, latent heat of evaporation, diameter of pores, mass transfer coefficient, viscosity of gas, and porosity were examined. The simulation results show that the food density would affect the vacuum cooling process but not the vacuum cooling end temperature. The surface temperature of food was slightly affected and the core temperature is not affected by the changed thermal conductivity. The core temperature and surface temperature are affected by the changed specific heat. The core temperature and surface temperature are affected by the changed latent heat of evaporation. The core temperature is affected by the diameter of pores. But the surface temperature is not affected obviously. The core temperature and surface temperature are not affected by the changed gas viscosity. The parameter sensitivity of mass transfer coefficient is obvious. The core temperature and surface temperature are affected by the changed mass transfer coefficient. In all the simulations, the end temperature of core and surface is not affected. The vacuum cooling process of porous medium is a process controlled by outside process.
Energy Technology Data Exchange (ETDEWEB)
Rottlaender, Iris
2008-08-15
An evaluation of the discovery potential for NMSSM Higgs bosons of the ATLAS experiment at the LHC is presented. For this purpose, seven two-dimensional benchmark planes in the six-dimensional parameter space of the NMSSM Higgs sector are defined. These planes include different types of phenomenology for which the discovery of NMSSM Higgs bosons is especially challenging and which are considered typical for the NMSSM. They are subsequently used to give a detailed evaluation of the Higgs boson discovery potential based on Monte Carlo studies from the ATLAS collaboration. Afterwards, the possibility of discovering NMSSM Higgs bosons via the H{sub 1}{yields}A{sub 1}A{sub 1}{yields}4{tau}{yields}4{mu}+8{nu} decay chain and with the vector boson fusion production mode is investigated. A particular emphasis is put on the mass reconstruction from the complex final state. Furthermore, a study of the jet reconstruction performance at the ATLAS experiment which is of crucial relevance for vector boson fusion searches is presented. A good detectability of the so-called tagging jets that originate from the scattered partons in the vector boson fusion process is of critical importance for an early Higgs boson discovery in many models and also within the framework of the NMSSM. (orig.)
Global parameter estimation for thermodynamic models of transcriptional regulation.
Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M; Sinha, Saurabh; Arnosti, David N
2013-07-15
Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. Copyright © 2013 Elsevier Inc. All rights reserved.
Modeling of Parameters of Subcritical Assembly SAD
Petrochenkov, S; Puzynin, I
2005-01-01
The accepted conceptual design of the experimental Subcritical Assembly in Dubna (SAD) is based on the MOX core with a nominal unit capacity of 25 kW (thermal). This corresponds to the multiplication coefficient $k_{\\rm eff} =0.95$ and accelerator beam power 1 kW. A subcritical assembly driven with the existing 660 MeV proton accelerator at the Joint Institute for Nuclear Research has been modelled in order to make choice of the optimal parameters for the future experiments. The Monte Carlo method was used to simulate neutron spectra, energy deposition and doses calculations. Some of the calculation results are presented in the paper.
Parameter estimation in fractional diffusion models
Kubilius, Kęstutis; Ralchenko, Kostiantyn
2017-01-01
This book is devoted to parameter estimation in diffusion models involving fractional Brownian motion and related processes. For many years now, standard Brownian motion has been (and still remains) a popular model of randomness used to investigate processes in the natural sciences, financial markets, and the economy. The substantial limitation in the use of stochastic diffusion models with Brownian motion is due to the fact that the motion has independent increments, and, therefore, the random noise it generates is “white,” i.e., uncorrelated. However, many processes in the natural sciences, computer networks and financial markets have long-term or short-term dependences, i.e., the correlations of random noise in these processes are non-zero, and slowly or rapidly decrease with time. In particular, models of financial markets demonstrate various kinds of memory and usually this memory is modeled by fractional Brownian diffusion. Therefore, the book constructs diffusion models with memory and provides s...
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
Directory of Open Access Journals (Sweden)
B. Asgari
2013-01-01
Full Text Available The model tuning through sensitivity analysis is a prominent procedure to assess the structural behavior and dynamic characteristics of cable-stayed bridges. Most of the previous sensitivity-based model tuning methods are automatic iterative processes; however, the results of recent studies show that the most reasonable results are achievable by applying the manual methods to update the analytical model of cable-stayed bridges. This paper presents a model updating algorithm for highly redundant cable-stayed bridges that can be used as an iterative manual procedure. The updating parameters are selected through the sensitivity analysis which helps to better understand the structural behavior of the bridge. The finite element model of Tatara Bridge is considered for the numerical studies. The results of the simulations indicate the efficiency and applicability of the presented manual tuning method for updating the finite element model of cable-stayed bridges. The new aspects regarding effective material and structural parameters and model tuning procedure presented in this paper will be useful for analyzing and model updating of cable-stayed bridges.
Piezoresistive Cantilever Performance-Part I: Analytical Model for Sensitivity.
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
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
Reliability-based sensitivity of mechanical components with arbitrary distribution parameters
International Nuclear Information System (INIS)
Zhang, Yi Min; Yang, Zhou; Wen, Bang Chun; He, Xiang Dong; Liu, Qiaoling
2010-01-01
This paper presents a reliability-based sensitivity method for mechanical components with arbitrary distribution parameters. Techniques from the perturbation method, the Edgeworth series, the reliability-based design theory, and the sensitivity analysis approach were employed directly to calculate the reliability-based sensitivity of mechanical components on the condition that the first four moments of the original random variables are known. The reliability-based sensitivity information of the mechanical components can be accurately and quickly obtained using a practical computer program. The effects of the design parameters on the reliability of mechanical components were studied. The method presented in this paper provides the theoretic basis for the reliability-based design of mechanical components
Tracer SWIW tests in propped and un-propped fractures: parameter sensitivity issues, revisited
Ghergut, Julia; Behrens, Horst; Sauter, Martin
2017-04-01
Single-well injection-withdrawal (SWIW) or 'push-then-pull' tracer methods appear attractive for a number of reasons: less uncertainty on design and dimensioning, and lower tracer quantities required than for inter-well tests; stronger tracer signals, enabling easier and cheaper metering, and shorter metering duration required, reaching higher tracer mass recovery than in inter-well tests; last not least: no need for a second well. However, SWIW tracer signal inversion faces a major issue: the 'push-then-pull' design weakens the correlation between tracer residence times and georeservoir transport parameters, inducing insensitivity or ambiguity of tracer signal inversion w. r. to some of those georeservoir parameters that are supposed to be the target of tracer tests par excellence: pore velocity, transport-effective porosity, fracture or fissure aperture and spacing or density (where applicable), fluid/solid or fluid/fluid phase interface density. Hydraulic methods cannot measure the transport-effective values of such parameters, because pressure signals correlate neither with fluid motion, nor with material fluxes through (fluid-rock, or fluid-fluid) phase interfaces. The notorious ambiguity impeding parameter inversion from SWIW test signals has nourished several 'modeling attitudes': (i) regard dispersion as the key process encompassing whatever superposition of underlying transport phenomena, and seek a statistical description of flow-path collectives enabling to characterize dispersion independently of any other transport parameter, as proposed by Gouze et al. (2008), with Hansen et al. (2016) offering a comprehensive analysis of the various ways dispersion model assumptions interfere with parameter inversion from SWIW tests; (ii) regard diffusion as the key process, and seek for a large-time, asymptotically advection-independent regime in the measured tracer signals (Haggerty et al. 2001), enabling a dispersion-independent characterization of multiple
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.
Applicability of genetic algorithms to parameter estimation of economic models
Directory of Open Access Journals (Sweden)
Marcel Ševela
2004-01-01
Full Text Available The paper concentrates on capability of genetic algorithms for parameter estimation of non-linear economic models. In the paper we test the ability of genetic algorithms to estimate of parameters of demand function for durable goods and simultaneously search for parameters of genetic algorithm that lead to maximum effectiveness of the computation algorithm. The genetic algorithms connect deterministic iterative computation methods with stochastic methods. In the genteic aůgorithm approach each possible solution is represented by one individual, those life and lifes of all generations of individuals run under a few parameter of genetic algorithm. Our simulations resulted in optimal mutation rate of 15% of all bits in chromosomes, optimal elitism rate 20%. We can not set the optimal extend of generation, because it proves positive correlation with effectiveness of genetic algorithm in all range under research, but its impact is degreasing. The used genetic algorithm was sensitive to mutation rate at most, than to extend of generation. The sensitivity to elitism rate is not so strong.
Duchêne, Gaëtan; Peeters, Frank; Peeters, André; Duprez, Thierry
2017-08-01
To compare the sensitivity and early temporal changes of diffusion parameters obtained from diffusion tensor imaging (DTI), diffusional kurtosis imaging (DKI), q-space analysis (QSA) and bi-exponential modelling in hyperacute stroke patients. A single investigational acquisition allowing the four diffusion analyses was performed on seven hyperacute stroke patients with a 3T system. The percentage change between ipsi- and contralateral regions were compared at admission and 24 h later. Two out of the seven patients were imaged every 6 h during this period. Kurtoses from both DKI and QSA were the most sensitive of the tested diffusion parameters in the few hours following ischemia. An early increase-maximum-decrease pattern of evolution was highlighted during the 24-h period for all parameters proportional to diffusion coefficients. A similar pattern was observed for both kurtoses in only one of two patients. Our comparison was performed using identical diffusion encoding timings and on patients in the same stage of their condition. Although preliminary, our findings confirm those of previous studies that showed enhanced sensitivity of kurtosis. A fine time mapping of diffusion metrics in hyperacute stroke patients was presented which advocates for further investigations on larger animal or human cohorts.
Badawy, B.; Fletcher, C. G.
2017-12-01
The parameterization of snow processes in land surface models is an important source of uncertainty in climate simulations. Quantifying the importance of snow-related parameters, and their uncertainties, may therefore lead to better understanding and quantification of uncertainty within integrated earth system models. However, quantifying the uncertainty arising from parameterized snow processes is challenging due to the high-dimensional parameter space, poor observational constraints, and parameter interaction. In this study, we investigate the sensitivity of the land simulation to uncertainty in snow microphysical parameters in the Canadian LAnd Surface Scheme (CLASS) using an uncertainty quantification (UQ) approach. A set of training cases (n=400) from CLASS is used to sample each parameter across its full range of empirical uncertainty, as determined from available observations and expert elicitation. A statistical learning model using support vector regression (SVR) is then constructed from the training data (CLASS output variables) to efficiently emulate the dynamical CLASS simulations over a much larger (n=220) set of cases. This approach is used to constrain the plausible range for each parameter using a skill score, and to identify the parameters with largest influence on the land simulation in CLASS at global and regional scales, using a random forest (RF) permutation importance algorithm. Preliminary sensitivity tests indicate that snow albedo refreshment threshold and the limiting snow depth, below which bare patches begin to appear, have the highest impact on snow output variables. The results also show a considerable reduction of the plausible ranges of the parameters values and hence reducing their uncertainty ranges, which can lead to a significant reduction of the model uncertainty. The implementation and results of this study will be presented and discussed in details.
Moose models with vanishing S parameter
International Nuclear Information System (INIS)
Casalbuoni, R.; De Curtis, S.; Dominici, D.
2004-01-01
In the linear moose framework, which naturally emerges in deconstruction models, we show that there is a unique solution for the vanishing of the S parameter at the lowest order in the weak interactions. We consider an effective gauge theory based on K SU(2) gauge groups, K+1 chiral fields, and electroweak groups SU(2) L and U(1) Y at the ends of the chain of the moose. S vanishes when a link in the moose chain is cut. As a consequence one has to introduce a dynamical nonlocal field connecting the two ends of the moose. Then the model acquires an additional custodial symmetry which protects this result. We examine also the possibility of a strong suppression of S through an exponential behavior of the link couplings as suggested by the Randall Sundrum metric
Stimulus Sensitivity of a Spiking Neural Network Model
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.
Leal-Junior, Arnaldo G.; Frizera, Anselmo; José Pontes, Maria
2018-03-01
Polymer optical fibers (POFs) are suitable for applications such as curvature sensors, strain, temperature, liquid level, among others. However, for enhancing sensitivity, many polymer optical fiber curvature sensors based on intensity variation require a lateral section. Lateral section length, depth, and surface roughness have great influence on the sensor sensitivity, hysteresis, and linearity. Moreover, the sensor curvature radius increase the stress on the fiber, which leads on variation of the sensor behavior. This paper presents the analysis relating the curvature radius and lateral section length, depth and surface roughness with the sensor sensitivity, hysteresis and linearity for a POF curvature sensor. Results show a strong correlation between the decision parameters behavior and the performance for sensor applications based on intensity variation. Furthermore, there is a trade-off among the sensitive zone length, depth, surface roughness, and curvature radius with the sensor desired performance parameters, which are minimum hysteresis, maximum sensitivity, and maximum linearity. The optimization of these parameters is applied to obtain a sensor with sensitivity of 20.9 mV/°, linearity of 0.9992 and hysteresis below 1%, which represent a better performance of the sensor when compared with the sensor without the optimization.
Relative sensitivity analysis of the predictive properties of sloppy models.
Myasnikova, Ekaterina; Spirov, Alexander
2018-01-25
Commonly among the model parameters characterizing complex biological systems are those that do not significantly influence the quality of the fit to experimental data, so-called "sloppy" parameters. The sloppiness can be mathematically expressed through saturating response functions (Hill's, sigmoid) thereby embodying biological mechanisms responsible for the system robustness to external perturbations. However, if a sloppy model is used for the prediction of the system behavior at the altered input (e.g. knock out mutations, natural expression variability), it may demonstrate the poor predictive power due to the ambiguity in the parameter estimates. We introduce a method of the predictive power evaluation under the parameter estimation uncertainty, Relative Sensitivity Analysis. The prediction problem is addressed in the context of gene circuit models describing the dynamics of segmentation gene expression in Drosophila embryo. Gene regulation in these models is introduced by a saturating sigmoid function of the concentrations of the regulatory gene products. We show how our approach can be applied to characterize the essential difference between the sensitivity properties of robust and non-robust solutions and select among the existing solutions those providing the correct system behavior at any reasonable input. In general, the method allows to uncover the sources of incorrect predictions and proposes the way to overcome the estimation uncertainties.
Sensitivity analysis of physical/operational parameters in neutron multiplicity counting
International Nuclear Information System (INIS)
Peerani, P.; Marin Ferrer, M.
2007-01-01
In this paper, we perform a sensitivity study on the influence of various physical and operational parameters on the results of neutron multiplicity counting. The purpose is to have a better understanding of the importance of each component and its contribution to the measurement uncertainty. Then we will be able to determine the optimal conditions for the operational parameters and for detector design and as well to point out weaknesses in the knowledge of critical fundamental nuclear data
Investigation of RADTRAN Stop Model input parameters for truck stops
International Nuclear Information System (INIS)
Griego, N.R.; Smith, J.D.; Neuhauser, K.S.
1996-01-01
RADTRAN is a computer code for estimating the risks and consequences as transport of radioactive materials (RAM). RADTRAN was developed and is maintained by Sandia National Laboratories for the US Department of Energy (DOE). For incident-free transportation, the dose to persons exposed while the shipment is stopped is frequently a major percentage of the overall dose. This dose is referred to as Stop Dose and is calculated by the Stop Model. Because stop dose is a significant portion of the overall dose associated with RAM transport, the values used as input for the Stop Model are important. Therefore, an investigation of typical values for RADTRAN Stop Parameters for truck stops was performed. The resulting data from these investigations were analyzed to provide mean values, standard deviations, and histograms. Hence, the mean values can be used when an analyst does not have a basis for selecting other input values for the Stop Model. In addition, the histograms and their characteristics can be used to guide statistical sampling techniques to measure sensitivity of the RADTRAN calculated Stop Dose to the uncertainties in the stop model input parameters. This paper discusses the details and presents the results of the investigation of stop model input parameters at truck stops
Li, Xin; Cai, Yu; Moloney, Brendan; Chen, Yiyi; Huang, Wei; Woods, Mark; Coakley, Fergus V; Rooney, William D; Garzotto, Mark G; Springer, Charles S
2016-08-01
Dynamic-Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has been used widely for clinical applications. Pharmacokinetic modeling of DCE-MRI data that extracts quantitative contrast reagent/tissue-specific model parameters is the most investigated method. One of the primary challenges in pharmacokinetic analysis of DCE-MRI data is accurate and reliable measurement of the arterial input function (AIF), which is the driving force behind all pharmacokinetics. Because of effects such as inflow and partial volume averaging, AIF measured from individual arteries sometimes require amplitude scaling for better representation of the blood contrast reagent (CR) concentration time-courses. Empirical approaches like blinded AIF estimation or reference tissue AIF derivation can be useful and practical, especially when there is no clearly visible blood vessel within the imaging field-of-view (FOV). Similarly, these approaches generally also require magnitude scaling of the derived AIF time-courses. Since the AIF varies among individuals even with the same CR injection protocol and the perfect scaling factor for reconstructing the ground truth AIF often remains unknown, variations in estimated pharmacokinetic parameters due to varying AIF scaling factors are of special interest. In this work, using simulated and real prostate cancer DCE-MRI data, we examined parameter variations associated with AIF scaling. Our results show that, for both the fast-exchange-limit (FXL) Tofts model and the water exchange sensitized fast-exchange-regime (FXR) model, the commonly fitted CR transfer constant (K(trans)) and the extravascular, extracellular volume fraction (ve) scale nearly proportionally with the AIF, whereas the FXR-specific unidirectional cellular water efflux rate constant, kio, and the CR intravasation rate constant, kep, are both AIF scaling insensitive. This indicates that, for DCE-MRI of prostate cancer and possibly other cancers, kio and kep may be more suitable imaging
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)
International Nuclear Information System (INIS)
Siegel, M.; Guzowski, R.; Rechard, R.; Erickson, K.
1986-01-01
The EPA Standard for geologic disposal of high level waste requires demonstration that the cumulative discharge of individual radioisotopes over a 10,000 year period at points 5 kilometers from the engineered barrier system will not exceed the limits prescribed in 40 CFR Part 191. The roles of the waste package, engineered facility, hydrogeology and geochemical processes in limiting radionuclide releases all must be considered in calculations designed to assess compliance of candidate repositories with the EPA Standard. In this talk, they will discuss the geochemical requirements of calculations used in these compliance assessments. In addition, they will describe the complementary roles of (1) simple models designed to bound the radionuclide discharge over the widest reasonable range of geochemical conditions and scenarios and (2) detailed geochemical models which can provide insights into the actual behavior of the radionuclides in the ground water. Finally, they will discuss development of sensitivity/uncertainty techniques designed to identify important site-specific geochemical parameters and processes using data from a basalt formation
Prior Sensitivity Analysis in Default Bayesian Structural Equation Modeling.
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).
Speed Sensorless mixed sensitivity linear parameter variant H_inf control of the induction motor
Toth, R.; Fodor, D.
2004-01-01
The paper shows the design of a robust control structure for the speed sensorless vector control of the IM, based on the mixed sensitivity (MS) linear parameter variant (LPV) H8 control theory. The controller makes possible the direct control of the flux and speed of the motor with torque adaptation
DEFF Research Database (Denmark)
Pingen, Georg; Evgrafov, Anton; Maute, Kurt
2009-01-01
We present an adjoint parameter sensitivity analysis formulation and solution strategy for the lattice Boltzmann method (LBM). The focus is on design optimization applications, in particular topology optimization. The lattice Boltzmann method is briefly described with an in-depth discussion...
Sensitivity analysis of large system of chemical kinetic parameters for engine combustion simulation
Energy Technology Data Exchange (ETDEWEB)
Hsieh, H; Sanz-Argent, J; Petitpas, G; Havstad, M; Flowers, D
2012-04-19
In this study, the authors applied the state-of-the art sensitivity methods to downselect system parameters from 4000+ to 8, (23000+ -> 4000+ -> 84 -> 8). This analysis procedure paves the way for future works: (1) calibrate the system response using existed experimental observations, and (2) predict future experiment results, using the calibrated system.
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
Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines
Kurç, Tahsin M.; Taveira, Luís F. R.; Melo, Alba C. M. A.; Gao, Yi; Kong, Jun; Saltz, Joel H.
2017-01-01
Abstract Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Availability and Implementation: Source code: https://github.com/SBU-BMI/region-templates/. Contact: teodoro@unb.br Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28062445
Models for setting ATM parameter values
DEFF Research Database (Denmark)
Blaabjerg, Søren; Gravey, A.; Romæuf, L.
1996-01-01
essential to set traffic characteristic values that are relevant to the considered cell stream, and that ensure that the amount of non-conforming traffic is small. Using a queueing model representation for the GCRA formalism, several methods are available for choosing the traffic characteristics. This paper......In ATM networks, a user should negotiate at connection set-up a traffic contract which includes traffic characteristics and requested QoS. The traffic characteristics currently considered are the Peak Cell Rate, the Sustainable Cell Rate, the Intrinsic Burst Tolerance and the Cell Delay Variation...... (CDV) tolerance(s). The values taken by these traffic parameters characterize the so-called ''Worst Case Traffic'' that is used by CAC procedures for accepting a new connection and allocating resources to it. Conformance to the negotiated traffic characteristics is defined, at the ingress User...
Global sensitivity analysis of DRAINMOD-FOREST, an integrated forest ecosystem model
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...
International Nuclear Information System (INIS)
Wołoszyn, Jerzy; Gołaś, Andrzej
2014-01-01
Highlights: • Paper propose a new methodology to sensitivity study of underground thermal storage. • Using MDF model and DOE technique significantly shorter of calculations time. • Calculation of one time step was equal to approximately 57 s. • Sensitivity study cover five thermo-physical parameters. • Conductivity of rock mass and grout material have a significant impact on efficiency. - Abstract: The aim of this study was to investigate the influence of selected parameters on the efficiency of underground thermal energy storage. In this paper, besides thermal conductivity, the effect of such parameters as specific heat, density of the rock mass, thermal conductivity and specific heat of grout material was investigated. Implementation of this objective requires the use of an efficient computational method. The aim of the research was achieved by using a new numerical model, Multi Degree of Freedom (MDF), as developed by the authors and Design of Experiment (DoE) techniques with a response surface. The presented methodology can significantly reduce the time that is needed for research and to determine the effect of various parameters on the efficiency of underground thermal energy storage. Preliminary results of the research confirmed that thermal conductivity of the rock mass has the greatest impact on the efficiency of underground thermal energy storage, and that other parameters also play quite significant role
Energy Technology Data Exchange (ETDEWEB)
Jeong, Jong Hwa; Lee, Heung Nae; Park, Jea Ho [KONES Corp., Seoul (Korea, Republic of); Lee, Won Jae [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Lee, Sang Il; Yoo, Yeon Jae [Hyundai Engineering Co., Seoul (Korea, Republic of)
2016-10-15
The heat generated from the VHTR is transferred to the intermediate loop through Intermediate Heat Exchanger (IHX). It is further passed on to the Sulfur-Iodine (SI) hydrogen production system (HPS) through Process Heat Exchanger (PHX). The IL provides the safety distance between the VHTR and HPS. Since the IL performance affects the overall nuclear HPS efficiency, it is required to optimize its design and operation parameters. In this study, the thermal-hydraulic sensitivity of IL parameters with various coolant options has been examined by using MARS-GCR code, which was already applied for the case of steam generator. Sensitivity study of the IL and PHX parameters has been carried out based on their thermal-hydraulic performance. Several parameters for design and operation, such as the pipe diameter, safety distance and surface area, are considered for different coolant options, He, CO{sub 2} and He-CO{sub 2} (2:8). It was found that the circulator work is the major factor affecting on the overall nuclear hydrogen production system efficiency. Circulator work increases with the safety distance, and decreases with the operation pressure and loop pipe diameter. Sensitivity results obtained from this study will contribute to the optimization of the IL design and operation parameters and the optimal coolant selection.
Stubberud, Marlene Waege; Myhre, Ane Marlene; Holand, Håkon; Kvalnes, Thomas; Ringsby, Thor Harald; Saether, Bernt-Erik; Jensen, Henrik
2017-05-01
The ratio between the effective and the census population size, Ne/N, is an important measure of the long-term viability and sustainability of a population. Understanding which demographic processes that affect Ne/N most will improve our understanding of how genetic drift and the probability of fixation of alleles is affected by demography. This knowledge may also be of vital importance in management of endangered populations and species. Here, we use data from 13 natural populations of house sparrow (Passer domesticus) in Norway to calculate the demographic parameters that determine Ne/N. Using the global variance-based Sobol' method for the sensitivity analyses, we found that Ne/N was most sensitive to demographic variance, especially among older individuals. Furthermore, the individual reproductive values (that determine the demographic variance) were most sensitive to variation in fecundity. Our results draw attention to the applicability of sensitivity analyses in population management and conservation. For population management aiming to reduce the loss of genetic variation, a sensitivity analysis may indicate the demographic parameters towards which resources should be focused. The result of such an analysis may depend on the life history and mating system of the population or species under consideration, because the vital rates and sex-age classes that Ne/N is most sensitive to may change accordingly. © 2017 John Wiley & Sons Ltd.
Study of the methodology for sensitivity calculations of fast reactors integral parameters
International Nuclear Information System (INIS)
Renke, C.A.C.
1981-06-01
A study of the methodology for sensitivity calculations of integral parameters of fast reactors for the adjustment of multigroup cross sections is presented. A description of several existent methods and theories is given, with special emphasis being regarded to variational perturbation theory, integrant of the sensitivity code VARI-1D used in this work. Two calculational systems are defined and a set of procedures and criteria is structured gathering the necessary conditions for the determination of the sensitivity coefficients. These coefficients are then computed by both the direct method and the variational perturbation theory. A reasonable number of sensitivity coefficients are computed and analyzed for three fast critical assemblies, covering a range of special interest of the spectrum. These coefficients are determined for severa integral parameters, for the capture and fission cross sections of the U-238 and Pu-239, covering all the energy up to 14.5 MeV. The nuclear data used were obtained the CARNAVAL II calculational system of the Instituto de Engenharia Nuclear. An optimization for sensitivity computations in a chainned sequence of procedures is made, yielding the sensitivities in the energy macrogroups as the final stage. (Author) [pt
Applying incentive sensitization models to behavioral addiction
DEFF Research Database (Denmark)
Rømer Thomsen, Kristine; Fjorback, Lone; Møller, Arne
2014-01-01
The incentive sensitization theory is a promising model for understanding the mechanisms underlying drug addiction, and has received support in animal and human studies. So far the theory has not been applied to the case of behavioral addictions like Gambling Disorder, despite sharing clinical...... symptoms and underlying neurobiology. We examine the relevance of this theory for Gambling Disorder and point to predictions for future studies. The theory promises a significant contribution to the understanding of behavioral addiction and opens new avenues for treatment....
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
Parameter Estimation of Partial Differential Equation Models
Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Maity, Arnab; Carroll, Raymond J.
2013-01-01
PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus
Mathematical properties and parameter estimation for transit compartment pharmacodynamic models.
Yates, James W T
2008-07-03
One feature of recent research in pharmacodynamic modelling has been the move towards more mechanistically based model structures. However, in all of these models there are common sub-systems, such as feedback loops and time-delays, whose properties and contribution to the model behaviour merit some mathematical analysis. In this paper a common pharmacodynamic model sub-structure is considered: the linear transit compartment. These models have a number of interesting properties as the length of the cascade chain is increased. In the limiting case a pure time-delay is achieved [Milsum, J.H., 1966. Biological Control Systems Analysis. McGraw-Hill Book Company, New York] and the initial behaviour becoming increasingly sensitive to parameter value perturbation. It is also shown that the modelled drug effect is attenuated, though the duration of action is longer. Through this analysis the range of behaviours that such models are capable of reproducing are characterised. The properties of these models and the experimental requirements are discussed in order to highlight how mathematical analysis prior to experimentation can enhance the utility of mathematical modelling.
Models for patients' recruitment in clinical trials and sensitivity analysis.
Mijoule, Guillaume; Savy, Stéphanie; Savy, Nicolas
2012-07-20
Taking a decision on the feasibility and estimating the duration of patients' recruitment in a clinical trial are very important but very hard questions to answer, mainly because of the huge variability of the system. The more elaborated works on this topic are those of Anisimov and co-authors, where they investigate modelling of the enrolment period by using Gamma-Poisson processes, which allows to develop statistical tools that can help the manager of the clinical trial to answer these questions and thus help him to plan the trial. The main idea is to consider an ongoing study at an intermediate time, denoted t(1). Data collected on [0,t(1)] allow to calibrate the parameters of the model, which are then used to make predictions on what will happen after t(1). This method allows us to estimate the probability of ending the trial on time and give possible corrective actions to the trial manager especially regarding how many centres have to be open to finish on time. In this paper, we investigate a Pareto-Poisson model, which we compare with the Gamma-Poisson one. We will discuss the accuracy of the estimation of the parameters and compare the models on a set of real case data. We make the comparison on various criteria : the expected recruitment duration, the quality of fitting to the data and its sensitivity to parameter errors. We discuss the influence of the centres opening dates on the estimation of the duration. This is a very important question to deal with in the setting of our data set. In fact, these dates are not known. For this discussion, we consider a uniformly distributed approach. Finally, we study the sensitivity of the expected duration of the trial with respect to the parameters of the model : we calculate to what extent an error on the estimation of the parameters generates an error in the prediction of the duration.
Mass balance model parameter transferability on a tropical glacier
Gurgiser, Wolfgang; Mölg, Thomas; Nicholson, Lindsey; Kaser, Georg
2013-04-01
The mass balance and melt water production of glaciers is of particular interest in the Peruvian Andes where glacier melt water has markedly increased water supply during the pronounced dry seasons in recent decades. However, the melt water contribution from glaciers is projected to decrease with appreciable negative impacts on the local society within the coming decades. Understanding mass balance processes on tropical glaciers is a prerequisite for modeling present and future glacier runoff. As a first step towards this aim we applied a process-based surface mass balance model in order to calculate observed ablation at two stakes in the ablation zone of Shallap Glacier (4800 m a.s.l., 9°S) in the Cordillera Blanca, Peru. Under the tropical climate, the snow line migrates very frequently across most of the ablation zone all year round causing large temporal and spatial variations of glacier surface conditions and related ablation. Consequently, pronounced differences between the two chosen stakes and the two years were observed. Hourly records of temperature, humidity, wind speed, short wave incoming radiation, and precipitation are available from an automatic weather station (AWS) on the moraine near the glacier for the hydrological years 2006/07 and 2007/08 while stake readings are available at intervals of between 14 to 64 days. To optimize model parameters, we used 1000 model simulations in which the most sensitive model parameters were varied randomly within their physically meaningful ranges. The modeled surface height change was evaluated against the two stake locations in the lower ablation zone (SH11, 4760m) and in the upper ablation zone (SH22, 4816m), respectively. The optimal parameter set for each point achieved good model skill but if we transfer the best parameter combination from one stake site to the other stake site model errors increases significantly. The same happens if we optimize the model parameters for each year individually and transfer
Tahmasbi, Vahid; Ghoreishi, Majid; Zolfaghari, Mojtaba
2017-11-01
The bone drilling process is very prominent in orthopedic surgeries and in the repair of bone fractures. It is also very common in dentistry and bone sampling operations. Due to the complexity of bone and the sensitivity of the process, bone drilling is one of the most important and sensitive processes in biomedical engineering. Orthopedic surgeries can be improved using robotic systems and mechatronic tools. The most crucial problem during drilling is an unwanted increase in process temperature (higher than 47 °C), which causes thermal osteonecrosis or cell death and local burning of the bone tissue. Moreover, imposing higher forces to the bone may lead to breaking or cracking and consequently cause serious damage. In this study, a mathematical second-order linear regression model as a function of tool drilling speed, feed rate, tool diameter, and their effective interactions is introduced to predict temperature and force during the bone drilling process. This model can determine the maximum speed of surgery that remains within an acceptable temperature range. Moreover, for the first time, using designed experiments, the bone drilling process was modeled, and the drilling speed, feed rate, and tool diameter were optimized. Then, using response surface methodology and applying a multi-objective optimization, drilling force was minimized to sustain an acceptable temperature range without damaging the bone or the surrounding tissue. In addition, for the first time, Sobol statistical sensitivity analysis is used to ascertain the effect of process input parameters on process temperature and force. The results show that among all effective input parameters, tool rotational speed, feed rate, and tool diameter have the highest influence on process temperature and force, respectively. The behavior of each output parameters with variation in each input parameter is further investigated. Finally, a multi-objective optimization has been performed considering all the
Sensitivity Analysis of Launch Vehicle Debris Risk Model
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 the Bone Fracture Risk Model
Lewandowski, Beth; Myers, Jerry; Sibonga, Jean Diane
2017-01-01
Introduction: The probability of bone fracture during and after spaceflight is quantified to aid in mission planning, to determine required astronaut fitness standards and training requirements and to inform countermeasure research and design. Probability is quantified with a probabilistic modeling approach where distributions of model parameter values, instead of single deterministic values, capture the parameter variability within the astronaut population and fracture predictions are probability distributions with a mean value and an associated uncertainty. Because of this uncertainty, the model in its current state cannot discern an effect of countermeasures on fracture probability, for example between use and non-use of bisphosphonates or between spaceflight exercise performed with the Advanced Resistive Exercise Device (ARED) or on devices prior to installation of ARED on the International Space Station. This is thought to be due to the inability to measure key contributors to bone strength, for example, geometry and volumetric distributions of bone mass, with areal bone mineral density (BMD) measurement techniques. To further the applicability of model, we performed a parameter sensitivity study aimed at identifying those parameter uncertainties that most effect the model forecasts in order to determine what areas of the model needed enhancements for reducing uncertainty. Methods: The bone fracture risk model (BFxRM), originally published in (Nelson et al) is a probabilistic model that can assess the risk of astronaut bone fracture. This is accomplished by utilizing biomechanical models to assess the applied loads; utilizing models of spaceflight BMD loss in at-risk skeletal locations; quantifying bone strength through a relationship between areal BMD and bone failure load; and relating fracture risk index (FRI), the ratio of applied load to bone strength, to fracture probability. There are many factors associated with these calculations including
International Nuclear Information System (INIS)
Rawat, S; Chavan, V M; Warrier, M; Chaturvedi, S
2011-01-01
The effect of temperature on the void nucleation and growth is studied using the molecular dynamics (MD) code LAMMPS (Large-Scale Atomic/Molecular Massively Parallel Simulator). Single crystal copper is triaxially expanded at 5 × 10 9 s −1 strain rate keeping the temperature constant. It is shown that the nucleation and growth of voids at these atomistic scales follows a macroscopic nucleation and growth (NAG) model. As the temperature increases there is a steady decrease in the nucleation and growth thresholds. As the melting point of copper is approached, a double-dip in the pressure–time profile is observed. Analysis of this double-dip shows that the first minimum corresponds to the disappearance of the long-range order due to the creation of stacking faults and the system no longer has a FCC structure. There is no nucleation of voids at this juncture. The second minimum corresponds to the nucleation and incipient growth of voids. We present the sensitivity of NAG parameters to temperature and the analysis of double-dip in the pressure–time profile for single crystal copper at 1250 K
Brady, Oliver J; Godfray, H Charles J; Tatem, Andrew J; Gething, Peter W; Cohen, Justin M; McKenzie, F Ellis; Perkins, T Alex; Reiner, Robert C; Tusting, Lucy S; Sinka, Marianne E; Moyes, Catherine L; Eckhoff, Philip A; Scott, Thomas W; Lindsay, Steven W; Hay, Simon I; Smith, David L
2016-02-01
Major gains have been made in reducing malaria transmission in many parts of the world, principally by scaling-up coverage with long-lasting insecticidal nets and indoor residual spraying. Historically, choice of vector control intervention has been largely guided by a parameter sensitivity analysis of George Macdonald's theory of vectorial capacity that suggested prioritizing methods that kill adult mosquitoes. While this advice has been highly successful for transmission suppression, there is a need to revisit these arguments as policymakers in certain areas consider which combinations of interventions are required to eliminate malaria. Using analytical solutions to updated equations for vectorial capacity we build on previous work to show that, while adult killing methods can be highly effective under many circumstances, other vector control methods are frequently required to fill effective coverage gaps. These can arise due to pre-existing or developing mosquito physiological and behavioral refractoriness but also due to additive changes in the relative importance of different vector species for transmission. Furthermore, the optimal combination of interventions will depend on the operational constraints and costs associated with reaching high coverage levels with each intervention. Reaching specific policy goals, such as elimination, in defined contexts requires increasingly non-generic advice from modelling. Our results emphasize the importance of measuring baseline epidemiology, intervention coverage, vector ecology and program operational constraints in predicting expected outcomes with different combinations of interventions. © The Author 2016. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.
Sensitive parameters' optimization of the permanent magnet supporting mechanism
Energy Technology Data Exchange (ETDEWEB)
Liu, Yongguang; Gao, Xiaohui; Wang, Yixuan; Yang, Xiaowei [Beihang University, Beijing (China)
2014-07-15
The fast development of the ultra-high speed vertical rotor promotes the study and exploration for the supporting mechanism. It has become the focus of research that how to improve the speed and overcome the vibration when the rotors pass through the low-order critical frequencies. This paper introduces a kind of permanent magnet (PM) supporting mechanism and describes an optimization method of its sensitive parameters, which can make the vertical rotor system reach 80000 r/min smoothly. Firstly we find the sensitive parameters through analyzing the rotor's features in the process of achieving high-speed, then, study these sensitive parameters and summarize the regularities with the method of combining the experiment and the finite element method (FEM), at last, achieve the optimization method of these parameters. That will not only get a stable effect of raising speed and shorten the debugging time greatly, but also promote the extensive application of the PM supporting mechanism in the ultra-high speed vertical rotors.
Kwon, Yong-Seok; Naeem, Khurram; Jeon, Min Yong; Kwon, Il-bum
2017-04-01
We analyze the relations of parameters in moving average method to enhance the event detectability of phase sensitive optical time domain reflectometer (OTDR). If the external events have unique frequency of vibration, then the control parameters of moving average method should be optimized in order to detect these events efficiently. A phase sensitive OTDR was implemented by a pulsed light source, which is composed of a laser diode, a semiconductor optical amplifier, an erbium-doped fiber amplifier, a fiber Bragg grating filter, and a light receiving part, which has a photo-detector and high speed data acquisition system. The moving average method is operated with the control parameters: total number of raw traces, M, number of averaged traces, N, and step size of moving, n. The raw traces are obtained by the phase sensitive OTDR with sound signals generated by a speaker. Using these trace data, the relation of the control parameters is analyzed. In the result, if the event signal has one frequency, then the optimal values of N, n are existed to detect the event efficiently.
Sensitivity of Austempering Heat Treatment of Ductile Irons to Changes in Process Parameters
Boccardo, A. D.; Dardati, P. M.; Godoy, L. A.; Celentano, D. J.
2018-03-01
Austempered ductile iron (ADI) is frequently obtained by means of a three-step austempering heat treatment. The parameters of this process play a crucial role on the microstructure of the final product. This paper considers the influence of some process parameters (i.e., the initial microstructure of ductile iron and the thermal cycle) on key features of the heat treatment (such as minimum required time for austenitization and austempering and microstructure of the final product). A computational simulation of the austempering heat treatment is reported in this work, which accounts for a coupled thermo-metallurgical behavior in terms of the evolution of temperature at the scale of the part being investigated (the macroscale) and the evolution of phases at the scale of microconstituents (the microscale). The paper focuses on the sensitivity of the process by looking at a sensitivity index and scatter plots. The sensitivity indices are determined by using a technique based on the variance of the output. The results of this study indicate that both the initial microstructure and the thermal cycle parameters play a key role in the production of ADI. This work also provides a guideline to help selecting values of the appropriate process parameters to obtain parts with a required microstructural characteristic.
Sensitivity of Austempering Heat Treatment of Ductile Irons to Changes in Process Parameters
Boccardo, A. D.; Dardati, P. M.; Godoy, L. A.; Celentano, D. J.
2018-06-01
Austempered ductile iron (ADI) is frequently obtained by means of a three-step austempering heat treatment. The parameters of this process play a crucial role on the microstructure of the final product. This paper considers the influence of some process parameters ( i.e., the initial microstructure of ductile iron and the thermal cycle) on key features of the heat treatment (such as minimum required time for austenitization and austempering and microstructure of the final product). A computational simulation of the austempering heat treatment is reported in this work, which accounts for a coupled thermo-metallurgical behavior in terms of the evolution of temperature at the scale of the part being investigated (the macroscale) and the evolution of phases at the scale of microconstituents (the microscale). The paper focuses on the sensitivity of the process by looking at a sensitivity index and scatter plots. The sensitivity indices are determined by using a technique based on the variance of the output. The results of this study indicate that both the initial microstructure and the thermal cycle parameters play a key role in the production of ADI. This work also provides a guideline to help selecting values of the appropriate process parameters to obtain parts with a required microstructural characteristic.
Tøndel, Kristin; Niederer, Steven A; Land, Sander; Smith, Nicolas P
2014-05-20
Striking a balance between the degree of model complexity and parameter identifiability, while still producing biologically feasible simulations using modelling is a major challenge in computational biology. While these two elements of model development are closely coupled, parameter fitting from measured data and analysis of model mechanisms have traditionally been performed separately and sequentially. This process produces potential mismatches between model and data complexities that can compromise the ability of computational frameworks to reveal mechanistic insights or predict new behaviour. In this study we address this issue by presenting a generic framework for combined model parameterisation, comparison of model alternatives and analysis of model mechanisms. The presented methodology is based on a combination of multivariate metamodelling (statistical approximation of the input-output relationships of deterministic models) and a systematic zooming into biologically feasible regions of the parameter space by iterative generation of new experimental designs and look-up of simulations in the proximity of the measured data. The parameter fitting pipeline includes an implicit sensitivity analysis and analysis of parameter identifiability, making it suitable for testing hypotheses for model reduction. Using this approach, under-constrained model parameters, as well as the coupling between parameters within the model are identified. The methodology is demonstrated by refitting the parameters of a published model of cardiac cellular mechanics using a combination of measured data and synthetic data from an alternative model of the same system. Using this approach, reduced models with simplified expressions for the tropomyosin/crossbridge kinetics were found by identification of model components that can be omitted without affecting the fit to the parameterising data. Our analysis revealed that model parameters could be constrained to a standard deviation of on
Sensitivity of system stability to model structure
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.
Sensitivity of SBLOCA analysis to model nodalization
International Nuclear Information System (INIS)
Lee, C.; Ito, T.; Abramson, P.B.
1983-01-01
The recent Semiscale test S-UT-8 indicates the possibility for primary liquid to hang up in the steam generators during a SBLOCA, permitting core uncovery prior to loop-seal clearance. In analysis of Small Break Loss of Coolant Accidents with RELAP5, it is found that resultant transient behavior is quite sensitive to the selection of nodalization for the steam generators. Although global parameters such as integrated mass loss, primary inventory and primary pressure are relatively insensitive to the nodalization, it is found that the predicted distribution of inventory around the primary is significantly affected by nodalization. More detailed nodalization predicts that more of the inventory tends to remain in the steam generators, resulting in less inventory in the reactor vessel and therefore causing earlier and more severe core uncovery
Sensitivity analysis of infectious disease models: methods, advances and their application
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
Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models
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.
Sensitivity Analysis of Depletion Parameters for Heat Load Evaluation of PWR Spent Fuel Storage Pool
International Nuclear Information System (INIS)
Kim, In Young; Lee, Un Chul
2011-01-01
As necessity of safety re-evaluation for spent fuel storage facility has emphasized after the Fukushima accident, accuracy improvement of heat load evaluation has become more important to acquire reliable thermal-hydraulic evaluation results. As groundwork, parametric and sensitivity analyses of various storage conditions for Kori Unit 4 spent fuel storage pool and spent fuel depletion parameters such as axial burnup effect, operation history, and specific heat are conducted using ORIGEN2 code. According to heat load evaluation and parametric sensitivity analyses, decay heat of last discharged fuel comprises maximum 80.42% of total heat load of storage facility and there is a negative correlation between effect of depletion parameters and cooling period. It is determined that specific heat is most influential parameter and operation history is secondly influential parameter. And decay heat of just discharged fuel is varied from 0.34 to 1.66 times of average value and decay heat of 1 year cooled fuel is varied from 0.55 to 1.37 times of average value in accordance with change of specific power. Namely depletion parameters can cause large variation in decay heat calculation of short-term cooled fuel. Therefore application of real operation data instead of user selection value is needed to improve evaluation accuracy. It is expected that these results could be used to improve accuracy of heat load assessment and evaluate uncertainty of calculated heat load.
Studying the physics potential of long-baseline experiments in terms of new sensitivity parameters
International Nuclear Information System (INIS)
Singh, Mandip
2016-01-01
We investigate physics opportunities to constraint the leptonic CP-violation phase δ_C_P through numerical analysis of working neutrino oscillation probability parameters, in the context of long-baseline experiments. Numerical analysis of two parameters, the “transition probability δ_C_P phase sensitivity parameter (A"M)” and the “CP-violation probability δ_C_P phase sensitivity parameter (A"C"P),” as functions of beam energy and/or baseline have been carried out. It is an elegant technique to broadly analyze different experiments to constrain the δ_C_P phase and also to investigate the mass hierarchy in the leptonic sector. Positive and negative values of the parameter A"C"P, corresponding to either hierarchy in the specific beam energy ranges, could be a very promising way to explore the mass hierarchy and δ_C_P phase. The keys to more robust bounds on the δ_C_P phase are improvements of the involved detection techniques to explore lower energies and relatively long baseline regions with better experimental accuracy.
Dependence of mis-alignment sensitivity of ring laser gyro cavity on cavity parameters
Energy Technology Data Exchange (ETDEWEB)
Sun Feng; Zhang Xi; Zhang Hongbo; Yang Changcheng, E-mail: sunok1234@sohu.com [Huazhong Institute of Electro-Optics - Wuhan National Lab for Optoelectronics, Wuhan, Hubei (China)
2011-02-01
The ring laser gyroscope (RLG), as a rotation sensor, has been widely used for navigation and guidance on vehicles and missiles. The environment of strong random-vibration and large acceleration may deteriorate the performance of the RLG due to the vibration-induced tilting of the mirrors. In this paper the RLG performance is theoretically analyzed and the parameters such as the beam diameter at the aperture, cavity mirror alignment sensitivities and power loss due to the mirror tilting are calculated. It is concluded that by carefully choosing the parameters, the significant loss in laser power can be avoided.
Directory of Open Access Journals (Sweden)
Hui Wan
2015-06-01
Full Text Available Sensitivity analysis is a fundamental approach to identify the most significant and sensitive parameters, helping us to understand complex hydrological models, particularly for time-consuming distributed flood forecasting models based on complicated theory with numerous parameters. Based on Sobol’ method, this study compared the sensitivity and interactions of distributed flood forecasting model parameters with and without accounting for correlation. Four objective functions: (1 Nash–Sutcliffe efficiency (ENS; (2 water balance coefficient (WB; (3 peak discharge efficiency (EP; and (4 time to peak efficiency (ETP were implemented to the Liuxihe model with hourly rainfall-runoff data collected in the Nanhua Creek catchment, Pearl River, China. Contrastive results for the sensitivity and interaction analysis were also illustrated among small, medium, and large flood magnitudes. Results demonstrated that the choice of objective functions had no effect on the sensitivity classification, while it had great influence on the sensitivity ranking for both uncorrelated and correlated cases. The Liuxihe model behaved and responded uniquely to various flood conditions. The results also indicated that the pairwise parameters interactions revealed a non-ignorable contribution to the model output variance. Parameters with high first or total order sensitivity indices presented a corresponding high second order sensitivity indices and correlation coefficients with other parameters. Without considering parameter correlations, the variance contributions of highly sensitive parameters might be underestimated and those of normally sensitive parameters might be overestimated. This research laid a basic foundation to improve the understanding of complex model behavior.
Convergence of surface diffusion parameters with model crystal size
Cohen, Jennifer M.; Voter, Arthur F.
1994-07-01
A study of the variation in the calculated quantities for adatom diffusion with respect to the size of the model crystal is presented. The reported quantities include surface diffusion barrier heights, pre-exponential factors, and dynamical correction factors. Embedded atom method (EAM) potentials were used throughout this effort. Both the layer size and the depth of the crystal were found to influence the values of the Arrhenius factors significantly. In particular, exchange type mechanisms required a significantly larger model than standard hopping mechanisms to determine adatom diffusion barriers of equivalent accuracy. The dynamical events that govern the corrections to transition state theory (TST) did not appear to be as sensitive to crystal depth. Suitable criteria for the convergence of the diffusion parameters with regard to the rate properties are illustrated.
A New Computationally Frugal Method For Sensitivity Analysis Of Environmental Models
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.
Study of the sensitivity of integral parameters related to 232 Thorium cross sections
International Nuclear Information System (INIS)
Guimaraes, L.N.F.; Menezes, A.
1986-01-01
The THOR critical assembly is used to test 232 Th basic nuclear data from ENDL-78, ENDF/B-IV, INDL-83, JENDL-1 and JENDL-2. The FORSS and UNISENS systems are used to calculate integral parameters and sensitivity profiles. The results show that 232 Th from JENDL-2 is superior to the others, with ENDL-78 showing the worst performance. The discrepancies can be credited to the different evaluations for the 232 Thorium scattering cross section. (Author) [pt
SENSITIVITY OF BODY SWAY PARAMETERS DURING QUIET STANDING TO MANIPULATION OF SUPPORT SURFACE SIZE
Directory of Open Access Journals (Sweden)
Sarabon Nejc
2010-09-01
Full Text Available The centre of pressure (COP movement during stance maintenance on a stable surface is commonly used to describe and evaluate static balance. The aim of our study was to test sensitivity of individual COP parameters to different stance positions which were used to address size specific changes in the support surface. Twenty-nine subjects participated in the study. They carried out three 60-second repetitions of each of the five balance tasks (parallel stance, semi-tandem stance, tandem stance, contra-tandem stance, single leg stance. Using the force plate, the monitored parameters included the total COP distance, the distance covered in antero-posterior and medio-lateral directions, the maximum oscillation amplitude in antero-posterior and medio-lateral directions, the total frequency of oscillation, as well as the frequency of oscillation in antero-posterior and medio-lateral directions. The parameters which describe the total COP distance were the most sensitive to changes in the balance task, whereas the frequency of oscillation proved to be sensitive to a slightly lesser extent. Reductions in the support surface size in each of the directions resulted in proportional changes of antero-posterior and medio- lateral directions. The frequency of oscillation did not increase evenly with the increase in the level of difficulty of the balance task, but reached a certain value, above which it did not increase. Our study revealed the monitored parameters of the COP to be sensitive to the support surface size manipulations. The results of the study provide an important source for clinical and research use of the body sway measurements.
Determination of new electroweak parameters at the ILC. Sensitivity to new physics
Energy Technology Data Exchange (ETDEWEB)
Beyer, M.; Schmidt, E.; Schroeder, H. [Rostock Univ. (Germany). Inst. fuer Physik; Kilian, W. [Siegen Univ. (Gesamthochschule) (Germany). Fach Physik]|[Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Krstonosic, P.; Reuter, J. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Moenig, K. [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany)
2006-04-15
We present a study of the sensitivity of an International Linear Collider (ILC) to electroweak parameters in the absence of a light Higgs boson. In particular, we consider those parameters that have been inaccessible at previous colliders, quartic gauge couplings. Within a generic effective-field theory context we analyze all processes that contain quasi-elastic weak-boson scattering, using complete six-fermion matrix elements in unweighted event samples, fast simulation of the ILC detector, and a multidimensional parameter fit of the set of anomalous couplings. The analysis does not rely on simplifying assumptions such as custodial symmetry or approximations such as the equivalence theorem. We supplement this by a similar new study of triple weak-boson production, which is sensitive to the same set of anomalous couplings. Including the known results on triple gauge couplings and oblique corrections, we thus quantitatively determine the indirect sensitivity of the ILC to new physics in the electroweak symmetry-breaking sector, conveniently parameterized by real or fictitious resonances in each accessible spin/isospin channel. (Orig.)
Determination of new electroweak parameters at the ILC. Sensitivity to new physics
International Nuclear Information System (INIS)
Beyer, M.; Schmidt, E.; Schroeder, H.; Krstonosic, P.; Reuter, J.; Moenig, K.
2006-04-01
We present a study of the sensitivity of an International Linear Collider (ILC) to electroweak parameters in the absence of a light Higgs boson. In particular, we consider those parameters that have been inaccessible at previous colliders, quartic gauge couplings. Within a generic effective-field theory context we analyze all processes that contain quasi-elastic weak-boson scattering, using complete six-fermion matrix elements in unweighted event samples, fast simulation of the ILC detector, and a multidimensional parameter fit of the set of anomalous couplings. The analysis does not rely on simplifying assumptions such as custodial symmetry or approximations such as the equivalence theorem. We supplement this by a similar new study of triple weak-boson production, which is sensitive to the same set of anomalous couplings. Including the known results on triple gauge couplings and oblique corrections, we thus quantitatively determine the indirect sensitivity of the ILC to new physics in the electroweak symmetry-breaking sector, conveniently parameterized by real or fictitious resonances in each accessible spin/isospin channel. (Orig.)
Supplementary Material for: A global sensitivity analysis approach for morphogenesis models
Boas, Sonja; Navarro, Marí a; Merks, Roeland; Blom, Joke
2015-01-01
) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided
A Fault Alarm and Diagnosis Method Based on Sensitive Parameters and Support Vector Machine
Zhang, Jinjie; Yao, Ziyun; Lv, Zhiquan; Zhu, Qunxiong; Xu, Fengtian; Jiang, Zhinong
2015-08-01
Study on the extraction of fault feature and the diagnostic technique of reciprocating compressor is one of the hot research topics in the field of reciprocating machinery fault diagnosis at present. A large number of feature extraction and classification methods have been widely applied in the related research, but the practical fault alarm and the accuracy of diagnosis have not been effectively improved. Developing feature extraction and classification methods to meet the requirements of typical fault alarm and automatic diagnosis in practical engineering is urgent task. The typical mechanical faults of reciprocating compressor are presented in the paper, and the existing data of online monitoring system is used to extract fault feature parameters within 15 types in total; the inner sensitive connection between faults and the feature parameters has been made clear by using the distance evaluation technique, also sensitive characteristic parameters of different faults have been obtained. On this basis, a method based on fault feature parameters and support vector machine (SVM) is developed, which will be applied to practical fault diagnosis. A better ability of early fault warning has been proved by the experiment and the practical fault cases. Automatic classification by using the SVM to the data of fault alarm has obtained better diagnostic accuracy.
Impact parameter sensitive study of inner-shell atomic processes in the experimental storage ring
Gumberidze, A.; Kozhuharov, C.; Zhang, R. T.; Trotsenko, S.; Kozhedub, Y. S.; DuBois, R. D.; Beyer, H. F.; Blumenhagen, K.-H.; Brandau, C.; Bräuning-Demian, A.; Chen, W.; Forstner, O.; Gao, B.; Gassner, T.; Grisenti, R. E.; Hagmann, S.; Hillenbrand, P.-M.; Indelicato, P.; Kumar, A.; Lestinsky, M.; Litvinov, Yu. A.; Petridis, N.; Schury, D.; Spillmann, U.; Trageser, C.; Trassinelli, M.; Tu, X.; Stöhlker, Th.
2017-10-01
In this work, we present a pilot experiment in the experimental storage ring (ESR) at GSI devoted to impact parameter sensitive studies of inner shell atomic processes for low-energy (heavy-) ion-atom collisions. The experiment was performed with bare and He-like xenon ions (Xe54+, Xe52+) colliding with neutral xenon gas atoms, resulting in a symmetric collision system. This choice of the projectile charge states was made in order to compare the effect of a filled K-shell with the empty one. The projectile and target X-rays have been measured at different observation angles for all impact parameters as well as for the impact parameter range of ∼35-70 fm.
Stability and Sensitive Analysis of a Model with Delay Quorum Sensing
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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.
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.
Deckers, Dave L.E.H.; Booij, Martijn J.; Rientjes, T.H.M.; Krol, Martinus S.
2010-01-01
This study attempts to examine if catchment variability favours regionalisation by principles of catchment similarity. Our work combines calibration of a simple conceptual model for multiple objectives and multi-regression analyses to establish a regional model between model sensitive parameters and
Development of Health Parameter Model for Risk Prediction of CVD Using SVM
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P. Unnikrishnan
2016-01-01
Full Text Available Current methods of cardiovascular risk assessment are performed using health factors which are often based on the Framingham study. However, these methods have significant limitations due to their poor sensitivity and specificity. We have compared the parameters from the Framingham equation with linear regression analysis to establish the effect of training of the model for the local database. Support vector machine was used to determine the effectiveness of machine learning approach with the Framingham health parameters for risk assessment of cardiovascular disease (CVD. The result shows that while linear model trained using local database was an improvement on Framingham model, SVM based risk assessment model had high sensitivity and specificity of prediction of CVD. This indicates that using the health parameters identified using Framingham study, machine learning approach overcomes the low sensitivity and specificity of Framingham model.
Sensitivity of NTCP parameter values against a change of dose calculation algorithm
International Nuclear Information System (INIS)
Brink, Carsten; Berg, Martin; Nielsen, Morten
2007-01-01
Optimization of radiation treatment planning requires estimations of the normal tissue complication probability (NTCP). A number of models exist that estimate NTCP from a calculated dose distribution. Since different dose calculation algorithms use different approximations the dose distributions predicted for a given treatment will in general depend on the algorithm. The purpose of this work is to test whether the optimal NTCP parameter values change significantly when the dose calculation algorithm is changed. The treatment plans for 17 breast cancer patients have retrospectively been recalculated with a collapsed cone algorithm (CC) to compare the NTCP estimates for radiation pneumonitis with those obtained from the clinically used pencil beam algorithm (PB). For the PB calculations the NTCP parameters were taken from previously published values for three different models. For the CC calculations the parameters were fitted to give the same NTCP as for the PB calculations. This paper demonstrates that significant shifts of the NTCP parameter values are observed for three models, comparable in magnitude to the uncertainties of the published parameter values. Thus, it is important to quote the applied dose calculation algorithm when reporting estimates of NTCP parameters in order to ensure correct use of the models
Models for estimating photosynthesis parameters from in situ production profiles
Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana
2017-12-01
The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of
Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.
2018-03-01
We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Directory of Open Access Journals (Sweden)
Jinchao Feng
2018-03-01
Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Sensitivity Analysis of Fatigue Crack Growth Model for API Steels in Gaseous Hydrogen.
Amaro, Robert L; Rustagi, Neha; Drexler, Elizabeth S; Slifka, Andrew J
2014-01-01
A model to predict fatigue crack growth of API pipeline steels in high pressure gaseous hydrogen has been developed and is presented elsewhere. The model currently has several parameters that must be calibrated for each pipeline steel of interest. This work provides a sensitivity analysis of the model parameters in order to provide (a) insight to the underlying mathematical and mechanistic aspects of the model, and (b) guidance for model calibration of other API steels.
Sensitivity Analysis of the USLE Soil Erodibility Factor to Its Determining Parameters
Mitova, Milena; Rousseva, Svetla
2014-05-01
Soil erosion is recognized as one of the most serious soil threats worldwide. Soil erosion prediction is the first step in soil conservation planning. The Universal Soil Loss Equation (USLE) is one of the most widely used models for soil erosion predictions. One of the five USLE predictors is the soil erodibility factor (K-factor), which evaluates the impact of soil characteristics on soil erosion rates. Soil erodibility nomograph defines K-factor depending on soil characteristics, such as: particle size distribution (fractions finer that 0.002 mm and from 0.1 to 0.002 mm), organic matter content, soil structure and soil profile water permeability. Identifying the soil characteristics, which mostly influence the K-factor would give an opportunity to control the soil loss through erosion by controlling the parameters, which reduce the K-factor value. The aim of the report is to present the results of analysis of the relative weight of these soil characteristics in the K-factor values. The relative impact of the soil characteristics on K-factor was studied through a series of statistical analyses of data from the geographic database for soil erosion risk assessments in Bulgaria. Degree of correlation between K-factor values and the parameters that determine it was studied by correlation analysis. The sensitivity of the K-factor was determined by studying the variance of each parameter within the range between minimum and maximum possible values considering average value of the other factors. Normalizing transformation of data sets was applied because of the different dimensions and the orders of variation of the values of the various parameters. The results show that the content of particles finer than 0.002 mm has the most significant relative impact on the soil erodibility, followed by the content of particles with size from 0.1 mm to 0.002 mm, the class of the water permeability of the soil profile, the content of organic matter and the aggregation class. The
Sensitivity study and parameter optimization of OCD tool for 14nm finFET process
Zhang, Zhensheng; Chen, Huiping; Cheng, Shiqiu; Zhan, Yunkun; Huang, Kun; Shi, Yaoming; Xu, Yiping
2016-03-01
Optical critical dimension (OCD) measurement has been widely demonstrated as an essential metrology method for monitoring advanced IC process in the technology node of 90 nm and beyond. However, the rapidly shrunk critical dimensions of the semiconductor devices and the increasing complexity of the manufacturing process bring more challenges to OCD. The measurement precision of OCD technology highly relies on the optical hardware configuration, spectral types, and inherently interactions between the incidence of light and various materials with various topological structures, therefore sensitivity analysis and parameter optimization are very critical in the OCD applications. This paper presents a method for seeking the optimum sensitive measurement configuration to enhance the metrology precision and reduce the noise impact to the greatest extent. In this work, the sensitivity of different types of spectra with a series of hardware configurations of incidence angles and azimuth angles were investigated. The optimum hardware measurement configuration and spectrum parameter can be identified. The FinFET structures in the technology node of 14 nm were constructed to validate the algorithm. This method provides guidance to estimate the measurement precision before measuring actual device features and will be beneficial for OCD hardware configuration.
Sensitivity Analysis of a Riparian Vegetation Growth Model
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Michael Nones
2016-11-01
Full Text Available The paper presents a sensitivity analysis of two main parameters used in a mathematic model able to evaluate the effects of changing hydrology on the growth of riparian vegetation along rivers and its effects on the cross-section width. Due to a lack of data in existing literature, in a past study the schematization proposed here was applied only to two large rivers, assuming steady conditions for the vegetational carrying capacity and coupling the vegetal model with a 1D description of the river morphology. In this paper, the limitation set by steady conditions is overcome, imposing the vegetational evolution dependent upon the initial plant population and the growth rate, which represents the potential growth of the overall vegetation along the watercourse. The sensitivity analysis shows that, regardless of the initial population density, the growth rate can be considered the main parameter defining the development of riparian vegetation, but it results site-specific effects, with significant differences for large and small rivers. Despite the numerous simplifications adopted and the small database analyzed, the comparison between measured and computed river widths shows a quite good capability of the model in representing the typical interactions between riparian vegetation and water flow occurring along watercourses. After a thorough calibration, the relatively simple structure of the code permits further developments and applications to a wide range of alluvial rivers.
Optimizing incomplete sample designs for item response model parameters
van der Linden, Willem J.
Several models for optimizing incomplete sample designs with respect to information on the item parameters are presented. The following cases are considered: (1) known ability parameters; (2) unknown ability parameters; (3) item sets with multiple ability scales; and (4) response models with
Directory of Open Access Journals (Sweden)
David Ojeda
Full Text Available Although the therapeutic effects of Vagus Nerve Stimulation (VNS have been recognized in pre-clinical and pilot clinical studies, the effect of different stimulation configurations on the cardiovascular response is still an open question, especially in the case of VNS delivered synchronously with cardiac activity. In this paper, we propose a formal mathematical methodology to analyze the acute cardiac response to different VNS configurations, jointly considering the chronotropic, dromotropic and inotropic cardiac effects. A latin hypercube sampling method was chosen to design a uniform experimental plan, composed of 75 different VNS configurations, with different values for the main parameters (current amplitude, number of delivered pulses, pulse width, interpulse period and the delay between the detected cardiac event and VNS onset. These VNS configurations were applied to 6 healthy, anesthetized sheep, while acquiring the associated cardiovascular response. Unobserved VNS configurations were estimated using a Gaussian process regression (GPR model. In order to quantitatively analyze the effect of each parameter and their combinations on the cardiac response, the Sobol sensitivity method was applied to the obtained GPR model and inter-individual sensitivity markers were estimated using a bootstrap approach. Results highlight the dominant effect of pulse current, pulse width and number of pulses, which explain respectively 49.4%, 19.7% and 6.0% of the mean global cardiovascular variability provoked by VNS. More interestingly, results also quantify the effect of the interactions between VNS parameters. In particular, the interactions between current and pulse width provoke higher cardiac effects than the changes on the number of pulses alone (between 6 and 25% of the variability. Although the sensitivity of individual VNS parameters seems similar for chronotropic, dromotropic and inotropic responses, the interacting effects of VNS parameters
Parameter Estimates in Differential Equation Models for Chemical Kinetics
Winkel, Brian
2011-01-01
We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…
Kim, Gun; Kim, Jin-Yeon; Kurtis, Kimberly E.; Jacobs, Laurence J.
2015-03-01
This research experimentally investigates the sensitivity of the acoustic nonlinearity parameter to microcracks in cement-based materials. Based on the second harmonic generation (SHG) technique, an experimental setup using non-contact, air-coupled detection is used to receive the consistent Rayleigh surface waves. To induce variations in the extent of microscale cracking in two types of specimens (concrete and mortar), shrinkage reducing admixture (SRA), is used in one set, while a companion specimen is prepared without SRA. A 50 kHz wedge transducer and a 100 kHz air-coupled transducer are implemented for the generation and detection of nonlinear Rayleigh waves. It is shown that the air-coupled detection method provides more repeatable fundamental and second harmonic amplitudes of the propagating Rayleigh waves. The obtained amplitudes are then used to calculate the relative nonlinearity parameter βre, the ratio of the second harmonic amplitude to the square of the fundamental amplitude. The experimental results clearly demonstrate that the nonlinearity parameter (βre) is highly sensitive to the microstructural changes in cement-based materials than the Rayleigh phase velocity and attenuation and that SRA has great potential to avoid shrinkage cracking in cement-based materials.
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Delaram Houshmand Kouchi
2017-05-01
Full Text Available The successful application of hydrological models relies on careful calibration and uncertainty analysis. However, there are many different calibration/uncertainty analysis algorithms, and each could be run with different objective functions. In this paper, we highlight the fact that each combination of optimization algorithm-objective functions may lead to a different set of optimum parameters, while having the same performance; this makes the interpretation of dominant hydrological processes in a watershed highly uncertain. We used three different optimization algorithms (SUFI-2, GLUE, and PSO, and eight different objective functions (R2, bR2, NSE, MNS, RSR, SSQR, KGE, and PBIAS in a SWAT model to calibrate the monthly discharges in two watersheds in Iran. The results show that all three algorithms, using the same objective function, produced acceptable calibration results; however, with significantly different parameter ranges. Similarly, an algorithm using different objective functions also produced acceptable calibration results, but with different parameter ranges. The different calibrated parameter ranges consequently resulted in significantly different water resource estimates. Hence, the parameters and the outputs that they produce in a calibrated model are “conditioned” on the choices of the optimization algorithm and objective function. This adds another level of non-negligible uncertainty to watershed models, calling for more attention and investigation in this area.
Modelling survival: exposure pattern, species sensitivity and uncertainty.
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.
Study on Parameters Modeling of Wind Turbines Using SCADA Data
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Yonglong YAN
2014-08-01
Full Text Available Taking the advantage of the current massive monitoring data from Supervisory Control and Data Acquisition (SCADA system of wind farm, it is of important significance for anomaly detection, early warning and fault diagnosis to build the data model of state parameters of wind turbines (WTs. The operational conditions and the relationships between the state parameters of wind turbines are complex. It is difficult to establish the model of state parameter accurately, and the modeling method of state parameters of wind turbines considering parameter selection is proposed. Firstly, by analyzing the characteristic of SCADA data, a reasonable range of data and monitoring parameters are chosen. Secondly, neural network algorithm is adapted, and the selection method of input parameters in the model is presented. Generator bearing temperature and cooling air temperature are regarded as target parameters, and the two models are built and input parameters of the models are selected, respectively. Finally, the parameter selection method in this paper and the method using genetic algorithm-partial least square (GA-PLS are analyzed comparatively, and the results show that the proposed methods are correct and effective. Furthermore, the modeling of two parameters illustrate that the method in this paper can applied to other state parameters of wind turbines.
Sensitivity of risk parameters to human errors in reactor safety study for a PWR
International Nuclear Information System (INIS)
Samanta, P.K.; Hall, R.E.; Swoboda, A.L.
1981-01-01
Sensitivities of the risk parameters, emergency safety system unavailabilities, accident sequence probabilities, release category probabilities and core melt probability were investigated for changes in the human error rates within the general methodological framework of the Reactor Safety Study (RSS) for a Pressurized Water Reactor (PWR). Impact of individual human errors were assessed both in terms of their structural importance to core melt and reliability importance on core melt probability. The Human Error Sensitivity Assessment of a PWR (HESAP) computer code was written for the purpose of this study. The code employed point estimate approach and ignored the smoothing technique applied in RSS. It computed the point estimates for the system unavailabilities from the median values of the component failure rates and proceeded in terms of point values to obtain the point estimates for the accident sequence probabilities, core melt probability, and release category probabilities. The sensitivity measure used was the ratio of the top event probability before and after the perturbation of the constituent events. Core melt probability per reactor year showed significant increase with the increase in the human error rates, but did not show similar decrease with the decrease in the human error rates due to the dominance of the hardware failures. When the Minimum Human Error Rate (M.H.E.R.) used is increased to 10 -3 , the base case human error rates start sensitivity to human errors. This effort now allows the evaluation of new error rate data along with proposed changes in the man machine interface
The Effects of Uncertainty in Speed-Flow Curve Parameters on a Large-Scale Model
DEFF Research Database (Denmark)
Manzo, Stefano; Nielsen, Otto Anker; Prato, Carlo Giacomo
2014-01-01
-delay functions express travel time as a function of traffic flows and the theoretical capacity of the modeled facility. The U.S. Bureau of Public Roads (BPR) formula is one of the most extensively applied volume delay functions in practice. This study investigated uncertainty in the BPR parameters. Initially......-stage Danish national transport model. The results clearly highlight the importance to modeling purposes of taking into account BPR formula parameter uncertainty, expressed as a distribution of values rather than assumed point values. Indeed, the model output demonstrates a noticeable sensitivity to parameter...
A Sensitivity Analysis of fMRI Balloon Model
Zayane, Chadia
2015-04-22
Functional magnetic resonance imaging (fMRI) allows the mapping of the brain activation through measurements of the Blood Oxygenation Level Dependent (BOLD) contrast. The characterization of the pathway from the input stimulus to the output BOLD signal requires the selection of an adequate hemodynamic model and the satisfaction of some specific conditions while conducting the experiment and calibrating the model. This paper, focuses on the identifiability of the Balloon hemodynamic model. By identifiability, we mean the ability to estimate accurately the model parameters given the input and the output measurement. Previous studies of the Balloon model have somehow added knowledge either by choosing prior distributions for the parameters, freezing some of them, or looking for the solution as a projection on a natural basis of some vector space. In these studies, the identification was generally assessed using event-related paradigms. This paper justifies the reasons behind the need of adding knowledge, choosing certain paradigms, and completing the few existing identifiability studies through a global sensitivity analysis of the Balloon model in the case of blocked design experiment.
A Sensitivity Analysis of fMRI Balloon Model
Zayane, Chadia; Laleg-Kirati, Taous-Meriem
2015-01-01
Functional magnetic resonance imaging (fMRI) allows the mapping of the brain activation through measurements of the Blood Oxygenation Level Dependent (BOLD) contrast. The characterization of the pathway from the input stimulus to the output BOLD signal requires the selection of an adequate hemodynamic model and the satisfaction of some specific conditions while conducting the experiment and calibrating the model. This paper, focuses on the identifiability of the Balloon hemodynamic model. By identifiability, we mean the ability to estimate accurately the model parameters given the input and the output measurement. Previous studies of the Balloon model have somehow added knowledge either by choosing prior distributions for the parameters, freezing some of them, or looking for the solution as a projection on a natural basis of some vector space. In these studies, the identification was generally assessed using event-related paradigms. This paper justifies the reasons behind the need of adding knowledge, choosing certain paradigms, and completing the few existing identifiability studies through a global sensitivity analysis of the Balloon model in the case of blocked design experiment.
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Gesine Flehmig
Full Text Available In obesity, elevated fat mass and ectopic fat accumulation are associated with changes in adipokine secretion, which may link obesity to inflammation and the development of insulin resistance. However, relationships among individual adipokines and between adipokines and parameters of obesity, glucose metabolism or inflammation are largely unknown. Serum concentrations of 20 adipokines were measured in 141 Caucasian obese men (n = 67 and women (n = 74 with a wide range of body weight, glycemia and insulin sensitivity. Unbiased, distance-based hierarchical cluster analyses were performed to recognize patterns among adipokines and their relationship with parameters of obesity, glucose metabolism, insulin sensitivity and inflammation. We identified two major adipokine clusters related to either (1 body fat mass and inflammation (leptin, ANGPTL3, DLL1, chemerin, Nampt, resistin or insulin sensitivity/hyperglycemia, and lipid metabolism (vaspin, clusterin, glypican 4, progranulin, ANGPTL6, GPX3, RBP4, DLK1, SFRP5, BMP7, adiponectin, CTRP3 and 5, omentin. In addition, we found distinct adipokine clusters in subgroups of patients with or without type 2 diabetes (T2D. Logistic regression analyses revealed ANGPTL6, DLK1, Nampt and progranulin as strongest adipokine correlates of T2D in obese individuals. The panel of 20 adipokines predicted T2D compared to a combination of HbA1c, HOMA-IR and fasting plasma glucose with lower sensitivity (78% versus 91% and specificity (76% versus 94%. Therefore, adipokine patterns may currently not be clinically useful for the diagnosis of metabolic diseases. Whether adipokine patterns are relevant for the predictive assessment of intervention outcomes needs to be further investigated.
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Yun-ah Han
2013-03-01
Full Text Available The effects of structural design parameters on the performance of nano-replicated photonic crystal (PC label-free biosensors were examined by the analysis of simulated reflection spectra of PC structures. The grating pitch, duty, scaled grating height and scaled TiO2 layer thickness were selected as the design factors to optimize the PC structure. The peak wavelength value (PWV, full width at half maximum of the peak, figure of merit for the bulk and surface sensitivities, and surface/bulk sensitivity ratio were also selected as the responses to optimize the PC label-free biosensor performance. A parametric study showed that the grating pitch was the dominant factor for PWV, and that it had low interaction effects with other scaled design factors. Therefore, we can isolate the effect of grating pitch using scaled design factors. For the design of PC-label free biosensor, one should consider that: (1 the PWV can be measured by the reflection peak measurement instruments, (2 the grating pitch and duty can be manufactured using conventional lithography systems, and (3 the optimum design is less sensitive to the grating height and TiO2 layer thickness variations in the fabrication process. In this paper, we suggested a design guide for highly sensitive PC biosensor in which one select the grating pitch and duty based on the limitations of the lithography and measurement system, and conduct a multi objective optimization of the grating height and TiO2 layer thickness for maximizing performance and minimizing the influence of parameter variation. Through multi-objective optimization of a PC structure with a fixed grating height of 550 nm and a duty of 50%, we obtained a surface FOM of 66.18 RIU−1 and an S/B ratio of 34.8%, with a grating height of 117 nm and TiO2 height of 210 nm.
Ju, Jonghyun; Han, Yun-ah; Kim, Seok-min
2013-03-07
The effects of structural design parameters on the performance of nano-replicated photonic crystal (PC) label-free biosensors were examined by the analysis of simulated reflection spectra of PC structures. The grating pitch, duty, scaled grating height and scaled TiO2 layer thickness were selected as the design factors to optimize the PC structure. The peak wavelength value (PWV), full width at half maximum of the peak, figure of merit for the bulk and surface sensitivities, and surface/bulk sensitivity ratio were also selected as the responses to optimize the PC label-free biosensor performance. A parametric study showed that the grating pitch was the dominant factor for PWV, and that it had low interaction effects with other scaled design factors. Therefore, we can isolate the effect of grating pitch using scaled design factors. For the design of PC-label free biosensor, one should consider that: (1) the PWV can be measured by the reflection peak measurement instruments, (2) the grating pitch and duty can be manufactured using conventional lithography systems, and (3) the optimum design is less sensitive to the grating height and TiO2 layer thickness variations in the fabrication process. In this paper, we suggested a design guide for highly sensitive PC biosensor in which one select the grating pitch and duty based on the limitations of the lithography and measurement system, and conduct a multi objective optimization of the grating height and TiO2 layer thickness for maximizing performance and minimizing the influence of parameter variation. Through multi-objective optimization of a PC structure with a fixed grating height of 550 nm and a duty of 50%, we obtained a surface FOM of 66.18 RIU-1 and an S/B ratio of 34.8%, with a grating height of 117 nm and TiO2 height of 210 nm.
Romano, N.; Petroselli, A.; Grimaldi, S.
2012-04-01
With the aim of combining the practical advantages of the Soil Conservation Service - Curve Number (SCS-CN) method and Green-Ampt (GA) infiltration model, we have developed a mixed procedure, which is referred to as CN4GA (Curve Number for Green-Ampt). The basic concept is that, for a given storm, the computed SCS-CN total net rainfall amount is used to calibrate the soil hydraulic conductivity parameter of the Green-Ampt model so as to distribute in time the information provided by the SCS-CN method. In a previous contribution, the proposed mixed procedure was evaluated on 100 observed events showing encouraging results. In this study, a sensitivity analysis is carried out to further explore the feasibility of applying the CN4GA tool in small ungauged catchments. The proposed mixed procedure constrains the GA model with boundary and initial conditions so that the GA soil hydraulic parameters are expected to be insensitive toward the net hyetograph peak. To verify and evaluate this behaviour, synthetic design hyetograph and synthetic rainfall time series are selected and used in a Monte Carlo analysis. The results are encouraging and confirm that the parameter variability makes the proposed method an appropriate tool for hydrologic predictions in ungauged catchments. Keywords: SCS-CN method, Green-Ampt method, rainfall excess, ungauged basins, design hydrograph, rainfall-runoff modelling.
The impact of Ag nanoparticles on the parameters of DSS- cells sensitized by Z907
International Nuclear Information System (INIS)
Ibrayev, N Kh; Aimukhanov, A K; Zeinidenov, A K
2016-01-01
Research of influence of Ag nanoparticles are in-process undertaken on absorption and on parameters CVC DSS-cells sensitized Z907. It is set that with the height of concentration Ag nanoparticles in tape to the concentration of 0.3% wt%. the absorbance of Z907 in a short-wave stripe grew to the value 1,6. It is set that under reaching the concentration of Ag nanoparticles in the cell of value the 0.3% wt%. efficiency of cell increased to 2.2%. (paper)
International Nuclear Information System (INIS)
Amorim, E.S. do; D'Oliveira, A.B.; Galvao, O.B.; Oyama, K.
1981-03-01
Sensitivity of control times to variation of a thermal reactor core parameters is defined by suitable changes in the power coefficient, core size and fuel enrichment. A control strategy is developed based on control theory concepts and on considerations of the physics of the problem. Digital diffusion theory simulation is described which tends to verify the control concepts considered, face dumped oscillations introduced in one thermal nuclear power system. The effectivity of the control actions, in terms of eliminating oscillations, provided guidelines for the working-group engaged in the analysis of the control rods and its optimal performance. (Author) [pt
International Nuclear Information System (INIS)
Gvildys, J.
1985-01-01
A sensitivity study of the HCDA slug impact response of fast reactor primary containment to properties of core surrounding structures was performed. Parameters such as the strength of the radial shield material, mass, void, and compressibility properties of the gas plenum material, mass of core material, and mass and compressibility properties of the coolant were used as variables to determine the magnitude of the slug impact loads. The response of the reactor primary containment and the partition of energy were also given. A study was also performed using water as coolant to study the difference in slug impact loads
Structure and sensitivity analysis of individual-based predator–prey models
International Nuclear Information System (INIS)
Imron, Muhammad Ali; Gergs, Andre; Berger, Uta
2012-01-01
The expensive computational cost of sensitivity analyses has hampered the use of these techniques for analysing individual-based models in ecology. A relatively cheap computational cost, referred to as the Morris method, was chosen to assess the relative effects of all parameters on the model’s outputs and to gain insights into predator–prey systems. Structure and results of the sensitivity analysis of the Sumatran tiger model – the Panthera Population Persistence (PPP) and the Notonecta foraging model (NFM) – were compared. Both models are based on a general predation cycle and designed to understand the mechanisms behind the predator–prey interaction being considered. However, the models differ significantly in their complexity and the details of the processes involved. In the sensitivity analysis, parameters that directly contribute to the number of prey items killed were found to be most influential. These were the growth rate of prey and the hunting radius of tigers in the PPP model as well as attack rate parameters and encounter distance of backswimmers in the NFM model. Analysis of distances in both of the models revealed further similarities in the sensitivity of the two individual-based models. The findings highlight the applicability and importance of sensitivity analyses in general, and screening design methods in particular, during early development of ecological individual-based models. Comparison of model structures and sensitivity analyses provides a first step for the derivation of general rules in the design of predator–prey models for both practical conservation and conceptual understanding. - Highlights: ► Structure of predation processes is similar in tiger and backswimmer model. ► The two individual-based models (IBM) differ in space formulations. ► In both models foraging distance is among the sensitive parameters. ► Morris method is applicable for the sensitivity analysis even of complex IBMs.
Sensitivity Analysis of Biome-Bgc Model for Dry Tropical Forests of Vindhyan Highlands, India
Kumar, M.; Raghubanshi, A. S.
2011-08-01
A process-based model BIOME-BGC was run for sensitivity analysis to see the effect of ecophysiological parameters on net primary production (NPP) of dry tropical forest of India. The sensitivity test reveals that the forest NPP was highly sensitive to the following ecophysiological parameters: Canopy light extinction coefficient (k), Canopy average specific leaf area (SLA), New stem C : New leaf C (SC:LC), Maximum stomatal conductance (gs,max), C:N of fine roots (C:Nfr), All-sided to projected leaf area ratio and Canopy water interception coefficient (Wint). Therefore, these parameters need more precision and attention during estimation and observation in the field studies.
Mixing-model Sensitivity to Initial Conditions in Hydrodynamic Predictions
Bigelow, Josiah; Silva, Humberto; Truman, C. Randall; Vorobieff, Peter
2017-11-01
Amagat and Dalton mixing-models were studied to compare their thermodynamic prediction of shock states. Numerical simulations with the Sandia National Laboratories shock hydrodynamic code CTH modeled University of New Mexico (UNM) shock tube laboratory experiments shocking a 1:1 molar mixture of helium (He) and sulfur hexafluoride (SF6) . Five input parameters were varied for sensitivity analysis: driver section pressure, driver section density, test section pressure, test section density, and mixture ratio (mole fraction). We show via incremental Latin hypercube sampling (LHS) analysis that significant differences exist between Amagat and Dalton mixing-model predictions. The differences observed in predicted shock speeds, temperatures, and pressures grow more pronounced with higher shock speeds. Supported by NNSA Grant DE-0002913.
Marković, D.; Koch, M.
2005-09-01
The influence of the periodic signals in time series on the Hurst parameter estimate is investigated with temporal, spectral and time-scale methods. The Hurst parameter estimates of the simulated periodic time series with a white noise background show a high sensitivity on the signal to noise ratio and for some methods, also on the data length used. The analysis is then carried on to the investigation of extreme monthly river flows of the Elbe River (Dresden) and of the Rhine River (Kaub). Effects of removing the periodic components employing different filtering approaches are discussed and it is shown that such procedures are a prerequisite for an unbiased estimation of H. In summary, our results imply that the first step in a time series long-correlation study should be the separation of the deterministic components from the stochastic ones. Otherwise wrong conclusions concerning possible memory effects may be drawn.
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)
Improving weather predictability by including land-surface model parameter uncertainty
Orth, Rene; Dutra, Emanuel; Pappenberger, Florian
2016-04-01
The land surface forms an important component of Earth system models and interacts nonlinearly with other parts such as ocean and atmosphere. To capture the complex and heterogenous hydrology of the land surface, land surface models include a large number of parameters impacting the coupling to other components of the Earth system model. Focusing on ECMWF's land-surface model HTESSEL we present in this study a comprehensive parameter sensitivity evaluation using multiple observational datasets in Europe. We select 6 poorly constrained effective parameters (surface runoff effective depth, skin conductivity, minimum stomatal resistance, maximum interception, soil moisture stress function shape, total soil depth) and explore their sensitivity to model outputs such as soil moisture, evapotranspiration and runoff using uncoupled simulations and coupled seasonal forecasts. Additionally we investigate the possibility to construct ensembles from the multiple land surface parameters. In the uncoupled runs we find that minimum stomatal resistance and total soil depth have the most influence on model performance. Forecast skill scores are moreover sensitive to the same parameters as HTESSEL performance in the uncoupled analysis. We demonstrate the robustness of our findings by comparing multiple best performing parameter sets and multiple randomly chosen parameter sets. We find better temperature and precipitation forecast skill with the best-performing parameter perturbations demonstrating representativeness of model performance across uncoupled (and hence less computationally demanding) and coupled settings. Finally, we construct ensemble forecasts from ensemble members derived with different best-performing parameterizations of HTESSEL. This incorporation of parameter uncertainty in the ensemble generation yields an increase in forecast skill, even beyond the skill of the default system. Orth, R., E. Dutra, and F. Pappenberger, 2016: Improving weather predictability by
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.
DEFF Research Database (Denmark)
Malaguerra, Flavio; Chambon, Julie Claire Claudia; Bjerg, Poul Løgstrup
2011-01-01
experiments of complete trichloroethene (TCE) degradation in natural sediments. Global sensitivity analysis was performed using the Morris method and Sobol sensitivity indices to identify the most influential model parameters. Results show that the sulfate concentration and fermentation kinetics are the most...
Parameter Optimisation for the Behaviour of Elastic Models over Time
DEFF Research Database (Denmark)
Mosegaard, Jesper
2004-01-01
Optimisation of parameters for elastic models is essential for comparison or finding equivalent behaviour of elastic models when parameters cannot simply be transferred or converted. This is the case with a large range of commonly used elastic models. In this paper we present a general method tha...
An automatic and effective parameter optimization method for model tuning
Directory of Open Access Journals (Sweden)
T. Zhang
2015-11-01
simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.
Good Models Gone Bad: Quantifying and Predicting Parameter-Induced Climate Model Simulation Failures
Lucas, D. D.; Klein, R.; Tannahill, J.; Brandon, S.; Covey, C. C.; Domyancic, D.; Ivanova, D. P.
2012-12-01
Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Statistical analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation failures of the Parallel Ocean Program (POP2). About 8.5% of our POP2 runs failed for numerical reasons at certain combinations of parameter values. We apply support vector machine (SVM) classification from the fields of pattern recognition and machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. The SVM classifiers readily predict POP2 failures in an independent validation ensemble, and are subsequently used to determine the causes of the failures via a global sensitivity analysis. Four parameters related to ocean mixing and viscosity are identified as the major sources of POP2 failures. Our method can be used to improve the robustness of complex scientific models to parameter perturbations and to better steer UQ ensembles. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).
GEMSFITS: Code package for optimization of geochemical model parameters and inverse modeling
International Nuclear Information System (INIS)
Miron, George D.; Kulik, Dmitrii A.; Dmytrieva, Svitlana V.; Wagner, Thomas
2015-01-01
Highlights: • Tool for generating consistent parameters against various types of experiments. • Handles a large number of experimental data and parameters (is parallelized). • Has a graphical interface and can perform statistical analysis on the parameters. • Tested on fitting the standard state Gibbs free energies of aqueous Al species. • Example on fitting interaction parameters of mixing models and thermobarometry. - Abstract: GEMSFITS is a new code package for fitting internally consistent input parameters of GEM (Gibbs Energy Minimization) geochemical–thermodynamic models against various types of experimental or geochemical data, and for performing inverse modeling tasks. It consists of the gemsfit2 (parameter optimizer) and gfshell2 (graphical user interface) programs both accessing a NoSQL database, all developed with flexibility, generality, efficiency, and user friendliness in mind. The parameter optimizer gemsfit2 includes the GEMS3K chemical speciation solver ( (http://gems.web.psi.ch/GEMS3K)), which features a comprehensive suite of non-ideal activity- and equation-of-state models of solution phases (aqueous electrolyte, gas and fluid mixtures, solid solutions, (ad)sorption. The gemsfit2 code uses the robust open-source NLopt library for parameter fitting, which provides a selection between several nonlinear optimization algorithms (global, local, gradient-based), and supports large-scale parallelization. The gemsfit2 code can also perform comprehensive statistical analysis of the fitted parameters (basic statistics, sensitivity, Monte Carlo confidence intervals), thus supporting the user with powerful tools for evaluating the quality of the fits and the physical significance of the model parameters. The gfshell2 code provides menu-driven setup of optimization options (data selection, properties to fit and their constraints, measured properties to compare with computed counterparts, and statistics). The practical utility, efficiency, and
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
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
Identifying the connective strength between model parameters and performance criteria
Directory of Open Access Journals (Sweden)
B. Guse
2017-11-01
Full Text Available In hydrological models, parameters are used to represent the time-invariant characteristics of catchments and to capture different aspects of hydrological response. Hence, model parameters need to be identified based on their role in controlling the hydrological behaviour. For the identification of meaningful parameter values, multiple and complementary performance criteria are used that compare modelled and measured discharge time series. The reliability of the identification of hydrologically meaningful model parameter values depends on how distinctly a model parameter can be assigned to one of the performance criteria. To investigate this, we introduce the new concept of connective strength between model parameters and performance criteria. The connective strength assesses the intensity in the interrelationship between model parameters and performance criteria in a bijective way. In our analysis of connective strength, model simulations are carried out based on a latin hypercube sampling. Ten performance criteria including Nash–Sutcliffe efficiency (NSE, Kling–Gupta efficiency (KGE and its three components (alpha, beta and r as well as RSR (the ratio of the root mean square error to the standard deviation for different segments of the flow duration curve (FDC are calculated. With a joint analysis of two regression tree (RT approaches, we derive how a model parameter is connected to different performance criteria. At first, RTs are constructed using each performance criterion as the target variable to detect the most relevant model parameters for each performance criterion. Secondly, RTs are constructed using each parameter as the target variable to detect which performance criteria are impacted by changes in the values of one distinct model parameter. Based on this, appropriate performance criteria are identified for each model parameter. In this study, a high bijective connective strength between model parameters and performance criteria
Wentworth, Mami Tonoe
techniques for model calibration. For Bayesian model calibration, we employ adaptive Metropolis algorithms to construct densities for input parameters in the heat model and the HIV model. To quantify the uncertainty in the parameters, we employ two MCMC algorithms: Delayed Rejection Adaptive Metropolis (DRAM) [33] and Differential Evolution Adaptive Metropolis (DREAM) [66, 68]. The densities obtained using these methods are compared to those obtained through the direct numerical evaluation of the Bayes' formula. We also combine uncertainties in input parameters and measurement errors to construct predictive estimates for a model response. A significant emphasis is on the development and illustration of techniques to verify the accuracy of sampling-based Metropolis algorithms. We verify the accuracy of DRAM and DREAM by comparing chains, densities and correlations obtained using DRAM, DREAM and the direct evaluation of Bayes formula. We also perform similar analysis for credible and prediction intervals for responses. Once the parameters are estimated, we employ energy statistics test [63, 64] to compare the densities obtained by different methods for the HIV model. The energy statistics are used to test the equality of distributions. We also consider parameter selection and verification techniques for models having one or more parameters that are noninfluential in the sense that they minimally impact model outputs. We illustrate these techniques for a dynamic HIV model but note that the parameter selection and verification framework is applicable to a wide range of biological and physical models. To accommodate the nonlinear input to output relations, which are typical for such models, we focus on global sensitivity analysis techniques, including those based on partial correlations, Sobol indices based on second-order model representations, and Morris indices, as well as a parameter selection technique based on standard errors. A significant objective is to provide
Sensitivity analysis of Takagi-Sugeno-Kang rainfall-runoff fuzzy models
Directory of Open Access Journals (Sweden)
A. P. Jacquin
2009-01-01
Full Text Available This paper is concerned with the sensitivity analysis of the model parameters of the Takagi-Sugeno-Kang fuzzy rainfall-runoff models previously developed by the authors. These models are classified in two types of fuzzy models, where the first type is intended to account for the effect of changes in catchment wetness and the second type incorporates seasonality as a source of non-linearity. The sensitivity analysis is performed using two global sensitivity analysis methods, namely Regional Sensitivity Analysis and Sobol's variance decomposition. The data of six catchments from different geographical locations and sizes are used in the sensitivity analysis. The sensitivity of the model parameters is analysed in terms of several measures of goodness of fit, assessing the model performance from different points of view. These measures include the Nash-Sutcliffe criteria, volumetric errors and peak errors. The results show that the sensitivity of the model parameters depends on both the catchment type and the measure used to assess the model performance.
Techno-economic sensitivity study of heliostat field parameters for micro-gas turbine CSP
Landman, Willem A.; Gauché, Paul; Dinter, Frank; Myburgh, J. T.
2017-06-01
Concentrating solar power systems based on micro-gas turbines potentially offer numerous benefits should they become commercially viable. Heliostat fields for such systems have unique requirements in that the number of heliostats and the focal ratios are typically much lower than conventional central receiver systems. This paper presents a techno-economic sensitivity study of heliostat field parameters for a micro-gas turbine central receiver system. A 100 kWe minitower system is considered for the base case and a one-at-a-time strategy is used to investigate parameter sensitivities. Increasing heliostat focal ratios are found to have significant optical performance benefits due to both a reduction in astigmatic aberrations and a reduction in the number of facet focal lengths required; confirming the hypothesis that smaller heliostats offer a techno-economic advantage. Fixed Horizontal Axis tracking mechanism is shown to outperform the conventional Azimuth Zenith tracking mechanism in high density heliostat fields. Although several improvements to heliostat field performance are discussed, the capex fraction of the heliostat field for such system is shown to be almost half that of a conventional central receiver system and optimum utilization of the higher capex components, namely; the receiver and turbine subsystems, are more rewarding than that of the heliostat field.
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.
The application of sensitivity analysis to models of large scale physiological systems
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.
Sensitivity analysis of the noble gas transport and fate model: CASCADR9
International Nuclear Information System (INIS)
Lindstrom, F.T.; Cawlfield, D.E.; Barker, L.E.
1994-03-01
CASCADR9 is a desert alluvial soil site-specific noble gas transport and fate model. Input parameters for CASCADR9 are: man-made source term, background concentration of radionuclides, radon half-life, soil porosity, period of barometric pressure wave, amplitude of barometric pressure wave, and effective eddy diffusivity. Using average flux, total flow, and radon concentration at the 40 day mark as output parameters, a sensitivity analysis for CASCADR9 is carried out, under a variety of scenarios. For each scenario, the parameter to which output parameters are most sensitive are identified
Resuspension parameters for TRAC dispersion model
International Nuclear Information System (INIS)
Langer, G.
1987-01-01
Resuspension factors for the wind erosion of soil contaminated with plutonium are necessary to run the Rocky Flats Plant Terrain Responsive Atmospheric Code (TRAC). The model predicts the dispersion and resulting population dose due to accidental plutonium releases
Shin, J.; Kim, K.-H.; Lee, K.-K.
2012-04-01
Sea level rise, which is one of the representative phenomena of climate changes caused by global warming, can affect groundwater system. The rising trend of the sea level caused by the global warming is reported to be about 3 mm/year for the most recent 10 year average (IPCC, 2007). The rate of sea level rise around the Korean peninsula is reported to be 2.30±2.22 mm/yr during the 1960-1999 period (Cho, 2002) and 2.16±1.77 mm/yr (Kim et al., 2009) during the 1968-2007 period. Both of these rates are faster than the 1.8±0.5 mm/yr global average for the similar 1961-2003 period (IPCC, 2007). In this study, we analyzed changes in the groundwater environment affected by the sea level rise by using an analytical methodology. We tried to find the most effective parameters of groundwater amount change in order to estimate the change in fresh water amount in coastal groundwater. A hypothetical island model of a cylindrical shape in considered. The groundwater storage change is bi-directional as the sea level rises according to the natural and hydrogeological conditions. Analysis of the computation results shows that topographic slope and hydraulic conductivity are the most sensitive factors. The contributions of the groundwater recharge rate and the thickness of aquifer below sea level are relatively less effective. In the island with steep seashore slopes larger than 1~2 degrees or so, the storage amount of fresh water in a coastal area increases as sea level rises. On the other hand, when sea level drops, the storage amount decreases. This is because the groundwater level also rises with the rising sea level in steep seashores. For relatively flat seashores, where the slope is smaller than around 1-2 degrees, the storage amount of coastal fresh water decreases when the sea level rises because the area flooded by the rising sea water is increased. The volume of aquifer fresh water in this circumstance is greatly reduced in proportion to the flooded area with the sea
Parameter Sensitivity of Shallow-Bias Tunnel with a Clear Distance Located in Rock
Directory of Open Access Journals (Sweden)
Xueliang Jiang
2018-01-01
Full Text Available In order to obtain the seismic internal force response laws of a shallow-bias tunnel with a small clear distance, the reliability of the numerical simulation is verified by the shaking table model test. The parameter sensitivity of the tunnel is studied by using MIDAS-NX finite element software. The effects of seismic wave peak (0.1 g, 0.2 g, 0.3 g, 0.4 g, 0.5 g, and 0.6 g, existing slope angle (30°, 45°, 60°, and 90°, clear distance (1.0 D, 1.5 D, 2.0 D, and 3.0 D, and excitation mode (X direction, Z direction, XY direction, and XYZ direction on the internal force response law of the tunnel are studied, respectively. The results show that (1 the shear force gradually increases with the increasing of seismic peak. The amplification is different with different measuring points. (2 Under different existing slope-angle conditions, the variation trend of shear force of the tunnel is similar, but the shear force is different. The existing slope has significant effect on the shear force response of the tunnel, and the degree is different with different slope angles. (3 Under the conditions of 1.5 D and 2.0 D, the shear force response of the tunnel is stronger, but the response of other conditions is relatively weak. The tunnel with 1.5 D to 2.0 D clear distance should be avoided. Different excitation modes have a significant effect on the shear force response of the tunnel. (4 Under the same excitation mode, the different excitation directions also have a significant effect on the shear force response. (5 The shear force response of the tunnel crosssection shows nonlinear variation trend. The shear force response is strongest at the arch shoulder and arch foot of the tunnel. The research results provide a useful reference for the design of antishock and vibration resistance of the tunnel.
Directory of Open Access Journals (Sweden)
Jonathan R Karr
2015-05-01
Full Text Available Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.
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.
A sensitivity analysis for a thermomechanical model of the Antarctic ice sheet and ice shelves
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
A reactive transport model for mercury fate in contaminated soil--sensitivity analysis.
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.
Computational modeling and sensitivity in uniform DT burn
International Nuclear Information System (INIS)
Hansen, Jon; Hryniw, Natalia; Kesler, Leigh A.; Li, Frank; Vold, Erik
2010-01-01
Understanding deuterium-tritium (DT) fusion is essential to achieving ignition in inertial confinement fusion. A burning DT plasma in a three temperature (3T) approximation and uniform in space is modeled as a system of five non-linear coupled ODEs. Special focus is given to the effects of Compton coupling, Planck opacity, and electron-ion coupling terms. Semi-implicit differencing is used to solve the system of equations. Time step size is varied to examine the stability and convergence of each solution. Data from NDI, SESAME, and TOPS databases is extracted to create analytic fits for the reaction rate parameter, the Planck opacity, and the coupling frequencies of the plasma temperatures. The impact of different high order fits to NDI date (the reaction rate parameter), and using TOPS versus SESAME opacity data is explored, and the sensitivity to several physics parameters in the coupling terms are also examined. The base model recovers the accepted 3T results for the temperature and burn histories. The Compton coupling is found to have a significant impact on the results. Varying a coefficient of this term shows that the model results can give reasonably good agreement with the peak temperatures reported in multi-group results as well as the accepted 3T results. The base model assumes a molar density of 1 mol/cm 3 , as well as a 5 keV intial temperature for all three temperatures. Different intial conditions are explored as well. Intial temperatures are set to 1 and 3 keV, the ratio of D to T is varied (2 and 3 as opposed to 1 in the base model), and densities are set to 10 mol/cm 3 and 100 mol/cm 3 . Again varying the Compton coefficient, the ion temperature results in the higher density case are in reasonable agreement with a recently published kinetic model.
Computational modeling and sensitivity in uniform DT burn
Energy Technology Data Exchange (ETDEWEB)
Hansen, Jon [Los Alamos National Laboratory; Hryniw, Natalia [Los Alamos National Laboratory; Kesler, Leigh A [Los Alamos National Laboratory; Li, Frank [Los Alamos National Laboratory; Vold, Erik [Los Alamos National Laboratory
2010-01-01
Understanding deuterium-tritium (DT) fusion is essential to achieving ignition in inertial confinement fusion. A burning DT plasma in a three temperature (3T) approximation and uniform in space is modeled as a system of five non-linear coupled ODEs. Special focus is given to the effects of Compton coupling, Planck opacity, and electron-ion coupling terms. Semi-implicit differencing is used to solve the system of equations. Time step size is varied to examine the stability and convergence of each solution. Data from NDI, SESAME, and TOPS databases is extracted to create analytic fits for the reaction rate parameter, the Planck opacity, and the coupling frequencies of the plasma temperatures. The impact of different high order fits to NDI date (the reaction rate parameter), and using TOPS versus SESAME opacity data is explored, and the sensitivity to several physics parameters in the coupling terms are also examined. The base model recovers the accepted 3T results for the temperature and burn histories. The Compton coupling is found to have a significant impact on the results. Varying a coefficient of this term shows that the model results can give reasonably good agreement with the peak temperatures reported in multi-group results as well as the accepted 3T results. The base model assumes a molar density of 1 mol/cm{sup 3}, as well as a 5 keV intial temperature for all three temperatures. Different intial conditions are explored as well. Intial temperatures are set to 1 and 3 keV, the ratio of D to T is varied (2 and 3 as opposed to 1 in the base model), and densities are set to 10 mol/cm{sup 3} and 100 mol/cm{sup 3}. Again varying the Compton coefficient, the ion temperature results in the higher density case are in reasonable agreement with a recently published kinetic model.
Directory of Open Access Journals (Sweden)
Steffi Kopprasch
Full Text Available Glucolipotoxicity is a major pathophysiological mechanism in the development of insulin resistance and type 2 diabetes mellitus (T2D. We aimed to detect subtle changes in the circulating lipid profile by shotgun lipidomics analyses and to associate them with four different insulin sensitivity indices.The cross-sectional study comprised 90 men with a broad range of insulin sensitivity including normal glucose tolerance (NGT, n = 33, impaired glucose tolerance (IGT, n = 32 and newly detected T2D (n = 25. Prior to oral glucose challenge plasma was obtained and quantitatively analyzed for 198 lipid molecular species from 13 different lipid classes including triacylglycerls (TAGs, phosphatidylcholine plasmalogen/ether (PC O-s, sphingomyelins (SMs, and lysophosphatidylcholines (LPCs. To identify a lipidomic signature of individual insulin sensitivity we applied three data mining approaches, namely least absolute shrinkage and selection operator (LASSO, Support Vector Regression (SVR and Random Forests (RF for the following insulin sensitivity indices: homeostasis model of insulin resistance (HOMA-IR, glucose insulin sensitivity index (GSI, insulin sensitivity index (ISI, and disposition index (DI. The LASSO procedure offers a high prediction accuracy and and an easier interpretability than SVR and RF.After LASSO selection, the plasma lipidome explained 3% (DI to maximal 53% (HOMA-IR variability of the sensitivity indexes. Among the lipid species with the highest positive LASSO regression coefficient were TAG 54:2 (HOMA-IR, PC O- 32:0 (GSI, and SM 40:3:1 (ISI. The highest negative regression coefficient was obtained for LPC 22:5 (HOMA-IR, TAG 51:1 (GSI, and TAG 58:6 (ISI.Although a substantial part of lipid molecular species showed a significant correlation with insulin sensitivity indices we were able to identify a limited number of lipid metabolites of particular importance based on the LASSO approach. These few selected lipids with the closest
Defining and detecting structural sensitivity in biological models: developing a new framework.
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.
Supplementary Material for: A global sensitivity analysis approach for morphogenesis models
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