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Sample records for parameter sensitivity analysis

  1. 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

  2. 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

  3. Sensitivity functions for uncertainty analysis: Sensitivity and uncertainty analysis of reactor performance parameters

    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

  4. 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.

  5. 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.

  6. 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)

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

    Science.gov (United States)

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

    2014-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Xiao-meng Song

    2013-01-01

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

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

    Science.gov (United States)

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

    2015-10-01

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

  10. Accuracy and sensitivity analysis on seismic anisotropy parameter estimation

    Science.gov (United States)

    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.

  11. Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

    Science.gov (United States)

    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

  12. How often do sensitivity analyses for economic parameters change cost-utility analysis conclusions?

    Science.gov (United States)

    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

  13. 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)

  14. 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

  15. 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.

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

    Science.gov (United States)

    Gul, R; Bernhard, S

    2015-11-01

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

  17. Sensitivity analysis of railpad parameters on vertical railway track dynamics

    NARCIS (Netherlands)

    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

  18. Groundwater pathway sensitivity analysis and hydrogeologic parameters identification for waste disposal in porous media

    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

  19. The derivative based variance sensitivity analysis for the distribution parameters and its computation

    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

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    J. Li

    2013-08-01

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

  2. 'PSA-SPN' - A Parameter Sensitivity Analysis Method Using Stochastic Petri Nets: Application to a Production Line System

    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.

  3. 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

  4. 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

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

    Science.gov (United States)

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

    2018-06-01

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

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

    Directory of Open Access Journals (Sweden)

    W. Castaings

    2009-04-01

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

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

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

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

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

  7. A Sensitivity Study for an Evaluation of Input Parameters Effect on a Preliminary Probabilistic Tsunami Hazard Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Rhee, Hyun-Me; Kim, Min Kyu; Choi, In-Kil [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Sheen, Dong-Hoon [Chonnam National University, Gwangju (Korea, Republic of)

    2014-10-15

    The tsunami hazard analysis has been based on the seismic hazard analysis. The seismic hazard analysis has been performed by using the deterministic method and the probabilistic method. To consider the uncertainties in hazard analysis, the probabilistic method has been regarded as attractive approach. The various parameters and their weight are considered by using the logic tree approach in the probabilistic method. The uncertainties of parameters should be suggested by analyzing the sensitivity because the various parameters are used in the hazard analysis. To apply the probabilistic tsunami hazard analysis, the preliminary study for the Ulchin NPP site had been performed. The information on the fault sources which was published by the Atomic Energy Society of Japan (AESJ) had been used in the preliminary study. The tsunami propagation was simulated by using the TSUNAMI{sub 1}.0 which was developed by Japan Nuclear Energy Safety Organization (JNES). The wave parameters have been estimated from the result of tsunami simulation. In this study, the sensitivity analysis for the fault sources which were selected in the previous studies has been performed. To analyze the effect of the parameters, the sensitivity analysis for the E3 fault source which was published by AESJ was performed. The effect of the recurrence interval, the potential maximum magnitude, and the beta were suggested by the sensitivity analysis results. Level of annual exceedance probability has been affected by the recurrence interval.. Wave heights have been influenced by the potential maximum magnitude and the beta. In the future, the sensitivity analysis for the all fault sources in the western part of Japan which were published AESJ would be performed.

  8. 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.

  9. AN OVERVIEW OF THE UNCERTAINTY ANALYSIS, SENSITIVITY ANALYSIS, AND PARAMETER ESTIMATION (UA/SA/PE) API AND HOW TO IMPLEMENT IT

    Science.gov (United States)

    The Application Programming Interface (API) for Uncertainty Analysis, Sensitivity Analysis, andParameter Estimation (UA/SA/PE API) (also known as Calibration, Optimization and Sensitivity and Uncertainty (CUSO)) was developed in a joint effort between several members of both ...

  10. Parameter Estimation and Sensitivity Analysis of an Urban Surface Energy Balance Parameterization at a Tropical Suburban Site

    Science.gov (United States)

    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

  11. Sensitivity analysis of effective population size to demographic parameters in house sparrow populations.

    Science.gov (United States)

    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.

  12. 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...

  13. Sensitivity Analysis of Uncertainty Parameter based on MARS-LMR Code on SHRT-45R of EBR II

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Seok-Ju; Kang, Doo-Hyuk; Seo, Jae-Seung [System Engineering and Technology Co., Daejeon (Korea, Republic of); Bae, Sung-Won [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Jeong, Hae-Yong [Sejong University, Seoul (Korea, Republic of)

    2016-10-15

    In order to assess the uncertainty quantification of the MARS-LMR code, the code has been improved by modifying the source code to accommodate calculation process required for uncertainty quantification. In the present study, a transient of Unprotected Loss of Flow(ULOF) is selected as typical cases of as Anticipated Transient without Scram(ATWS) which belongs to DEC category. The MARS-LMR input generation for EBR II SHRT-45R and execution works are performed by using the PAPIRUS program. The sensitivity analysis is carried out with Uncertainty Parameter of the MARS-LMR code for EBR-II SHRT-45R. Based on the results of sensitivity analysis, dominant parameters with large sensitivity to FoM are picked out. Dominant parameters selected are closely related to the development process of ULOF event.

  14. 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.

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

    Science.gov (United States)

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

    2015-07-01

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

  16. 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.

  17. 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)

  18. 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.

  19. Parameter sensitivity analysis of a 1-D cold region lake model for land-surface schemes

    Science.gov (United States)

    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.

  20. Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process

    Science.gov (United States)

    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

  1. 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

  2. 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.

  3. 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

  4. Three-dimensional optimization and sensitivity analysis of dental implant thread parameters using finite element analysis.

    Science.gov (United States)

    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.

  5. Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

    Science.gov (United States)

    Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende

    2014-01-01

    Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

  6. Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  8. PAPIRUS, a parallel computing framework for sensitivity analysis, uncertainty propagation, and estimation of parameter distribution

    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

  9. PAPIRUS, a parallel computing framework for sensitivity analysis, uncertainty propagation, and estimation of parameter distribution

    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.

  10. Adjoint Parameter Sensitivity Analysis for the Hydrodynamic Lattice Boltzmann Method with Applications to Design Optimization

    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...

  11. Parameter sensitivity analysis of nonlinear piezoelectric probe in tapping mode atomic force microscopy for measurement improvement

    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.

  12. Parameter estimation and sensitivity analysis for a mathematical model with time delays of leukemia

    Science.gov (United States)

    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.

  13. Chemical kinetic functional sensitivity analysis: Elementary sensitivities

    International Nuclear Information System (INIS)

    Demiralp, M.; Rabitz, H.

    1981-01-01

    Sensitivity analysis is considered for kinetics problems defined in the space--time domain. This extends an earlier temporal Green's function method to handle calculations of elementary functional sensitivities deltau/sub i//deltaα/sub j/ where u/sub i/ is the ith species concentration and α/sub j/ is the jth system parameter. The system parameters include rate constants, diffusion coefficients, initial conditions, boundary conditions, or any other well-defined variables in the kinetic equations. These parameters are generally considered to be functions of position and/or time. Derivation of the governing equations for the sensitivities and the Green's funciton are presented. The physical interpretation of the Green's function and sensitivities is given along with a discussion of the relation of this work to earlier research

  14. Sensitivity analysis of parameters important to nuclear criticality safety of Castor X/28F spent nuclear fuel cask

    Energy Technology Data Exchange (ETDEWEB)

    Leotlela, Mosebetsi J. [Witwatersrand Univ., Johannesburg (South Africa). School of Physics; Koeberg Operating Unit, Johannesburg (South Africa). Regulations and Licensing; Malgas, Isaac [Koeberg Nuclear Power Station, Duinefontein (South Africa). Nuclear Engineering Analysis; Taviv, Eugene [ASARA consultants (PTY) LTD, Johannesburg (South Africa)

    2015-11-15

    In nuclear criticality safety analysis it is essential to ascertain how various components of the nuclear system will perform under certain conditions they may be subjected to, particularly if the components of the system are likely to be affected by environmental factors such as temperature, radiation or material composition. It is therefore prudent that a sensitivity analysis is performed to determine and quantify the response of the output to variation in any of the input parameters. In a fissile system, the output parameter of importance is the k{sub eff}. Therefore, in attempting to prevent reactivity-induced accidents, it is important for the criticality safety analyst to have a quantified degree of response for the neutron multiplication factor to perturbation in a given input parameter. This article will present the results of the perturbation of the parameters that are important to nuclear criticality safety analysis and their respective correlation equations for deriving the sensitivity coefficients.

  15. A sensitivity analysis method for the body segment inertial parameters based on ground reaction and joint moment regressor matrices.

    Science.gov (United States)

    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.

  16. Sensitivity analysis in oxidation ditch modelling: the effect of variations in stoichiometric, kinetic and operating parameters on the performance indices

    NARCIS (Netherlands)

    Abusam, A.A.A.; Keesman, K.J.; Straten, van G.; Spanjers, H.; Meinema, K.

    2001-01-01

    This paper demonstrates the application of the factorial sensitivity analysis methodology in studying the influence of variations in stoichiometric, kinetic and operating parameters on the performance indices of an oxidation ditch simulation model (benchmark). Factorial sensitivity analysis

  17. A parameter tree approach to estimating system sensitivities to parameter sets

    International Nuclear Information System (INIS)

    Jarzemba, M.S.; Sagar, B.

    2000-01-01

    Total System Performance Assessment Code called TPA, realizations are obtained and analyzed. In the examples presented, groups of five important parameters, one for each level of the tree, are used to identify branches of the tree and construct the bins. In the first example, the five important parameters are selected by more traditional sensitivity analysis techniques. This example shows that relatively few branches of the tree dominate system performance. In another example, the same realizations are used but the most important five-parameter set is determined in a stepwise manner (using the parameter tree technique) and it is found that these five parameters do not match the five of the first example. This important result shows that sensitivities based on individual parameters (i.e. one parameter at a time) may differ from sensitivities estimated based on joint sets of parameters (i.e. two or more parameters at a time). The technique is extended using subsystem outputs to define the branches of the tree. The subsystem outputs used in this example are the total cumulative radionuclide release (TCR) from the engineered barriers, unsaturated zone, and saturated zone over 10,000 yr. The technique is found to be successful in estimating the relative influence of each of these three subsystems on the overall system behavior

  18. Techniques for sensitivity analysis of SYVAC results

    International Nuclear Information System (INIS)

    Prust, J.O.

    1985-05-01

    Sensitivity analysis techniques may be required to examine the sensitivity of SYVAC model predictions to the input parameter values, the subjective probability distributions assigned to the input parameters and to the relationship between dose and the probability of fatal cancers plus serious hereditary disease in the first two generations of offspring of a member of the critical group. This report mainly considers techniques for determining the sensitivity of dose and risk to the variable input parameters. The performance of a sensitivity analysis technique may be improved by decomposing the model and data into subsets for analysis, making use of existing information on sensitivity and concentrating sampling in regions the parameter space that generates high doses or risks. A number of sensitivity analysis techniques are reviewed for their application to the SYVAC model including four techniques tested in an earlier study by CAP Scientific for the SYVAC project. This report recommends the development now of a method for evaluating the derivative of dose and parameter value and extending the Kruskal-Wallis technique to test for interactions between parameters. It is also recommended that the sensitivity of the output of each sub-model of SYVAC to input parameter values should be examined. (author)

  19. Sensitivity Analysis of Unsaturated Flow and Contaminant Transport with Correlated Parameters

    Science.gov (United States)

    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...

  20. Field-sensitivity To Rheological Parameters

    Science.gov (United States)

    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.

  1. Reduction of low frequency vibration of truck driver and seating system through system parameter identification, sensitivity analysis and active control

    Science.gov (United States)

    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.

  2. Sensitivity analysis approaches applied to systems biology models.

    Science.gov (United States)

    Zi, Z

    2011-11-01

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

  3. 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.

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

    Science.gov (United States)

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

    2016-02-01

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

  5. Sensitivity analysis of respiratory parameter uncertainties: impact of criterion function form and constraints.

    Science.gov (United States)

    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.

  6. MOVES regional level sensitivity analysis

    Science.gov (United States)

    2012-01-01

    The MOVES Regional Level Sensitivity Analysis was conducted to increase understanding of the operations of the MOVES Model in regional emissions analysis and to highlight the following: : the relative sensitivity of selected MOVES Model input paramet...

  7. 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

  8. Parameters Identification and Sensitive Characteristics Analysis for Lithium-Ion Batteries of Electric Vehicles

    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.

  9. Sensitivity Analysis of the Influence of Structural Parameters on Dynamic Behaviour of Highly Redundant Cable-Stayed Bridges

    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.

  10. 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

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

    Science.gov (United States)

    Ely, D. Matthew

    2006-01-01

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

  12. Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.

    Science.gov (United States)

    Arampatzis, Georgios; Katsoulakis, Markos A; Pantazis, Yannis

    2015-01-01

    Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially) sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of parameters over the

  13. Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.

    Directory of Open Access Journals (Sweden)

    Georgios Arampatzis

    Full Text Available Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of

  14. 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.

  15. Sensitivity analysis of a PWR pressurizer

    International Nuclear Information System (INIS)

    Bruel, Renata Nunes

    1997-01-01

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

  16. Sensitivity analysis of minor actinides transmutation to physical and technological parameters

    International Nuclear Information System (INIS)

    Kooyman, T.; Buiron, L.

    2015-01-01

    Minor actinides transmutation is one of the 3 main axis defined by the 2006 French law for management of nuclear waste, along with long-term storage and use of a deep geological repository. Transmutation options for critical systems can be divided in two different approaches: (a) homogeneous transmutation, in which minor actinides are mixed with the fuel. This exhibits the drawback of 'polluting' the entire fuel cycle with minor actinides and also has an important impact on core reactivity coefficients such as Doppler Effect or sodium void worth for fast reactors when the minor actinides fraction increases above 3 to 5% depending on the core; (b) heterogeneous transmutation, in which minor actinides are inserted into transmutation targets which can be located in the center or in the periphery of the core. This presents the advantage of decoupling the management of the minor actinides from the conventional fuel and not impacting the core reactivity coefficients. In both cases, the design and analyses of potential transmutation systems have been carried out in the frame of Gen IV fast reactor using a 'perturbation' approach in which nominal power reactor parameters are modified to accommodate the loading of minor actinides. However, when designing such a transmutation strategy, parameters from all steps of the fuel cycle must be taken into account, such as spent fuel heat load, gamma or neutron sources or fabrication feasibility. Considering a multi-recycling strategy of minor actinides, an analysis of relevant estimators necessary to fully analyze a transmutation strategy has been performed in this work and a sensitivity analysis of these estimators to a broad choice of reactors and fuel cycle parameters has been carried out. No threshold or percolation effects were observed. Saturation of transmutation rate with regards to several parameters has been observed, namely the minor actinides volume fraction and the irradiation time. Estimators of interest that have been

  17. Sensitivity analysis in life cycle assessment

    NARCIS (Netherlands)

    Groen, E.A.; Heijungs, R.; Bokkers, E.A.M.; Boer, de I.J.M.

    2014-01-01

    Life cycle assessments require many input parameters and many of these parameters are uncertain; therefore, a sensitivity analysis is an essential part of the final interpretation. The aim of this study is to compare seven sensitivity methods applied to three types of case stud-ies. Two

  18. Sensitivity Analysis of Input Parameters for the Dose Assessment from Gaseous Effluents due to the Normal Operation of Jordan Research and Training Reactor

    International Nuclear Information System (INIS)

    Kim, Sukhoon; Lee, Seunghee; Kim, Juyoul; Kim, Juyub; Han, Moonhee

    2015-01-01

    In this study, therefore, the sensitivity analysis of input variables for the dose assessment was performed for reviewing the effect of each parameter on the result after determining the type and range of parameters that could affect the exposure dose of the public. (Since JRTR will be operated by the concept of 'no liquid discharge,' the input parameters used for calculation of dose due to liquid effluents are not considered in the sensitivity analysis.) In this paper, the sensitivity analysis of input parameters for the dose assessment in the vicinity of the site boundary due to gaseous effluents was performed for a total of thirty-five (35) cases. And, detailed results for the input variables that have an significant effect are shown in Figures 1 through 7, respectively. For preparing a R-ER for the operating license of the JRTR, these results will be updated by the additional information and could be applied to predicting the variation trend of the exposure dose in the process of updating the input parameters for the dose assessment reflecting the characteristics of the JRTR site

  19. Sensitivity analysis of the RESRAD, a dose assessment code

    International Nuclear Information System (INIS)

    Yu, C.; Cheng, J.J.; Zielen, A.J.

    1991-01-01

    The RESRAD code is a pathway analysis code that is designed to calculate radiation doses and derive soil cleanup criteria for the US Department of Energy's environmental restoration and waste management program. the RESRAD code uses various pathway and consumption-rate parameters such as soil properties and food ingestion rates in performing such calculations and derivations. As with any predictive model, the accuracy of the predictions depends on the accuracy of the input parameters. This paper summarizes the results of a sensitivity analysis of RESRAD input parameters. Three methods were used to perform the sensitivity analysis: (1) Gradient Enhanced Software System (GRESS) sensitivity analysis software package developed at oak Ridge National Laboratory; (2) direct perturbation of input parameters; and (3) built-in graphic package that shows parameter sensitivities while the RESRAD code is operational

  20. Sensitivity analysis on parameters and processes affecting vapor intrusion risk

    KAUST Repository

    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.

  1. Sensitivity analysis of the parameters of an HIV/AIDS model with condom campaign and antiretroviral therapy

    Science.gov (United States)

    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.

  2. Sensitivity analysis of the effect of various key parameters on fission product concentration (mass number 120 to 126)

    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

  3. A general first-order global sensitivity analysis method

    International Nuclear Information System (INIS)

    Xu Chonggang; Gertner, George Zdzislaw

    2008-01-01

    Fourier amplitude sensitivity test (FAST) is one of the most popular global sensitivity analysis techniques. The main mechanism of FAST is to assign each parameter with a characteristic frequency through a search function. Then, for a specific parameter, the variance contribution can be singled out of the model output by the characteristic frequency. Although FAST has been widely applied, there are two limitations: (1) the aliasing effect among parameters by using integer characteristic frequencies and (2) the suitability for only models with independent parameters. In this paper, we synthesize the improvement to overcome the aliasing effect limitation [Tarantola S, Gatelli D, Mara TA. Random balance designs for the estimation of first order global sensitivity indices. Reliab Eng Syst Safety 2006; 91(6):717-27] and the improvement to overcome the independence limitation [Xu C, Gertner G. Extending a global sensitivity analysis technique to models with correlated parameters. Comput Stat Data Anal 2007, accepted for publication]. In this way, FAST can be a general first-order global sensitivity analysis method for linear/nonlinear models with as many correlated/uncorrelated parameters as the user specifies. We apply the general FAST to four test cases with correlated parameters. The results show that the sensitivity indices derived by the general FAST are in good agreement with the sensitivity indices derived by the correlation ratio method, which is a non-parametric method for models with correlated parameters

  4. 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.

  5. Sensitivity Analysis of a Simplified Fire Dynamic Model

    DEFF Research Database (Denmark)

    Sørensen, Lars Schiøtt; Nielsen, Anker

    2015-01-01

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

  6. Sensitivity Analysis Without Assumptions.

    Science.gov (United States)

    Ding, Peng; VanderWeele, Tyler J

    2016-05-01

    Unmeasured confounding may undermine the validity of causal inference with observational studies. Sensitivity analysis provides an attractive way to partially circumvent this issue by assessing the potential influence of unmeasured confounding on causal conclusions. However, previous sensitivity analysis approaches often make strong and untestable assumptions such as having an unmeasured confounder that is binary, or having no interaction between the effects of the exposure and the confounder on the outcome, or having only one unmeasured confounder. Without imposing any assumptions on the unmeasured confounder or confounders, we derive a bounding factor and a sharp inequality such that the sensitivity analysis parameters must satisfy the inequality if an unmeasured confounder is to explain away the observed effect estimate or reduce it to a particular level. Our approach is easy to implement and involves only two sensitivity parameters. Surprisingly, our bounding factor, which makes no simplifying assumptions, is no more conservative than a number of previous sensitivity analysis techniques that do make assumptions. Our new bounding factor implies not only the traditional Cornfield conditions that both the relative risk of the exposure on the confounder and that of the confounder on the outcome must satisfy but also a high threshold that the maximum of these relative risks must satisfy. Furthermore, this new bounding factor can be viewed as a measure of the strength of confounding between the exposure and the outcome induced by a confounder.

  7. 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.

  8. Probabilistic sensitivity analysis of biochemical reaction systems.

    Science.gov (United States)

    Zhang, Hong-Xuan; Dempsey, William P; Goutsias, John

    2009-09-07

    Sensitivity analysis is an indispensable tool for studying the robustness and fragility properties of biochemical reaction systems as well as for designing optimal approaches for selective perturbation and intervention. Deterministic sensitivity analysis techniques, using derivatives of the system response, have been extensively used in the literature. However, these techniques suffer from several drawbacks, which must be carefully considered before using them in problems of systems biology. We develop here a probabilistic approach to sensitivity analysis of biochemical reaction systems. The proposed technique employs a biophysically derived model for parameter fluctuations and, by using a recently suggested variance-based approach to sensitivity analysis [Saltelli et al., Chem. Rev. (Washington, D.C.) 105, 2811 (2005)], it leads to a powerful sensitivity analysis methodology for biochemical reaction systems. The approach presented in this paper addresses many problems associated with derivative-based sensitivity analysis techniques. Most importantly, it produces thermodynamically consistent sensitivity analysis results, can easily accommodate appreciable parameter variations, and allows for systematic investigation of high-order interaction effects. By employing a computational model of the mitogen-activated protein kinase signaling cascade, we demonstrate that our approach is well suited for sensitivity analysis of biochemical reaction systems and can produce a wealth of information about the sensitivity properties of such systems. The price to be paid, however, is a substantial increase in computational complexity over derivative-based techniques, which must be effectively addressed in order to make the proposed approach to sensitivity analysis more practical.

  9. 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.

  10. Extended forward sensitivity analysis of one-dimensional isothermal flow

    International Nuclear Information System (INIS)

    Johnson, M.; Zhao, H.

    2013-01-01

    Sensitivity analysis and uncertainty quantification is an important part of nuclear safety analysis. In this work, forward sensitivity analysis is used to compute solution sensitivities on 1-D fluid flow equations typical of those found in system level codes. Time step sensitivity analysis is included as a method for determining the accumulated error from time discretization. The ability to quantify numerical error arising from the time discretization is a unique and important feature of this method. By knowing the relative sensitivity of time step with other physical parameters, the simulation is allowed to run at optimized time steps without affecting the confidence of the physical parameter sensitivity results. The time step forward sensitivity analysis method can also replace the traditional time step convergence studies that are a key part of code verification with much less computational cost. One well-defined benchmark problem with manufactured solutions is utilized to verify the method; another test isothermal flow problem is used to demonstrate the extended forward sensitivity analysis process. Through these sample problems, the paper shows the feasibility and potential of using the forward sensitivity analysis method to quantify uncertainty in input parameters and time step size for a 1-D system-level thermal-hydraulic safety code. (authors)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2018-02-12

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

  12. Reliability analysis of a sensitive and independent stabilometry parameter set.

    Science.gov (United States)

    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.

  13. Reliability analysis of a sensitive and independent stabilometry parameter set

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    L. A. Lee

    2011-12-01

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

  15. 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.

  16. Sensitivity analysis of critical experiment with direct perturbation compared to TSUNAMI-3D sensitivity analysis

    International Nuclear Information System (INIS)

    Barber, A. D.; Busch, R.

    2009-01-01

    The goal of this work is to obtain sensitivities from direct uncertainty analysis calculation and correlate those calculated values with the sensitivities produced from TSUNAMI-3D (Tools for Sensitivity and Uncertainty Analysis Methodology Implementation in Three Dimensions). A full sensitivity analysis is performed on a critical experiment to determine the overall uncertainty of the experiment. Small perturbation calculations are performed for all known uncertainties to obtain the total uncertainty of the experiment. The results from a critical experiment are only known as well as the geometric and material properties. The goal of this relationship is to simplify the uncertainty quantification process in assessing a critical experiment, while still considering all of the important parameters. (authors)

  17. An analysis of sensitivity of CLIMEX parameters in mapping species potential distribution and the broad-scale changes observed with minor variations in parameters values: an investigation using open-field Solanum lycopersicum and Neoleucinodes elegantalis as an example

    Science.gov (United States)

    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.

  18. A global sensitivity analysis approach for morphogenesis models

    KAUST Repository

    Boas, Sonja E. M.

    2015-11-21

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

  19. A global sensitivity analysis approach for morphogenesis models.

    Science.gov (United States)

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

    2015-11-21

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

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

    NARCIS (Netherlands)

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

    2015-01-01

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

  1. Sobol' sensitivity analysis for stressor impacts on honeybee ...

    Science.gov (United States)

    We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather, colony resources, population structure, and other important variables. This allows us to test the effects of defined pesticide exposure scenarios versus controlled simulations that lack pesticide exposure. The daily resolution of the model also allows us to conditionally identify sensitivity metrics. We use the variancebased global decomposition sensitivity analysis method, Sobol’, to assess firstand secondorder parameter sensitivities within VarroaPop, allowing us to determine how variance in the output is attributed to each of the input variables across different exposure scenarios. Simulations with VarroaPop indicate queen strength, forager life span and pesticide toxicity parameters are consistent, critical inputs for colony dynamics. Further analysis also reveals that the relative importance of these parameters fluctuates throughout the simulation period according to the status of other inputs. Our preliminary results show that model variability is conditional and can be attributed to different parameters depending on different timescales. By using sensitivity analysis to assess model output and variability, calibrations of simulation models can be better informed to yield more

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

    Science.gov (United States)

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

    2011-12-01

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

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

    Science.gov (United States)

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

    2015-04-01

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

  4. Global optimization and sensitivity analysis

    International Nuclear Information System (INIS)

    Cacuci, D.G.

    1990-01-01

    A new direction for the analysis of nonlinear models of nuclear systems is suggested to overcome fundamental limitations of sensitivity analysis and optimization methods currently prevalent in nuclear engineering usage. This direction is toward a global analysis of the behavior of the respective system as its design parameters are allowed to vary over their respective design ranges. Presented is a methodology for global analysis that unifies and extends the current scopes of sensitivity analysis and optimization by identifying all the critical points (maxima, minima) and solution bifurcation points together with corresponding sensitivities at any design point of interest. The potential applicability of this methodology is illustrated with test problems involving multiple critical points and bifurcations and comprising both equality and inequality constraints

  5. Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis :

    Energy Technology Data Exchange (ETDEWEB)

    Adams, Brian M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ebeida, Mohamed Salah [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Eldred, Michael S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jakeman, John Davis [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stephens, John Adam [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vigil, Dena M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wildey, Timothy Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bohnhoff, William J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Eddy, John P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hu, Kenneth T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Dalbey, Keith R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bauman, Lara E [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hough, Patricia Diane [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-05-01

    The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

  6. Sensitivity analysis in remote sensing

    CERN Document Server

    Ustinov, Eugene A

    2015-01-01

    This book contains a detailed presentation of general principles of sensitivity analysis as well as their applications to sample cases of remote sensing experiments. An emphasis is made on applications of adjoint problems, because they are more efficient in many practical cases, although their formulation may seem counterintuitive to a beginner. Special attention is paid to forward problems based on higher-order partial differential equations, where a novel matrix operator approach to formulation of corresponding adjoint problems is presented. Sensitivity analysis (SA) serves for quantitative models of physical objects the same purpose, as differential calculus does for functions. SA provides derivatives of model output parameters (observables) with respect to input parameters. In remote sensing SA provides computer-efficient means to compute the jacobians, matrices of partial derivatives of observables with respect to the geophysical parameters of interest. The jacobians are used to solve corresponding inver...

  7. 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.

  8. Are LOD and LOQ Reliable Parameters for Sensitivity Evaluation of Spectroscopic Methods?

    Science.gov (United States)

    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.

  9. Global sensitivity analysis of a model related to memory formation in synapses: Model reduction based on epistemic parameter uncertainties and related issues.

    Science.gov (United States)

    Kulasiri, Don; Liang, Jingyi; He, Yao; Samarasinghe, Sandhya

    2017-04-21

    We investigate the epistemic uncertainties of parameters of a mathematical model that describes the dynamics of CaMKII-NMDAR complex related to memory formation in synapses using global sensitivity analysis (GSA). The model, which was published in this journal, is nonlinear and complex with Ca 2+ patterns with different level of frequencies as inputs. We explore the effects of parameter on the key outputs of the model to discover the most sensitive ones using GSA and partial ranking correlation coefficient (PRCC) and to understand why they are sensitive and others are not based on the biology of the problem. We also extend the model to add presynaptic neurotransmitter vesicles release to have action potentials as inputs of different frequencies. We perform GSA on this extended model to show that the parameter sensitivities are different for the extended model as shown by PRCC landscapes. Based on the results of GSA and PRCC, we reduce the original model to a less complex model taking the most important biological processes into account. We validate the reduced model against the outputs of the original model. We show that the parameter sensitivities are dependent on the inputs and GSA would make us understand the sensitivities and the importance of the parameters. A thorough phenomenological understanding of the relationships involved is essential to interpret the results of GSA and hence for the possible model reduction. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. A Global Sensitivity Analysis Methodology for Multi-physics Applications

    Energy Technology Data Exchange (ETDEWEB)

    Tong, C H; Graziani, F R

    2007-02-02

    Experiments are conducted to draw inferences about an entire ensemble based on a selected number of observations. This applies to both physical experiments as well as computer experiments, the latter of which are performed by running the simulation models at different input configurations and analyzing the output responses. Computer experiments are instrumental in enabling model analyses such as uncertainty quantification and sensitivity analysis. This report focuses on a global sensitivity analysis methodology that relies on a divide-and-conquer strategy and uses intelligent computer experiments. The objective is to assess qualitatively and/or quantitatively how the variabilities of simulation output responses can be accounted for by input variabilities. We address global sensitivity analysis in three aspects: methodology, sampling/analysis strategies, and an implementation framework. The methodology consists of three major steps: (1) construct credible input ranges; (2) perform a parameter screening study; and (3) perform a quantitative sensitivity analysis on a reduced set of parameters. Once identified, research effort should be directed to the most sensitive parameters to reduce their uncertainty bounds. This process is repeated with tightened uncertainty bounds for the sensitive parameters until the output uncertainties become acceptable. To accommodate the needs of multi-physics application, this methodology should be recursively applied to individual physics modules. The methodology is also distinguished by an efficient technique for computing parameter interactions. Details for each step will be given using simple examples. Numerical results on large scale multi-physics applications will be available in another report. Computational techniques targeted for this methodology have been implemented in a software package called PSUADE.

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

    Science.gov (United States)

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

    2013-01-01

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

  12. Stability assessment and operating parameter optimization on experimental results in very small plasma focus, using sensitivity analysis

    Science.gov (United States)

    Jafari, Hossein; Habibi, Morteza

    2018-04-01

    Regarding the importance of stability in small-scale plasma focus devices for producing the repeatable and strength pinching, a sensitivity analysis approach has been used for applicability in design parameters optimization of an actually very low energy device (84 nF, 48 nH, 8-9.5 kV, ∼2.7-3.7 J). To optimize the devices functional specification, four different coaxial electrode configurations have been studied, scanning an argon gas pressure range from 0.6 to 1.5 mbar via the charging voltage variation study from 8.3 to 9.3 kV. The strength and efficient pinching was observed for the tapered anode configuration, over an expanded operating pressure range of 0.6 to 1.5 mbar. The analysis results showed that the most sensitive of the pinch voltage was associated with 0.88 ± 0.8mbar argon gas pressure and 8.3-8.5 kV charging voltage, respectively, as the optimum operating parameters. From the viewpoint of stability assessment of the device, it was observed that the least variation in stable operation of the device was for a charging voltage range of 8.3 to 8.7 kV in an operating pressure range from 0.6 to 1.1 mbar.

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

    Science.gov (United States)

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

    2013-12-01

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

  14. Sensitivity analysis of LOFT L2-5 test calculations

    International Nuclear Information System (INIS)

    Prosek, Andrej

    2014-01-01

    The uncertainty quantification of best-estimate code predictions is typically accompanied by a sensitivity analysis, in which the influence of the individual contributors to uncertainty is determined. The objective of this study is to demonstrate the improved fast Fourier transform based method by signal mirroring (FFTBM-SM) for the sensitivity analysis. The sensitivity study was performed for the LOFT L2-5 test, which simulates the large break loss of coolant accident. There were 14 participants in the BEMUSE (Best Estimate Methods-Uncertainty and Sensitivity Evaluation) programme, each performing a reference calculation and 15 sensitivity runs of the LOFT L2-5 test. The important input parameters varied were break area, gap conductivity, fuel conductivity, decay power etc. For the influence of input parameters on the calculated results the FFTBM-SM was used. The only difference between FFTBM-SM and original FFTBM is that in the FFTBM-SM the signals are symmetrized to eliminate the edge effect (the so called edge is the difference between the first and last data point of one period of the signal) in calculating average amplitude. It is very important to eliminate unphysical contribution to the average amplitude, which is used as a figure of merit for input parameter influence on output parameters. The idea is to use reference calculation as 'experimental signal', 'sensitivity run' as 'calculated signal', and average amplitude as figure of merit for sensitivity instead for code accuracy. The larger is the average amplitude the larger is the influence of varied input parameter. The results show that with FFTBM-SM the analyst can get good picture of the contribution of the parameter variation to the results. They show when the input parameters are influential and how big is this influence. FFTBM-SM could be also used to quantify the influence of several parameter variations on the results. However, the influential parameters could not be

  15. 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

  16. Sensitivity analysis of dynamic characteristic of the fixture based on design variables

    International Nuclear Information System (INIS)

    Wang Dongsheng; Nong Shaoning; Zhang Sijian; Ren Wanfa

    2002-01-01

    The research on the sensitivity analysis is dealt with of structural natural frequencies to structural design parameters. A typical fixture for vibration test is designed. Using I-DEAS Finite Element programs, the sensitivity of its natural frequency to design parameters is analyzed by Matrix Perturbation Method. The research result shows that the sensitivity analysis is a fast and effective dynamic re-analysis method to dynamic design and parameters modification of complex structures such as fixtures

  17. Evaluation of parameter sensitivities for flux-switching permanent magnet machines based on simplified equivalent magnetic circuit

    Directory of Open Access Journals (Sweden)

    Gan Zhang

    2017-05-01

    Full Text Available Most of the published papers regarding the design of flux-switching permanent magnet machines are focused on the analysis and optimization of electromagnetic or mechanical behaviors, however, the evaluate of the parameter sensitivities have not been covered, which contrarily, is the main contribution of this paper. Based on the finite element analysis (FEA and simplified equivalent magnetic circuit, the method proposed in this paper enables the influences of parameters on the electromagnetic performances, i.e. the parameter sensitivities, to be given by equations. The FEA results are also validated by experimental measurements.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  19. 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.

  20. A sensitivity analysis of hazardous waste disposal site climatic and soil design parameters using HELP3

    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

  1. UMTS Common Channel Sensitivity Analysis

    DEFF Research Database (Denmark)

    Pratas, Nuno; Rodrigues, António; Santos, Frederico

    2006-01-01

    and as such it is necessary that both channels be available across the cell radius. This requirement makes the choice of the transmission parameters a fundamental one. This paper presents a sensitivity analysis regarding the transmission parameters of two UMTS common channels: RACH and FACH. Optimization of these channels...... is performed and values for the key transmission parameters in both common channels are obtained. On RACH these parameters are the message to preamble offset, the initial SIR target and the preamble power step while on FACH it is the transmission power offset....

  2. Cogeneration: Key feasibility analysis parameters

    International Nuclear Information System (INIS)

    Coslovi, S.; Zulian, A.

    1992-01-01

    This paper first reviews the essential requirements, in terms of scope, objectives and methods, of technical/economic feasibility analyses applied to cogeneration systems proposed for industrial plants in Italy. Attention is given to the influence on overall feasibility of the following factors: electric power and fuel costs, equipment coefficients of performance, operating schedules, maintenance costs, Italian Government taxes and financial and legal incentives. Through an examination of several feasibility studies that were done on cogeneration proposals relative to different industrial sectors, a sensitivity analysis is performed on the effects of varying the weights of different cost benefit analysis parameters. With the use of statistical analyses, standard deviations are then determined for key analysis parameters, and guidelines are suggested for analysis simplifications

  3. Identification of the most sensitive parameters in the activated sludge model implemented in BioWin software.

    Science.gov (United States)

    Liwarska-Bizukojc, Ewa; Biernacki, Rafal

    2010-10-01

    In order to simulate biological wastewater treatment processes, data concerning wastewater and sludge composition, process kinetics and stoichiometry are required. Selection of the most sensitive parameters is an important step of model calibration. The aim of this work is to verify the predictability of the activated sludge model, which is implemented in BioWin software, and select its most influential kinetic and stoichiometric parameters with the help of sensitivity analysis approach. Two different measures of sensitivity are applied: the normalised sensitivity coefficient (S(i,j)) and the mean square sensitivity measure (delta(j)(msqr)). It occurs that 17 kinetic and stoichiometric parameters of the BioWin activated sludge (AS) model can be regarded as influential on the basis of S(i,j) calculations. Half of the influential parameters are associated with growth and decay of phosphorus accumulating organisms (PAOs). The identification of the set of the most sensitive parameters should support the users of this model and initiate the elaboration of determination procedures for the parameters, for which it has not been done yet. Copyright 2010 Elsevier Ltd. All rights reserved.

  4. Sensitivity analysis for decision-making using the MORE method-A Pareto approach

    International Nuclear Information System (INIS)

    Ravalico, Jakin K.; Maier, Holger R.; Dandy, Graeme C.

    2009-01-01

    Integrated Assessment Modelling (IAM) incorporates knowledge from different disciplines to provide an overarching assessment of the impact of different management decisions. The complex nature of these models, which often include non-linearities and feedback loops, requires special attention for sensitivity analysis. This is especially true when the models are used to form the basis of management decisions, where it is important to assess how sensitive the decisions being made are to changes in model parameters. This research proposes an extension to the Management Option Rank Equivalence (MORE) method of sensitivity analysis; a new method of sensitivity analysis developed specifically for use in IAM and decision-making. The extension proposes using a multi-objective Pareto optimal search to locate minimum combined parameter changes that result in a change in the preferred management option. It is demonstrated through a case study of the Namoi River, where results show that the extension to MORE is able to provide sensitivity information for individual parameters that takes into account simultaneous variations in all parameters. Furthermore, the increased sensitivities to individual parameters that are discovered when joint parameter variation is taken into account shows the importance of ensuring that any sensitivity analysis accounts for these changes.

  5. Performances of non-parametric statistics in sensitivity analysis and parameter ranking

    International Nuclear Information System (INIS)

    Saltelli, A.

    1987-01-01

    Twelve parametric and non-parametric sensitivity analysis techniques are compared in the case of non-linear model responses. The test models used are taken from the long-term risk analysis for the disposal of high level radioactive waste in a geological formation. They describe the transport of radionuclides through a set of engineered and natural barriers from the repository to the biosphere and to man. The output data from these models are the dose rates affecting the maximum exposed individual of a critical group at a given point in time. All the techniques are applied to the output from the same Monte Carlo simulations, where a modified version of Latin Hypercube method is used for the sample selection. Hypothesis testing is systematically applied to quantify the degree of confidence in the results given by the various sensitivity estimators. The estimators are ranked according to their robustness and stability, on the basis of two test cases. The conclusions are that no estimator can be considered the best from all points of view and recommend the use of more than just one estimator in sensitivity analysis

  6. Estimation of parameter sensitivities for stochastic reaction networks

    KAUST Repository

    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.

  7. Sensitive zone parameters and curvature radius evaluation for polymer optical fiber curvature sensors

    Science.gov (United States)

    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.

  8. DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Eldred, Michael Scott; Vigil, Dena M.; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Lefantzi, Sophia (Sandia National Laboratories, Livermore, CA); Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Eddy, John P.

    2011-12-01

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the DAKOTA software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of DAKOTA-related research publications in the areas of surrogate-based optimization, uncertainty quantification, and optimization under uncertainty that provide the foundation for many of DAKOTA's iterative analysis capabilities.

  9. Global sensitivity analysis for identifying important parameters of nitrogen nitrification and denitrification under model uncertainty and scenario uncertainty

    Science.gov (United States)

    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

  10. Parameter Identification with the Random Perturbation Particle Swarm Optimization Method and Sensitivity Analysis of an Advanced Pressurized Water Reactor Nuclear Power Plant Model for Power Systems

    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.

  11. Sensitivity analysis of ranked data: from order statistics to quantiles

    NARCIS (Netherlands)

    Heidergott, B.F.; Volk-Makarewicz, W.

    2015-01-01

    In this paper we provide the mathematical theory for sensitivity analysis of order statistics of continuous random variables, where the sensitivity is with respect to a distributional parameter. Sensitivity analysis of order statistics over a finite number of observations is discussed before

  12. Global sensitivity analysis in stochastic simulators of uncertain reaction networks.

    Science.gov (United States)

    Navarro Jimenez, M; Le Maître, O P; Knio, O M

    2016-12-28

    Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol's decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

  13. Global sensitivity analysis in stochastic simulators of uncertain reaction networks

    KAUST Repository

    Navarro, María

    2016-12-26

    Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol’s decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. A sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

  14. Semianalytical Solution and Parameters Sensitivity Analysis of Shallow Shield Tunneling-Induced Ground Settlement

    Directory of Open Access Journals (Sweden)

    Jifeng Liu

    2017-01-01

    Full Text Available The influence of boundary soil properties on tunneling-induced ground settlement is generally not considered in current analytic solutions, and the hypothesis of equal initial stress in vertical and horizontal makes the application of the above solutions limited. Based on the homogeneous half-plane hypothesis, by defining the boundary condition according to the ground loss pattern in shallow tunnel, and with the use of Mohr-Coulomb plastic yielding criteria and classic Lame and Kiersch elastic equations by separating the nonuniform stress field to uniform and single-direction stress field, a semiempirical solution for ground settlement induced by single shallow circular tunnel is presented and sensitivity to the ground parameters is analyzed. The methods of settlement control are offered by influence factors analysis of semiempirical solution. A case study in Beijing Metro tunnel shows that the semiempirical solution agrees well with the in situ measured results.

  15. A sensitivity analysis of process design parameters, commodity prices and robustness on the economics of odour abatement technologies.

    Science.gov (United States)

    Estrada, José M; Kraakman, N J R Bart; Lebrero, Raquel; Muñoz, Raúl

    2012-01-01

    The sensitivity of the economics of the five most commonly applied odour abatement technologies (biofiltration, biotrickling filtration, activated carbon adsorption, chemical scrubbing and a hybrid technology consisting of a biotrickling filter coupled with carbon adsorption) towards design parameters and commodity prices was evaluated. Besides, the influence of the geographical location on the Net Present Value calculated for a 20 years lifespan (NPV20) of each technology and its robustness towards typical process fluctuations and operational upsets were also assessed. This comparative analysis showed that biological techniques present lower operating costs (up to 6 times) and lower sensitivity than their physical/chemical counterparts, with the packing material being the key parameter affecting their operating costs (40-50% of the total operating costs). The use of recycled or partially treated water (e.g. secondary effluent in wastewater treatment plants) offers an opportunity to significantly reduce costs in biological techniques. Physical/chemical technologies present a high sensitivity towards H2S concentration, which is an important drawback due to the fluctuating nature of malodorous emissions. The geographical analysis evidenced high NPV20 variations around the world for all the technologies evaluated, but despite the differences in wage and price levels, biofiltration and biotrickling filtration are always the most cost-efficient alternatives (NPV20). When, in an economical evaluation, the robustness is as relevant as the overall costs (NPV20), the hybrid technology would move up next to BTF as the most preferred technologies. Copyright © 2012 Elsevier Inc. All rights reserved.

  16. A sensitivity analysis of a personalized pulse wave propagation model for arteriovenous fistula surgery. Part A: Identification of most influential model parameters.

    Science.gov (United States)

    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.

  17. Least squares shadowing sensitivity analysis of a modified Kuramoto–Sivashinsky equation

    International Nuclear Information System (INIS)

    Blonigan, Patrick J.; Wang, Qiqi

    2014-01-01

    Highlights: •Modifying the Kuramoto–Sivashinsky equation and changing its boundary conditions make it an ergodic dynamical system. •The modified Kuramoto–Sivashinsky equation exhibits distinct dynamics for three different ranges of system parameters. •Least squares shadowing sensitivity analysis computes accurate gradients for a wide range of system parameters. - Abstract: Computational methods for sensitivity analysis are invaluable tools for scientists and engineers investigating a wide range of physical phenomena. However, many of these methods fail when applied to chaotic systems, such as the Kuramoto–Sivashinsky (K–S) equation, which models a number of different chaotic systems found in nature. The following paper discusses the application of a new sensitivity analysis method developed by the authors to a modified K–S equation. We find that least squares shadowing sensitivity analysis computes accurate gradients for solutions corresponding to a wide range of system parameters

  18. Using sensitivity derivatives for design and parameter estimation in an atmospheric plasma discharge simulation

    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.

  19. Probabilistic sensitivity analysis of system availability using Gaussian processes

    International Nuclear Information System (INIS)

    Daneshkhah, Alireza; Bedford, Tim

    2013-01-01

    The availability of a system under a given failure/repair process is a function of time which can be determined through a set of integral equations and usually calculated numerically. We focus here on the issue of carrying out sensitivity analysis of availability to determine the influence of the input parameters. The main purpose is to study the sensitivity of the system availability with respect to the changes in the main parameters. In the simplest case that the failure repair process is (continuous time/discrete state) Markovian, explicit formulae are well known. Unfortunately, in more general cases availability is often a complicated function of the parameters without closed form solution. Thus, the computation of sensitivity measures would be time-consuming or even infeasible. In this paper, we show how Sobol and other related sensitivity measures can be cheaply computed to measure how changes in the model inputs (failure/repair times) influence the outputs (availability measure). We use a Bayesian framework, called the Bayesian analysis of computer code output (BACCO) which is based on using the Gaussian process as an emulator (i.e., an approximation) of complex models/functions. This approach allows effective sensitivity analysis to be achieved by using far smaller numbers of model runs than other methods. The emulator-based sensitivity measure is used to examine the influence of the failure and repair densities' parameters on the system availability. We discuss how to apply the methods practically in the reliability context, considering in particular the selection of parameters and prior distributions and how we can ensure these may be considered independent—one of the key assumptions of the Sobol approach. The method is illustrated on several examples, and we discuss the further implications of the technique for reliability and maintenance analysis

  20. 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.

  1. 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.)

  2. 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.)

  3. Flexural modeling of the elastic lithosphere at an ocean trench: A parameter sensitivity analysis using analytical solutions

    Science.gov (United States)

    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.

  4. Time-dependent reliability sensitivity analysis of motion mechanisms

    International Nuclear Information System (INIS)

    Wei, Pengfei; Song, Jingwen; Lu, Zhenzhou; Yue, Zhufeng

    2016-01-01

    Reliability sensitivity analysis aims at identifying the source of structure/mechanism failure, and quantifying the effects of each random source or their distribution parameters on failure probability or reliability. In this paper, the time-dependent parametric reliability sensitivity (PRS) analysis as well as the global reliability sensitivity (GRS) analysis is introduced for the motion mechanisms. The PRS indices are defined as the partial derivatives of the time-dependent reliability w.r.t. the distribution parameters of each random input variable, and they quantify the effect of the small change of each distribution parameter on the time-dependent reliability. The GRS indices are defined for quantifying the individual, interaction and total contributions of the uncertainty in each random input variable to the time-dependent reliability. The envelope function method combined with the first order approximation of the motion error function is introduced for efficiently estimating the time-dependent PRS and GRS indices. Both the time-dependent PRS and GRS analysis techniques can be especially useful for reliability-based design. This significance of the proposed methods as well as the effectiveness of the envelope function method for estimating the time-dependent PRS and GRS indices are demonstrated with a four-bar mechanism and a car rack-and-pinion steering linkage. - Highlights: • Time-dependent parametric reliability sensitivity analysis is presented. • Time-dependent global reliability sensitivity analysis is presented for mechanisms. • The proposed method is especially useful for enhancing the kinematic reliability. • An envelope method is introduced for efficiently implementing the proposed methods. • The proposed method is demonstrated by two real planar mechanisms.

  5. 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

  6. 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.

  7. Universally sloppy parameter sensitivities in systems biology models.

    Science.gov (United States)

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

    2007-10-01

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

  8. Sensitivity analysis of numerical solutions for environmental fluid problems

    International Nuclear Information System (INIS)

    Tanaka, Nobuatsu; Motoyama, Yasunori

    2003-01-01

    In this study, we present a new numerical method to quantitatively analyze the error of numerical solutions by using the sensitivity analysis. If a reference case of typical parameters is one calculated with the method, no additional calculation is required to estimate the results of the other numerical parameters such as more detailed solutions. Furthermore, we can estimate the strict solution from the sensitivity analysis results and can quantitatively evaluate the reliability of the numerical solution by calculating the numerical error. (author)

  9. 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

  10. Uncertainty Quantification and Global Sensitivity Analysis of Subsurface Flow Parameters to Gravimetric Variations During Pumping Tests in Unconfined Aquifers

    Science.gov (United States)

    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

  11. Sensitivity Analysis of an Agent-Based Model of Culture's Consequences for Trade

    NARCIS (Netherlands)

    Burgers, S.L.G.E.; Jonker, C.M.; Hofstede, G.J.; Verwaart, D.

    2010-01-01

    This paper describes the analysis of an agent-based model’s sensitivity to changes in parameters that describe the agents’ cultural background, relational parameters, and parameters of the decision functions. As agent-based models may be very sensitive to small changes in parameter values, it is of

  12. Reliability of a new biokinetic model of zirconium in internal dosimetry: part II, parameter sensitivity analysis.

    Science.gov (United States)

    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.

  13. Histogram analysis derived from apparent diffusion coefficient (ADC) is more sensitive to reflect serological parameters in myositis than conventional ADC analysis.

    Science.gov (United States)

    Meyer, Hans Jonas; Emmer, Alexander; Kornhuber, Malte; Surov, Alexey

    2018-05-01

    Diffusion-weighted imaging (DWI) has the potential of being able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize tissues on MRI. The aim of this study was to correlate histogram parameters derived from apparent diffusion coefficient (ADC) maps with serological parameters in myositis. 16 patients with autoimmune myositis were included in this retrospective study. DWI was obtained on a 1.5 T scanner by using the b-values of 0 and 1000 s mm - 2 . Histogram analysis was performed as a whole muscle measurement by using a custom-made Matlab-based application. The following ADC histogram parameters were estimated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, and the following percentiles ADCp10, ADCp25, ADCp75, ADCp90, as well histogram parameters kurtosis, skewness, and entropy. In all patients, the blood sample was acquired within 3 days to the MRI. The following serological parameters were estimated: alanine aminotransferase, aspartate aminotransferase, creatine kinase, lactate dehydrogenase, C-reactive protein (CRP) and myoglobin. All patients were screened for Jo1-autobodies. Kurtosis correlated inversely with CRP (p = -0.55 and 0.03). Furthermore, ADCp10 and ADCp90 values tended to correlate with creatine kinase (p = -0.43, 0.11, and p = -0.42, = 0.12 respectively). In addition, ADCmean, p10, p25, median, mode, and entropy were different between Jo1-positive and Jo1-negative patients. ADC histogram parameters are sensitive for detection of muscle alterations in myositis patients. Advances in knowledge: This study identified that kurtosis derived from ADC maps is associated with CRP in myositis patients. Furthermore, several ADC histogram parameters are statistically different between Jo1-positive and Jo1-negative patients.

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

    KAUST Repository

    Boas, Sonja

    2015-01-01

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

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

    Science.gov (United States)

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

    2018-01-01

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

  16. Development of a System Analysis Toolkit for Sensitivity Analysis, Uncertainty Propagation, and Estimation of Parameter Distribution

    International Nuclear Information System (INIS)

    Heo, Jaeseok; Kim, Kyung Doo

    2015-01-01

    Statistical approaches to uncertainty quantification and sensitivity analysis are very important in estimating the safety margins for an engineering design application. This paper presents a system analysis and optimization toolkit developed by Korea Atomic Energy Research Institute (KAERI), which includes multiple packages of the sensitivity analysis and uncertainty quantification algorithms. In order to reduce the computing demand, multiple compute resources including multiprocessor computers and a network of workstations are simultaneously used. A Graphical User Interface (GUI) was also developed within the parallel computing framework for users to readily employ the toolkit for an engineering design and optimization problem. The goal of this work is to develop a GUI framework for engineering design and scientific analysis problems by implementing multiple packages of system analysis methods in the parallel computing toolkit. This was done by building an interface between an engineering simulation code and the system analysis software packages. The methods and strategies in the framework were designed to exploit parallel computing resources such as those found in a desktop multiprocessor workstation or a network of workstations. Available approaches in the framework include statistical and mathematical algorithms for use in science and engineering design problems. Currently the toolkit has 6 modules of the system analysis methodologies: deterministic and probabilistic approaches of data assimilation, uncertainty propagation, Chi-square linearity test, sensitivity analysis, and FFTBM

  17. Development of a System Analysis Toolkit for Sensitivity Analysis, Uncertainty Propagation, and Estimation of Parameter Distribution

    Energy Technology Data Exchange (ETDEWEB)

    Heo, Jaeseok; Kim, Kyung Doo [KAERI, Daejeon (Korea, Republic of)

    2015-05-15

    Statistical approaches to uncertainty quantification and sensitivity analysis are very important in estimating the safety margins for an engineering design application. This paper presents a system analysis and optimization toolkit developed by Korea Atomic Energy Research Institute (KAERI), which includes multiple packages of the sensitivity analysis and uncertainty quantification algorithms. In order to reduce the computing demand, multiple compute resources including multiprocessor computers and a network of workstations are simultaneously used. A Graphical User Interface (GUI) was also developed within the parallel computing framework for users to readily employ the toolkit for an engineering design and optimization problem. The goal of this work is to develop a GUI framework for engineering design and scientific analysis problems by implementing multiple packages of system analysis methods in the parallel computing toolkit. This was done by building an interface between an engineering simulation code and the system analysis software packages. The methods and strategies in the framework were designed to exploit parallel computing resources such as those found in a desktop multiprocessor workstation or a network of workstations. Available approaches in the framework include statistical and mathematical algorithms for use in science and engineering design problems. Currently the toolkit has 6 modules of the system analysis methodologies: deterministic and probabilistic approaches of data assimilation, uncertainty propagation, Chi-square linearity test, sensitivity analysis, and FFTBM.

  18. 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.

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

    Science.gov (United States)

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

    2012-12-01

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

  20. The role of sensitivity analysis in assessing uncertainty

    International Nuclear Information System (INIS)

    Crick, M.J.; Hill, M.D.

    1987-01-01

    Outside the specialist world of those carrying out performance assessments considerable confusion has arisen about the meanings of sensitivity analysis and uncertainty analysis. In this paper we attempt to reduce this confusion. We then go on to review approaches to sensitivity analysis within the context of assessing uncertainty, and to outline the types of test available to identify sensitive parameters, together with their advantages and disadvantages. The views expressed in this paper are those of the authors; they have not been formally endorsed by the National Radiological Protection Board and should not be interpreted as Board advice

  1. 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)

  2. Adjoint sensitivity analysis of plasmonic structures using the FDTD method.

    Science.gov (United States)

    Zhang, Yu; Ahmed, Osman S; Bakr, Mohamed H

    2014-05-15

    We present an adjoint variable method for estimating the sensitivities of arbitrary responses with respect to the parameters of dispersive discontinuities in nanoplasmonic devices. Our theory is formulated in terms of the electric field components at the vicinity of perturbed discontinuities. The adjoint sensitivities are computed using at most one extra finite-difference time-domain (FDTD) simulation regardless of the number of parameters. Our approach is illustrated through the sensitivity analysis of an add-drop coupler consisting of a square ring resonator between two parallel waveguides. The computed adjoint sensitivities of the scattering parameters are compared with those obtained using the accurate but computationally expensive central finite difference approach.

  3. The EVEREST project: sensitivity analysis of geological disposal systems

    International Nuclear Information System (INIS)

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

    1997-01-01

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

  4. Discrete non-parametric kernel estimation for global sensitivity analysis

    International Nuclear Information System (INIS)

    Senga Kiessé, Tristan; Ventura, Anne

    2016-01-01

    This work investigates the discrete kernel approach for evaluating the contribution of the variance of discrete input variables to the variance of model output, via analysis of variance (ANOVA) decomposition. Until recently only the continuous kernel approach has been applied as a metamodeling approach within sensitivity analysis framework, for both discrete and continuous input variables. Now the discrete kernel estimation is known to be suitable for smoothing discrete functions. We present a discrete non-parametric kernel estimator of ANOVA decomposition of a given model. An estimator of sensitivity indices is also presented with its asymtotic convergence rate. Some simulations on a test function analysis and a real case study from agricultural have shown that the discrete kernel approach outperforms the continuous kernel one for evaluating the contribution of moderate or most influential discrete parameters to the model output. - Highlights: • We study a discrete kernel estimation for sensitivity analysis of a model. • A discrete kernel estimator of ANOVA decomposition of the model is presented. • Sensitivity indices are calculated for discrete input parameters. • An estimator of sensitivity indices is also presented with its convergence rate. • An application is realized for improving the reliability of environmental models.

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

    International Nuclear Information System (INIS)

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

    1988-01-01

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

  6. Probabilistic sensitivity analysis in health economics.

    Science.gov (United States)

    Baio, Gianluca; Dawid, A Philip

    2015-12-01

    Health economic evaluations have recently become an important part of the clinical and medical research process and have built upon more advanced statistical decision-theoretic foundations. In some contexts, it is officially required that uncertainty about both parameters and observable variables be properly taken into account, increasingly often by means of Bayesian methods. Among these, probabilistic sensitivity analysis has assumed a predominant role. The objective of this article is to review the problem of health economic assessment from the standpoint of Bayesian statistical decision theory with particular attention to the philosophy underlying the procedures for sensitivity analysis. © The Author(s) 2011.

  7. Sensitivity Analysis in Sequential Decision Models.

    Science.gov (United States)

    Chen, Qiushi; Ayer, Turgay; Chhatwal, Jagpreet

    2017-02-01

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

  8. Local sensitivity analysis for inverse problems solved by singular value decomposition

    Science.gov (United States)

    Hill, M.C.; Nolan, B.T.

    2010-01-01

    Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by

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

    Science.gov (United States)

    Leonard, J. I.

    1974-01-01

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

  10. Investigation, sensitivity analysis, and multi-objective optimization of effective parameters on temperature and force in robotic drilling cortical bone.

    Science.gov (United States)

    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

  11. Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

    Directory of Open Access Journals (Sweden)

    Rupert Faltermeier

    2015-01-01

    Full Text Available Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP and intracranial pressure (ICP. Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP, with the outcome of the patients represented by the Glasgow Outcome Scale (GOS. For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

  12. Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

    Science.gov (United States)

    Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

    2015-01-01

    Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

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

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

    Science.gov (United States)

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

    2018-04-01

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

  15. Sensitivity Analysis of Methane Hydrate Reservoirs: Effects of Reservoir Parameters on Gas Productivity and Economics

    Science.gov (United States)

    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

  16. Uncertainty quantification and sensitivity analysis with CASL Core Simulator VERA-CS

    International Nuclear Information System (INIS)

    Brown, C.S.; Zhang, Hongbin

    2016-01-01

    VERA-CS (Virtual Environment for Reactor Applications, Core Simulator) is a coupled neutron transport and thermal-hydraulics code under development by the Consortium for Advanced Simulation of Light Water Reactors (CASL). An approach to uncertainty quantification and sensitivity analysis with VERA-CS was developed and a new toolkit was created to perform uncertainty quantification and sensitivity analysis. A 2 × 2 fuel assembly model was developed and simulated by VERA-CS, and uncertainty quantification and sensitivity analysis were performed with fourteen uncertain input parameters. The minimum departure from nucleate boiling ratio (MDNBR), maximum fuel center-line temperature, and maximum outer clad surface temperature were chosen as the selected figures of merit. Pearson, Spearman, and partial correlation coefficients were considered for all of the figures of merit in sensitivity analysis and coolant inlet temperature was consistently the most influential parameter. Parameters used as inputs to the critical heat flux calculation with the W-3 correlation were shown to be the most influential on the MDNBR, maximum fuel center-line temperature, and maximum outer clad surface temperature.

  17. Sensitivity Analysis of FEAST-Metal Fuel Performance Code: Initial Results

    International Nuclear Information System (INIS)

    Edelmann, Paul Guy; Williams, Brian J.; Unal, Cetin; Yacout, Abdellatif

    2012-01-01

    This memo documents the completion of the LANL milestone, M3FT-12LA0202041, describing methodologies and initial results using FEAST-Metal. The FEAST-Metal code calculations for this work are being conducted at LANL in support of on-going activities related to sensitivity analysis of fuel performance codes. The objective is to identify important macroscopic parameters of interest to modeling and simulation of metallic fuel performance. This report summarizes our preliminary results for the sensitivity analysis using 6 calibration datasets for metallic fuel developed at ANL for EBR-II experiments. Sensitivity ranking methodology was deployed to narrow down the selected parameters for the current study. There are approximately 84 calibration parameters in the FEAST-Metal code, of which 32 were ultimately used in Phase II of this study. Preliminary results of this sensitivity analysis led to the following ranking of FEAST models for future calibration and improvements: fuel conductivity, fission gas transport/release, fuel creep, and precipitation kinetics. More validation data is needed to validate calibrated parameter distributions for future uncertainty quantification studies with FEAST-Metal. Results of this study also served to point out some code deficiencies and possible errors, and these are being investigated in order to determine root causes and to improve upon the existing code models.

  18. MOVES sensitivity analysis update : Transportation Research Board Summer Meeting 2012 : ADC-20 Air Quality Committee

    Science.gov (United States)

    2012-01-01

    OVERVIEW OF PRESENTATION : Evaluation Parameters : EPAs Sensitivity Analysis : Comparison to Baseline Case : MOVES Sensitivity Run Specification : MOVES Sensitivity Input Parameters : Results : Uses of Study

  19. 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.

  20. SENSIT: a cross-section and design sensitivity and uncertainty analysis code

    International Nuclear Information System (INIS)

    Gerstl, S.A.W.

    1980-01-01

    SENSIT computes the sensitivity and uncertainty of a calculated integral response (such as a dose rate) due to input cross sections and their uncertainties. Sensitivity profiles are computed for neutron and gamma-ray reaction cross sections of standard multigroup cross section sets and for secondary energy distributions (SEDs) of multigroup scattering matrices. In the design sensitivity mode, SENSIT computes changes in an integral response due to design changes and gives the appropriate sensitivity coefficients. Cross section uncertainty analyses are performed for three types of input data uncertainties: cross-section covariance matrices for pairs of multigroup reaction cross sections, spectral shape uncertainty parameters for secondary energy distributions (integral SED uncertainties), and covariance matrices for energy-dependent response functions. For all three types of data uncertainties SENSIT computes the resulting variance and estimated standard deviation in an integral response of interest, on the basis of generalized perturbation theory. SENSIT attempts to be more comprehensive than earlier sensitivity analysis codes, such as SWANLAKE

  1. Sensitivity analysis of simulated SOA loadings using a variance-based statistical approach: SENSITIVITY ANALYSIS OF SOA

    Energy Technology Data Exchange (ETDEWEB)

    Shrivastava, Manish [Pacific Northwest National Laboratory, Richland Washington USA; Zhao, Chun [Pacific Northwest National Laboratory, Richland Washington USA; Easter, Richard C. [Pacific Northwest National Laboratory, Richland Washington USA; Qian, Yun [Pacific Northwest National Laboratory, Richland Washington USA; Zelenyuk, Alla [Pacific Northwest National Laboratory, Richland Washington USA; Fast, Jerome D. [Pacific Northwest National Laboratory, Richland Washington USA; Liu, Ying [Pacific Northwest National Laboratory, Richland Washington USA; Zhang, Qi [Department of Environmental Toxicology, University of California Davis, California USA; Guenther, Alex [Department of Earth System Science, University of California, Irvine California USA

    2016-04-08

    We investigate the sensitivity of secondary organic aerosol (SOA) loadings simulated by a regional chemical transport model to 7 selected tunable model parameters: 4 involving emissions of anthropogenic and biogenic volatile organic compounds, anthropogenic semi-volatile and intermediate volatility organics (SIVOCs), and NOx, 2 involving dry deposition of SOA precursor gases, and one involving particle-phase transformation of SOA to low volatility. We adopt a quasi-Monte Carlo sampling approach to effectively sample the high-dimensional parameter space, and perform a 250 member ensemble of simulations using a regional model, accounting for some of the latest advances in SOA treatments based on our recent work. We then conduct a variance-based sensitivity analysis using the generalized linear model method to study the responses of simulated SOA loadings to the tunable parameters. Analysis of SOA variance from all 250 simulations shows that the volatility transformation parameter, which controls whether particle-phase transformation of SOA from semi-volatile SOA to non-volatile is on or off, is the dominant contributor to variance of simulated surface-level daytime SOA (65% domain average contribution). We also split the simulations into 2 subsets of 125 each, depending on whether the volatility transformation is turned on/off. For each subset, the SOA variances are dominated by the parameters involving biogenic VOC and anthropogenic SIVOC emissions. Furthermore, biogenic VOC emissions have a larger contribution to SOA variance when the SOA transformation to non-volatile is on, while anthropogenic SIVOC emissions have a larger contribution when the transformation is off. NOx contributes less than 4.3% to SOA variance, and this low contribution is mainly attributed to dominance of intermediate to high NOx conditions throughout the simulated domain. The two parameters related to dry deposition of SOA precursor gases also have very low contributions to SOA variance

  2. Parametric sensitivity analysis for biochemical reaction networks based on pathwise information theory.

    Science.gov (United States)

    Pantazis, Yannis; Katsoulakis, Markos A; Vlachos, Dionisios G

    2013-10-22

    Stochastic modeling and simulation provide powerful predictive methods for the intrinsic understanding of fundamental mechanisms in complex biochemical networks. Typically, such mathematical models involve networks of coupled jump stochastic processes with a large number of parameters that need to be suitably calibrated against experimental data. In this direction, the parameter sensitivity analysis of reaction networks is an essential mathematical and computational tool, yielding information regarding the robustness and the identifiability of model parameters. However, existing sensitivity analysis approaches such as variants of the finite difference method can have an overwhelming computational cost in models with a high-dimensional parameter space. We develop a sensitivity analysis methodology suitable for complex stochastic reaction networks with a large number of parameters. The proposed approach is based on Information Theory methods and relies on the quantification of information loss due to parameter perturbations between time-series distributions. For this reason, we need to work on path-space, i.e., the set consisting of all stochastic trajectories, hence the proposed approach is referred to as "pathwise". The pathwise sensitivity analysis method is realized by employing the rigorously-derived Relative Entropy Rate, which is directly computable from the propensity functions. A key aspect of the method is that an associated pathwise Fisher Information Matrix (FIM) is defined, which in turn constitutes a gradient-free approach to quantifying parameter sensitivities. The structure of the FIM turns out to be block-diagonal, revealing hidden parameter dependencies and sensitivities in reaction networks. As a gradient-free method, the proposed sensitivity analysis provides a significant advantage when dealing with complex stochastic systems with a large number of parameters. In addition, the knowledge of the structure of the FIM can allow to efficiently address

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

    Science.gov (United States)

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

    2010-10-24

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

  4. Sensitivity Analysis of Viscoelastic Structures

    Directory of Open Access Journals (Sweden)

    A.M.G. de Lima

    2006-01-01

    Full Text Available In the context of control of sound and vibration of mechanical systems, the use of viscoelastic materials has been regarded as a convenient strategy in many types of industrial applications. Numerical models based on finite element discretization have been frequently used in the analysis and design of complex structural systems incorporating viscoelastic materials. Such models must account for the typical dependence of the viscoelastic characteristics on operational and environmental parameters, such as frequency and temperature. In many applications, including optimal design and model updating, sensitivity analysis based on numerical models is a very usefull tool. In this paper, the formulation of first-order sensitivity analysis of complex frequency response functions is developed for plates treated with passive constraining damping layers, considering geometrical characteristics, such as the thicknesses of the multi-layer components, as design variables. Also, the sensitivity of the frequency response functions with respect to temperature is introduced. As an example, response derivatives are calculated for a three-layer sandwich plate and the results obtained are compared with first-order finite-difference approximations.

  5. Understanding dynamics using sensitivity analysis: caveat and solution

    Science.gov (United States)

    2011-01-01

    Background Parametric sensitivity analysis (PSA) has become one of the most commonly used tools in computational systems biology, in which the sensitivity coefficients are used to study the parametric dependence of biological models. As many of these models describe dynamical behaviour of biological systems, the PSA has subsequently been used to elucidate important cellular processes that regulate this dynamics. However, in this paper, we show that the PSA coefficients are not suitable in inferring the mechanisms by which dynamical behaviour arises and in fact it can even lead to incorrect conclusions. Results A careful interpretation of parametric perturbations used in the PSA is presented here to explain the issue of using this analysis in inferring dynamics. In short, the PSA coefficients quantify the integrated change in the system behaviour due to persistent parametric perturbations, and thus the dynamical information of when a parameter perturbation matters is lost. To get around this issue, we present a new sensitivity analysis based on impulse perturbations on system parameters, which is named impulse parametric sensitivity analysis (iPSA). The inability of PSA and the efficacy of iPSA in revealing mechanistic information of a dynamical system are illustrated using two examples involving switch activation. Conclusions The interpretation of the PSA coefficients of dynamical systems should take into account the persistent nature of parametric perturbations involved in the derivation of this analysis. The application of PSA to identify the controlling mechanism of dynamical behaviour can be misleading. By using impulse perturbations, introduced at different times, the iPSA provides the necessary information to understand how dynamics is achieved, i.e. which parameters are essential and when they become important. PMID:21406095

  6. 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

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

    Science.gov (United States)

    Leterme, Bertrand; Jacques, Diederik

    2015-11-01

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

  8. Application of Sensitivity Analysis in Design of Sustainable Buildings

    DEFF Research Database (Denmark)

    Heiselberg, Per; Brohus, Henrik; Rasmussen, Henrik

    2009-01-01

    satisfies the design objectives and criteria. In the design of sustainable buildings, it is beneficial to identify the most important design parameters in order to more efficiently develop alternative design solutions or reach optimized design solutions. Sensitivity analyses make it possible to identify...... possible to influence the most important design parameters. A methodology of sensitivity analysis is presented and an application example is given for design of an office building in Denmark....

  9. 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.

  10. Sensitivity/uncertainty analysis of a borehole scenario comparing Latin Hypercube Sampling and deterministic sensitivity approaches

    International Nuclear Information System (INIS)

    Harper, W.V.; Gupta, S.K.

    1983-10-01

    A computer code was used to study steady-state flow for a hypothetical borehole scenario. The model consists of three coupled equations with only eight parameters and three dependent variables. This study focused on steady-state flow as the performance measure of interest. Two different approaches to sensitivity/uncertainty analysis were used on this code. One approach, based on Latin Hypercube Sampling (LHS), is a statistical sampling method, whereas, the second approach is based on the deterministic evaluation of sensitivities. The LHS technique is easy to apply and should work well for codes with a moderate number of parameters. Of deterministic techniques, the direct method is preferred when there are many performance measures of interest and a moderate number of parameters. The adjoint method is recommended when there are a limited number of performance measures and an unlimited number of parameters. This unlimited number of parameters capability can be extremely useful for finite element or finite difference codes with a large number of grid blocks. The Office of Nuclear Waste Isolation will use the technique most appropriate for an individual situation. For example, the adjoint method may be used to reduce the scope to a size that can be readily handled by a technique such as LHS. Other techniques for sensitivity/uncertainty analysis, e.g., kriging followed by conditional simulation, will be used also. 15 references, 4 figures, 9 tables

  11. 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 ...

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

    International Nuclear Information System (INIS)

    Spiessl, Sabine; Becker, Dirk-Alexander

    2017-06-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Spiessl, Sabine; Becker, Dirk-Alexander

    2017-06-15

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

  14. Sensitivity analysis of longitudinal cracking on asphalt pavement using MEPDG in permafrost region

    Directory of Open Access Journals (Sweden)

    Chen Zhang

    2015-02-01

    Full Text Available Longitudinal cracking is one of the most important distresses of asphalt pavement in permafrost regions. The sensitivity analysis of design parameters for asphalt pavement can be used to study the influence of every parameter on longitudinal cracking, which can help optimizing the design of the pavement structure. In this study, 20 test sections of Qinghai–Tibet Highway were selected to conduct the sensitivity analysis of longitudinal cracking on material parameter based on Mechanistic-Empirical Pavement Design Guide (MEPDG and single factorial sensitivity analysis method. Some computer aided engineering (CAE simulation techniques, such as the Latin hypercube sampling (LHS technique and the multiple regression analysis are used as auxiliary means. Finally, the sensitivity spectrum of material parameter on longitudinal cracking was established. The result shows the multiple regression analysis can be used to determine the remarkable influence factor more efficiently and to process the qualitative analysis when applying the MEPDG software in sensitivity analysis of longitudinal cracking in permafrost regions. The effect weights of the three parameters on longitudinal cracking in descending order are air void, effective binder content and PG grade. The influence of air void on top layer is bigger than that on middle layer and bottom layer. The influence of effective asphalt content on top layer is bigger than that on middle layer and bottom layer, and the influence of bottom layer is slightly bigger than middle layer. The accumulated value of longitudinal cracking on middle layer and bottom layer in the design life would begin to increase when the design temperature of PG grade increased.

  15. Sensitivity analysis of a complex, proposed geologic waste disposal system using the Fourier Amplitude Sensitivity Test method

    International Nuclear Information System (INIS)

    Lu Yichi; Mohanty, Sitakanta

    2001-01-01

    The Fourier Amplitude Sensitivity Test (FAST) method has been used to perform a sensitivity analysis of a computer model developed for conducting total system performance assessment of the proposed high-level nuclear waste repository at Yucca Mountain, Nevada, USA. The computer model has a large number of random input parameters with assigned probability density functions, which may or may not be uniform, for representing data uncertainty. The FAST method, which was previously applied to models with parameters represented by the uniform probability distribution function only, has been modified to be applied to models with nonuniform probability distribution functions. Using an example problem with a small input parameter set, several aspects of the FAST method, such as the effects of integer frequency sets and random phase shifts in the functional transformations, and the number of discrete sampling points (equivalent to the number of model executions) on the ranking of the input parameters have been investigated. Because the number of input parameters of the computer model under investigation is too large to be handled by the FAST method, less important input parameters were first screened out using the Morris method. The FAST method was then used to rank the remaining parameters. The validity of the parameter ranking by the FAST method was verified using the conditional complementary cumulative distribution function (CCDF) of the output. The CCDF results revealed that the introduction of random phase shifts into the functional transformations, proposed by previous investigators to disrupt the repetitiveness of search curves, does not necessarily improve the sensitivity analysis results because it destroys the orthogonality of the trigonometric functions, which is required for Fourier analysis

  16. Thermo-economic analysis of combined power plants with changing economic parameters

    International Nuclear Information System (INIS)

    Bidini, G.; Desideri, U.; Facchini, B.

    1991-01-01

    A method of thermo-economic analysis for the choice of optimal thermodynamic parameters of steam bottoming cycles in combined cycle power plants is presented. By keeping the thermodynamic aspects separated from the economic aspects, this method allows designers to easily perform a sensitivity analysis of the change in the economic parameters

  17. 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.

  18. 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

  19. Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

    Science.gov (United States)

    Rakovec, O.; Hill, M. C.; Clark, M. P.; Weerts, A. H.; Teuling, A. J.; Uijlenhoet, R.

    2014-01-01

    This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based "local" methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative "bucket-style" hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.

  20. Linear regression and sensitivity analysis in nuclear reactor design

    International Nuclear Information System (INIS)

    Kumar, Akansha; Tsvetkov, Pavel V.; McClarren, Ryan G.

    2015-01-01

    Highlights: • Presented a benchmark for the applicability of linear regression to complex systems. • Applied linear regression to a nuclear reactor power system. • Performed neutronics, thermal–hydraulics, and energy conversion using Brayton’s cycle for the design of a GCFBR. • Performed detailed sensitivity analysis to a set of parameters in a nuclear reactor power system. • Modeled and developed reactor design using MCNP, regression using R, and thermal–hydraulics in Java. - Abstract: The paper presents a general strategy applicable for sensitivity analysis (SA), and uncertainity quantification analysis (UA) of parameters related to a nuclear reactor design. This work also validates the use of linear regression (LR) for predictive analysis in a nuclear reactor design. The analysis helps to determine the parameters on which a LR model can be fit for predictive analysis. For those parameters, a regression surface is created based on trial data and predictions are made using this surface. A general strategy of SA to determine and identify the influential parameters those affect the operation of the reactor is mentioned. Identification of design parameters and validation of linearity assumption for the application of LR of reactor design based on a set of tests is performed. The testing methods used to determine the behavior of the parameters can be used as a general strategy for UA, and SA of nuclear reactor models, and thermal hydraulics calculations. A design of a gas cooled fast breeder reactor (GCFBR), with thermal–hydraulics, and energy transfer has been used for the demonstration of this method. MCNP6 is used to simulate the GCFBR design, and perform the necessary criticality calculations. Java is used to build and run input samples, and to extract data from the output files of MCNP6, and R is used to perform regression analysis and other multivariate variance, and analysis of the collinearity of data

  1. The SSI TOOLBOX Source Term Model SOSIM - Screening for important radionuclides and parameter sensitivity analysis

    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.

  2. Sensitivity Analysis of Fire Dynamics Simulation

    DEFF Research Database (Denmark)

    Brohus, Henrik; Nielsen, Peter V.; Petersen, Arnkell J.

    2007-01-01

    (Morris method). The parameters considered are selected among physical parameters and program specific parameters. The influence on the calculation result as well as the CPU time is considered. It is found that the result is highly sensitive to many parameters even though the sensitivity varies...

  3. Application of adjoint sensitivity analysis to nuclear reactor fuel rod performance

    International Nuclear Information System (INIS)

    Wilderman, S.J.; Was, G.S.

    1984-01-01

    Adjoint sensitivity analysis in nuclear fuel behavior modeling is extended to operate on the entire power history for both Zircaloy and stainless steel cladding via the computer codes FCODE-ALPHA/SS and SCODE/SS. The sensitivities of key variables to input parameters are found to be highly non-intuitive and strongly dependent on the fuel-clad gap status and the history of the fuel during the cycle. The sensitivities of five key variables, clad circumferential stress and strain, fission gas release, fuel centerline temperature and fuel-clad gap, to eleven input parameters are studied. The most important input parameters (yielding significances between 1 and 100) are fabricated clad inner and outer radii and fuel radius. The least important significances (less than 0.01) are the time since reactor start-up and fuel-burnup densification rate. Intermediate to these are fabricated fuel porosity, linear heat generation rate, the power history scale factor, clad outer temperature, fill gas pressure and coolant pressure. Stainless steel and Zircaloy have similar sensitivities at start-up but these diverges a burnup proceeds due to the effect of the higher creep rate of Zircaloy which causes the system to be more responsive to changes in input parameters. The value of adjoint sensitivity analysis lies in its capability of uncovering dependencies of fuel variables on input parameters that cannot be determined by a sequential thought process. (orig.)

  4. Sensitivity Analysis of Vagus Nerve Stimulation Parameters on Acute Cardiac Autonomic Responses: Chronotropic, Inotropic and Dromotropic Effects.

    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

  5. Sensitivity analysis of the reactor safety study. Final report

    International Nuclear Information System (INIS)

    Parkinson, W.J.; Rasmussen, N.C.; Hinkle, W.D.

    1979-01-01

    The Reactor Safety Study (RSS) or Wash 1400 developed a methodology estimating the public risk from light water nuclear reactors. In order to give further insights into this study, a sensitivity analysis has been performed to determine the significant contributors to risk for both the PWR and BWR. The sensitivity to variation of the point values of the failure probabilities reported in the RSS was determined for the safety systems identified therein, as well as for many of the generic classes from which individual failures contributed to system failures. Increasing as well as decreasing point values were considered. An analysis of the sensitivity to increasing uncertainty in system failure probabilities was also performed. The sensitivity parameters chosen were release category probabilities, core melt probability, and the risk parameters of early fatalities, latent cancers and total property damage. The latter three are adequate for describing all public risks identified in the RSS. The results indicate reductions of public risk by less than a factor of two for factor reductions in system or generic failure probabilities as high as one hundred. There also appears to be more benefit in monitoring the most sensitive systems to verify adherence to RSS failure rates than to backfitting present reactors. The sensitivity analysis results do indicate, however, possible benefits in reducing human error rates

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

    Science.gov (United States)

    Siamphukdee, Kanjana; Collins, Frank; Zou, Roger

    2013-06-01

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

  7. DAKOTA, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis:version 4.0 reference manual

    Energy Technology Data Exchange (ETDEWEB)

    Griffin, Joshua D. (Sandai National Labs, Livermore, CA); Eldred, Michael Scott; Martinez-Canales, Monica L. (Sandai National Labs, Livermore, CA); Watson, Jean-Paul; Kolda, Tamara Gibson (Sandai National Labs, Livermore, CA); Adams, Brian M.; Swiler, Laura Painton; Williams, Pamela J. (Sandai National Labs, Livermore, CA); Hough, Patricia Diane (Sandai National Labs, Livermore, CA); Gay, David M.; Dunlavy, Daniel M.; Eddy, John P.; Hart, William Eugene; Guinta, Anthony A.; Brown, Shannon L.

    2006-10-01

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a reference manual for the commands specification for the DAKOTA software, providing input overviews, option descriptions, and example specifications.

  8. A comprehensive sensitivity and uncertainty analysis of a milk drying process

    DEFF Research Database (Denmark)

    Ferrari, A.; Gutiérrez, S.; Sin, G.

    2015-01-01

    A simple steady state model of a milk drying process was built to help process understanding. It involves a spray chamber and also internal/external fluid beds. The model was subjected to a statistical analysis for quality assurance using sensitivity analysis (SA) of inputs/parameters, identifiab......A simple steady state model of a milk drying process was built to help process understanding. It involves a spray chamber and also internal/external fluid beds. The model was subjected to a statistical analysis for quality assurance using sensitivity analysis (SA) of inputs...... technique. SA results provide evidence towards over-parameterization in the model, and the chamber inlet dry bulb air temperature was the variable (input) with the highest sensitivity. IA results indicated that at most 4 parameters are identifiable: two from spray chamber and one from each fluid bed dryer...

  9. Sensitivity Analysis of the USLE Soil Erodibility Factor to Its Determining Parameters

    Science.gov (United States)

    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

  10. The sensitivity and significance analysis of parameters in the model of pH regulation on lactic acid production by Lactobacillus bulgaricus.

    Science.gov (United States)

    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.

  11. Sensitivity analysis

    Science.gov (United States)

    ... page: //medlineplus.gov/ency/article/003741.htm Sensitivity analysis To use the sharing features on this page, please enable JavaScript. Sensitivity analysis determines the effectiveness of antibiotics against microorganisms (germs) ...

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

    Science.gov (United States)

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

    2017-12-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  14. Sensitivity analysis of EQ3

    International Nuclear Information System (INIS)

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

    1990-01-01

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

  15. Sensitivity analysis of a greedy heuristic for knapsack problems

    NARCIS (Netherlands)

    Ghosh, D; Chakravarti, N; Sierksma, G

    2006-01-01

    In this paper, we carry out parametric analysis as well as a tolerance limit based sensitivity analysis of a greedy heuristic for two knapsack problems-the 0-1 knapsack problem and the subset sum problem. We carry out the parametric analysis based on all problem parameters. In the tolerance limit

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

    Science.gov (United States)

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

    2013-01-01

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

  17. Therapeutic Implications from Sensitivity Analysis of Tumor Angiogenesis Models

    Science.gov (United States)

    Poleszczuk, Jan; Hahnfeldt, Philip; Enderling, Heiko

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    E. M. Enderlin

    2013-10-01

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

  19. Sensitivity analysis for hydrology and pesticide supply towards the river in SWAT

    Science.gov (United States)

    Holvoet, K.; van Griensven, A.; Seuntjens, P.; Vanrolleghem, P. A.

    The dynamic behaviour of pesticides in river systems strongly depends on varying climatological conditions and agricultural management practices. To describe this behaviour at the river-basin scale, integrated hydrological and water quality models are needed. A crucial step in understanding the various processes determining pesticide fate is to perform a sensitivity analysis. Sensitivity analysis for hydrology and pesticide supply in SWAT (Soil and Water Assessment Tool) will provide useful support for the development of a reliable hydrological model and will give insight in which parameters are most sensitive concerning pesticide supply towards rivers. The study was performed on the Nil catchment in Belgium. In this study we utilised an LH-OAT sensitivity analysis. The LH-OAT method combines the One-factor-At-a-Time (OAT) design and Latin Hypercube (LH) sampling by taking the Latin Hypercube samples as initial points for an OAT design. By means of the LH-OAT sensitivity analysis, the dominant hydrological parameters were determined and a reduction of the number of model parameters was performed. Dominant hydrological parameters were the curve number (CN2), the surface runoff lag (surlag), the recharge to deep aquifer (rchrg_dp) and the threshold depth of water in the shallow aquifer (GWQMN). Next, the selected parameters were estimated by manual calibration. Hereby, the Nash-Sutcliffe coefficient of efficiency improved from an initial value of -22.4 to +0.53. In the second part, sensitivity analyses were performed to provide insight in which parameters or model inputs contribute most to variance in pesticide output. The results of this study show that for the Nil catchment, hydrologic parameters are dominant in controlling pesticide predictions. The other parameter that affects pesticide concentrations in surface water is ‘apfp_pest’, which meaning was changed into a parameter that controls direct losses to the river system (e.g., through the clean up of spray

  20. Sequential designs for sensitivity analysis of functional inputs in computer experiments

    International Nuclear Information System (INIS)

    Fruth, J.; Roustant, O.; Kuhnt, S.

    2015-01-01

    Computer experiments are nowadays commonly used to analyze industrial processes aiming at achieving a wanted outcome. Sensitivity analysis plays an important role in exploring the actual impact of adjustable parameters on the response variable. In this work we focus on sensitivity analysis of a scalar-valued output of a time-consuming computer code depending on scalar and functional input parameters. We investigate a sequential methodology, based on piecewise constant functions and sequential bifurcation, which is both economical and fully interpretable. The new approach is applied to a sheet metal forming problem in three sequential steps, resulting in new insights into the behavior of the forming process over time. - Highlights: • Sensitivity analysis method for functional and scalar inputs is presented. • We focus on the discovery of most influential parts of the functional domain. • We investigate economical sequential methodology based on piecewise constant functions. • Normalized sensitivity indices are introduced and investigated theoretically. • Successful application to sheet metal forming on two functional inputs

  1. Predicting the fate of micropollutants during wastewater treatment: Calibration and sensitivity analysis.

    Science.gov (United States)

    Baalbaki, Zeina; Torfs, Elena; Yargeau, Viviane; Vanrolleghem, Peter A

    2017-12-01

    The presence of micropollutants in the environment and their toxic impacts on the aquatic environment have raised concern about their inefficient removal in wastewater treatment plants. In this study, the fate of micropollutants of four different classes was simulated in a conventional activated sludge plant using a bioreactor micropollutant fate model coupled to a settler model. The latter was based on the Bürger-Diehl model extended for the first time to include micropollutant fate processes. Calibration of model parameters was completed by matching modelling results with full-scale measurements (i.e. including aqueous and particulate phase concentrations of micropollutants) obtained from a 4-day sampling campaign. Modelling results showed that further biodegradation takes place in the sludge blanket of the settler for the highly biodegradable caffeine, underlining the need for a reactive settler model. The adopted Monte Carlo based calibration approach also provided an overview of the model's global sensitivity to the parameters. This analysis showed that for each micropollutant and according to the dominant fate process, a different set of one or more parameters had a significant impact on the model fit, justifying the selection of parameter subsets for model calibration. A dynamic local sensitivity analysis was also performed with the calibrated parameters. This analysis supported the conclusions from the global sensitivity and provided guidance for future sampling campaigns. This study expands the understanding of micropollutant fate models when applied to different micropollutants, in terms of global and local sensitivity to model parameters, as well as the identifiability of the parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Quantifying Parameter Sensitivity, Interaction and Transferability in Hydrologically Enhanced Versions of Noah-LSM over Transition Zones

    Science.gov (United States)

    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.

  3. Rapid Debris Analysis Project Task 3 Final Report - Sensitivity of Fallout to Source Parameters, Near-Detonation Environment Material Properties, Topography, and Meteorology

    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.

  4. Application of Sensitivity Analysis in Design of Integrated Building Concepts

    DEFF Research Database (Denmark)

    Heiselberg, Per; Brohus, Henrik; Hesselholt, Allan Tind

    2007-01-01

    analysis makes it possible to identify the most important parameters in relation to building performance and to focus design and optimization of integrated building concepts on these fewer, but most important parameters. The sensitivity analyses will typically be performed at a reasonably early stage...... the design requirements and objectives. In the design of integrated building concepts it is beneficial to identify the most important design parameters in order to more efficiently develop alternative design solutions or more efficiently perform an optimization of the building performance. The sensitivity...

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

    Directory of Open Access Journals (Sweden)

    Y. Tang

    2007-01-01

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

  6. Parameter sensitivity analysis of the mixed Green-Ampt/Curve-Number method for rainfall excess estimation in small ungauged catchments

    Science.gov (United States)

    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.

  7. Bayesian Sensitivity Analysis of a Nonlinear Dynamic Factor Analysis Model with Nonparametric Prior and Possible Nonignorable Missingness.

    Science.gov (United States)

    Tang, Niansheng; Chow, Sy-Miin; Ibrahim, Joseph G; Zhu, Hongtu

    2017-12-01

    Many psychological concepts are unobserved and usually represented as latent factors apprehended through multiple observed indicators. When multiple-subject multivariate time series data are available, dynamic factor analysis models with random effects offer one way of modeling patterns of within- and between-person variations by combining factor analysis and time series analysis at the factor level. Using the Dirichlet process (DP) as a nonparametric prior for individual-specific time series parameters further allows the distributional forms of these parameters to deviate from commonly imposed (e.g., normal or other symmetric) functional forms, arising as a result of these parameters' restricted ranges. Given the complexity of such models, a thorough sensitivity analysis is critical but computationally prohibitive. We propose a Bayesian local influence method that allows for simultaneous sensitivity analysis of multiple modeling components within a single fitting of the model of choice. Five illustrations and an empirical example are provided to demonstrate the utility of the proposed approach in facilitating the detection of outlying cases and common sources of misspecification in dynamic factor analysis models, as well as identification of modeling components that are sensitive to changes in the DP prior specification.

  8. Steady state likelihood ratio sensitivity analysis for stiff kinetic Monte Carlo simulations.

    Science.gov (United States)

    Núñez, M; Vlachos, D G

    2015-01-28

    Kinetic Monte Carlo simulation is an integral tool in the study of complex physical phenomena present in applications ranging from heterogeneous catalysis to biological systems to crystal growth and atmospheric sciences. Sensitivity analysis is useful for identifying important parameters and rate-determining steps, but the finite-difference application of sensitivity analysis is computationally demanding. Techniques based on the likelihood ratio method reduce the computational cost of sensitivity analysis by obtaining all gradient information in a single run. However, we show that disparity in time scales of microscopic events, which is ubiquitous in real systems, introduces drastic statistical noise into derivative estimates for parameters affecting the fast events. In this work, the steady-state likelihood ratio sensitivity analysis is extended to singularly perturbed systems by invoking partial equilibration for fast reactions, that is, by working on the fast and slow manifolds of the chemistry. Derivatives on each time scale are computed independently and combined to the desired sensitivity coefficients to considerably reduce the noise in derivative estimates for stiff systems. The approach is demonstrated in an analytically solvable linear system.

  9. Comparison of global sensitivity analysis techniques and importance measures in PSA

    International Nuclear Information System (INIS)

    Borgonovo, E.; Apostolakis, G.E.; Tarantola, S.; Saltelli, A.

    2003-01-01

    This paper discusses application and results of global sensitivity analysis techniques to probabilistic safety assessment (PSA) models, and their comparison to importance measures. This comparison allows one to understand whether PSA elements that are important to the risk, as revealed by importance measures, are also important contributors to the model uncertainty, as revealed by global sensitivity analysis. We show that, due to epistemic dependence, uncertainty and global sensitivity analysis of PSA models must be performed at the parameter level. A difficulty arises, since standard codes produce the calculations at the basic event level. We discuss both the indirect comparison through importance measures computed for basic events, and the direct comparison performed using the differential importance measure and the Fussell-Vesely importance at the parameter level. Results are discussed for the large LLOCA sequence of the advanced test reactor PSA

  10. 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.

  11. 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...

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

    Directory of Open Access Journals (Sweden)

    Jie Bao

    2015-12-01

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

  13. A comparison of Bayesian and Monte Carlo sensitivity analysis for unmeasured confounding.

    Science.gov (United States)

    McCandless, Lawrence C; Gustafson, Paul

    2017-08-15

    Bias from unmeasured confounding is a persistent concern in observational studies, and sensitivity analysis has been proposed as a solution. In the recent years, probabilistic sensitivity analysis using either Monte Carlo sensitivity analysis (MCSA) or Bayesian sensitivity analysis (BSA) has emerged as a practical analytic strategy when there are multiple bias parameters inputs. BSA uses Bayes theorem to formally combine evidence from the prior distribution and the data. In contrast, MCSA samples bias parameters directly from the prior distribution. Intuitively, one would think that BSA and MCSA ought to give similar results. Both methods use similar models and the same (prior) probability distributions for the bias parameters. In this paper, we illustrate the surprising finding that BSA and MCSA can give very different results. Specifically, we demonstrate that MCSA can give inaccurate uncertainty assessments (e.g. 95% intervals) that do not reflect the data's influence on uncertainty about unmeasured confounding. Using a data example from epidemiology and simulation studies, we show that certain combinations of data and prior distributions can result in dramatic prior-to-posterior changes in uncertainty about the bias parameters. This occurs because the application of Bayes theorem in a non-identifiable model can sometimes rule out certain patterns of unmeasured confounding that are not compatible with the data. Consequently, the MCSA approach may give 95% intervals that are either too wide or too narrow and that do not have 95% frequentist coverage probability. Based on our findings, we recommend that analysts use BSA for probabilistic sensitivity analysis. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  14. Application of Monte Carlo filtering method in regional sensitivity analysis of AASHTOWare Pavement ME design

    Directory of Open Access Journals (Sweden)

    Zhong Wu

    2017-04-01

    Full Text Available Since AASHTO released the Mechanistic-Empirical Pavement Design Guide (MEPDG for public review in 2004, many highway research agencies have performed sensitivity analyses using the prototype MEPDG design software. The information provided by the sensitivity analysis is essential for design engineers to better understand the MEPDG design models and to identify important input parameters for pavement design. In literature, different studies have been carried out based on either local or global sensitivity analysis methods, and sensitivity indices have been proposed for ranking the importance of the input parameters. In this paper, a regional sensitivity analysis method, Monte Carlo filtering (MCF, is presented. The MCF method maintains many advantages of the global sensitivity analysis, while focusing on the regional sensitivity of the MEPDG model near the design criteria rather than the entire problem domain. It is shown that the information obtained from the MCF method is more helpful and accurate in guiding design engineers in pavement design practices. To demonstrate the proposed regional sensitivity method, a typical three-layer flexible pavement structure was analyzed at input level 3. A detailed procedure to generate Monte Carlo runs using the AASHTOWare Pavement ME Design software was provided. The results in the example show that the sensitivity ranking of the input parameters in this study reasonably matches with that in a previous study under a global sensitivity analysis. Based on the analysis results, the strengths, practical issues, and applications of the MCF method were further discussed.

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

    NARCIS (Netherlands)

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

    2016-01-01

    Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle-tendon (MT) model parameters for each of

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

    NARCIS (Netherlands)

    Carbone, Vincenzo; van der Krogt, Marjolein; Koopman, Hubertus F.J.M.; Verdonschot, Nicolaas Jacobus Joseph

    2016-01-01

    Subject-specific musculoskeletal (MS) models of the lower extremity are essential for applications such as predicting the effects of orthopedic surgery. We performed an extensive sensitivity analysis to assess the effects of potential errors in Hill muscle–tendon (MT) model parameters for each of

  17. Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis:version 4.0 developers manual.

    Energy Technology Data Exchange (ETDEWEB)

    Griffin, Joshua D. (Sandia National lababoratory, Livermore, CA); Eldred, Michael Scott; Martinez-Canales, Monica L. (Sandia National lababoratory, Livermore, CA); Watson, Jean-Paul; Kolda, Tamara Gibson (Sandia National lababoratory, Livermore, CA); Giunta, Anthony Andrew; Adams, Brian M.; Swiler, Laura Painton; Williams, Pamela J. (Sandia National lababoratory, Livermore, CA); Hough, Patricia Diane (Sandia National lababoratory, Livermore, CA); Gay, David M.; Dunlavy, Daniel M.; Eddy, John P.; Hart, William Eugene; Brown, Shannon L.

    2006-10-01

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a developers manual for the DAKOTA software and describes the DAKOTA class hierarchies and their interrelationships. It derives directly from annotation of the actual source code and provides detailed class documentation, including all member functions and attributes.

  18. DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, developers manual.

    Energy Technology Data Exchange (ETDEWEB)

    Eldred, Michael Scott; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gay, David M.; Eddy, John P.; Haskell, Karen H.

    2010-05-01

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a developers manual for the DAKOTA software and describes the DAKOTA class hierarchies and their interrelationships. It derives directly from annotation of the actual source code and provides detailed class documentation, including all member functions and attributes.

  19. Uncertainty Quantification and Regional Sensitivity Analysis of Snow-related Parameters in the Canadian LAnd Surface Scheme (CLASS)

    Science.gov (United States)

    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.

  20. Small particle bed reactors: Sensitivity to Brayton cycle parameters

    Science.gov (United States)

    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.

  1. 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.

  2. Sensitivity analysis for modules for various biosphere types

    International Nuclear Information System (INIS)

    Karlsson, Sara; Bergstroem, U.; Rosen, K.

    2000-09-01

    This study presents the results of a sensitivity analysis for the modules developed earlier for calculation of ecosystem specific dose conversion factors (EDFs). The report also includes a comparison between the probabilistically calculated mean values of the EDFs and values gained in deterministic calculations. An overview of the distribution of radionuclides between different environmental parts in the models is also presented. The radionuclides included in the study were 36 Cl, 59 Ni, 93 Mo, 129 I, 135 Cs, 237 Np and 239 Pu, sel to represent various behaviour in the biosphere and some are of particular importance from the dose point of view. The deterministic and probabilistic EDFs showed a good agreement, for most nuclides and modules. Exceptions from this occurred if very skew distributions were used for parameters of importance for the results. Only a minor amount of the released radionuclides were present in the model compartments for all modules, except for the agricultural land module. The differences between the radionuclides were not pronounced which indicates that nuclide specific parameters were of minor importance for the retention of radionuclides for the simulated time period of 10 000 years in those modules. The results from the agricultural land module showed a different pattern. Large amounts of the radionuclides were present in the solid fraction of the saturated soil zone. The high retention within this compartment makes the zone a potential source for future exposure. Differences between the nuclides due to element specific Kd-values could be seen. The amount of radionuclides present in the upper soil layer, which is the most critical zone for exposure to humans, was less then 1% for all studied radionuclides. The sensitivity analysis showed that the physical/chemical parameters were the most important in most modules in contrast to the dominance of biological parameters in the uncertainty analysis. The only exception was the well module where

  3. 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

  4. Carbon dioxide capture processes: Simulation, design and sensitivity analysis

    DEFF Research Database (Denmark)

    Zaman, Muhammad; Lee, Jay Hyung; Gani, Rafiqul

    2012-01-01

    equilibrium and associated property models are used. Simulations are performed to investigate the sensitivity of the process variables to change in the design variables including process inputs and disturbances in the property model parameters. Results of the sensitivity analysis on the steady state...... performance of the process to the L/G ratio to the absorber, CO2 lean solvent loadings, and striper pressure are presented in this paper. Based on the sensitivity analysis process optimization problems have been defined and solved and, a preliminary control structure selection has been made.......Carbon dioxide is the main greenhouse gas and its major source is combustion of fossil fuels for power generation. The objective of this study is to carry out the steady-state sensitivity analysis for chemical absorption of carbon dioxide capture from flue gas using monoethanolamine solvent. First...

  5. Parameter Sensitivity and Laboratory Benchmarking of a Biogeochemical Process Model for Enhanced Anaerobic Dechlorination

    Science.gov (United States)

    Kouznetsova, I.; Gerhard, J. I.; Mao, X.; Barry, D. A.; Robinson, C.; Brovelli, A.; Harkness, M.; Fisher, A.; Mack, E. E.; Payne, J. A.; Dworatzek, S.; Roberts, J.

    2008-12-01

    A detailed model to simulate trichloroethene (TCE) dechlorination in anaerobic groundwater systems has been developed and implemented through PHAST, a robust and flexible geochemical modeling platform. The approach is comprehensive but retains flexibility such that models of varying complexity can be used to simulate TCE biodegradation in the vicinity of nonaqueous phase liquid (NAPL) source zones. The complete model considers a full suite of biological (e.g., dechlorination, fermentation, sulfate and iron reduction, electron donor competition, toxic inhibition, pH inhibition), physical (e.g., flow and mass transfer) and geochemical processes (e.g., pH modulation, gas formation, mineral interactions). Example simulations with the model demonstrated that the feedback between biological, physical, and geochemical processes is critical. Successful simulation of a thirty-two-month column experiment with site soil, complex groundwater chemistry, and exhibiting both anaerobic dechlorination and endogenous respiration, provided confidence in the modeling approach. A comprehensive suite of batch simulations was then conducted to estimate the sensitivity of predicted TCE degradation to the 36 model input parameters. A local sensitivity analysis was first employed to rank the importance of parameters, revealing that 5 parameters consistently dominated model predictions across a range of performance metrics. A global sensitivity analysis was then performed to evaluate the influence of a variety of full parameter data sets available in the literature. The modeling study was performed as part of the SABRE (Source Area BioREmediation) project, a public/private consortium whose charter is to determine if enhanced anaerobic bioremediation can result in effective and quantifiable treatment of chlorinated solvent DNAPL source areas. The modelling conducted has provided valuable insight into the complex interactions between processes in the evolving biogeochemical systems

  6. 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.

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

    KAUST Repository

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

    2015-01-01

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

  8. Sensitivity analysis of recovery efficiency in high-temperature aquifer thermal energy storage with single well

    DEFF Research Database (Denmark)

    Jeon, Jun-Seo; Lee, Seung-Rae; Pasquinelli, Lisa

    2015-01-01

    ., it is getting more attention as these issues are gradually alleviated. In this study, a sensitivity analysis of recovery efficiency in two cases of HT-ATES system with a single well is conducted to select key parameters. For a fractional factorial design used to choose input parameters with uniformity...... with Smoothly Clopped Absolute Deviation Penalty, is utilized. Finally, the sensitivity analysis is performed based on the variation decomposition. According to the result of sensitivity analysis, the most important input variables are selected and confirmed to consider the interaction effects for each case...

  9. 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

  10. Sensitivity Analysis Based on Markovian Integration by Parts Formula

    Directory of Open Access Journals (Sweden)

    Yongsheng Hang

    2017-10-01

    Full Text Available Sensitivity analysis is widely applied in financial risk management and engineering; it describes the variations brought by the changes of parameters. Since the integration by parts technique for Markov chains is well developed in recent years, in this paper we apply it for computation of sensitivity and show the closed-form expressions for two commonly-used time-continuous Markovian models. By comparison, we conclude that our approach outperforms the existing technique of computing sensitivity on Markovian models.

  11. Sensitivity analysis of model output - a step towards robust safety indicators?

    International Nuclear Information System (INIS)

    Broed, R.; Pereira, A.; Moberg, L.

    2004-01-01

    The protection of the environment from ionising radiation challenges the radioecological community with the issue of harmonising disparate safety indicators. These indicators should preferably cover the whole spectrum of model predictions on chemo-toxic and radiation impact of contaminants. In question is not only the protection of man and biota but also of abiotic systems. In many cases modelling will constitute the basis for an evaluation of potential impact. It is recognised that uncertainty and sensitivity analysis of model output will play an important role in the 'construction' of safety indicators that are robust, reliable and easy to explain to all groups of stakeholders including the general public. However, environmental models of transport of radionuclides have some extreme characteristics. They are, a) complex, b) non-linear, c) include a huge number of input parameters, d) input parameters are associated with large or very large uncertainties, e) parameters are often correlated to each other, f) uncertainties other than parameter-driven may be present in the modelling system, g) space variability and time-dependence of parameters are present, h) model predictions may cover geological time scales. Consequently, uncertainty and sensitivity analysis are non-trivial tasks, challenging the decision-maker when it comes to the interpretation of safety indicators or the application of regulatory criteria. In this work we use the IAEA model ISAM, to make a set of Monte Carlo calculations. The ISAM model includes several nuclides and decay chains, many compartments and variable parameters covering the range of nuclide migration pathways from the near field to the biosphere. The goal of our calculations is to make a global sensitivity analysis. After extracting the non-influential parameters, the M.C. calculations are repeated with those parameters frozen. Reducing the number of parameters to a few ones will simplify the interpretation of the results and the use

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    Hui Wan

    2015-06-01

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

  14. Probability density adjoint for sensitivity analysis of the Mean of Chaos

    Energy Technology Data Exchange (ETDEWEB)

    Blonigan, Patrick J., E-mail: blonigan@mit.edu; Wang, Qiqi, E-mail: qiqi@mit.edu

    2014-08-01

    Sensitivity analysis, especially adjoint based sensitivity analysis, is a powerful tool for engineering design which allows for the efficient computation of sensitivities with respect to many parameters. However, these methods break down when used to compute sensitivities of long-time averaged quantities in chaotic dynamical systems. This paper presents a new method for sensitivity analysis of ergodic chaotic dynamical systems, the density adjoint method. The method involves solving the governing equations for the system's invariant measure and its adjoint on the system's attractor manifold rather than in phase-space. This new approach is derived for and demonstrated on one-dimensional chaotic maps and the three-dimensional Lorenz system. It is found that the density adjoint computes very finely detailed adjoint distributions and accurate sensitivities, but suffers from large computational costs.

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

    Science.gov (United States)

    O'Reilly, A. M.

    2017-12-01

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

  16. Selecting Sensitive Parameter Subsets in Dynamical Models With Application to Biomechanical System Identification.

    Science.gov (United States)

    Ramadan, Ahmed; Boss, Connor; Choi, Jongeun; Peter Reeves, N; Cholewicki, Jacek; Popovich, John M; Radcliffe, Clark J

    2018-07-01

    Estimating many parameters of biomechanical systems with limited data may achieve good fit but may also increase 95% confidence intervals in parameter estimates. This results in poor identifiability in the estimation problem. Therefore, we propose a novel method to select sensitive biomechanical model parameters that should be estimated, while fixing the remaining parameters to values obtained from preliminary estimation. Our method relies on identifying the parameters to which the measurement output is most sensitive. The proposed method is based on the Fisher information matrix (FIM). It was compared against the nonlinear least absolute shrinkage and selection operator (LASSO) method to guide modelers on the pros and cons of our FIM method. We present an application identifying a biomechanical parametric model of a head position-tracking task for ten human subjects. Using measured data, our method (1) reduced model complexity by only requiring five out of twelve parameters to be estimated, (2) significantly reduced parameter 95% confidence intervals by up to 89% of the original confidence interval, (3) maintained goodness of fit measured by variance accounted for (VAF) at 82%, (4) reduced computation time, where our FIM method was 164 times faster than the LASSO method, and (5) selected similar sensitive parameters to the LASSO method, where three out of five selected sensitive parameters were shared by FIM and LASSO methods.

  17. Biosphere dose conversion Factor Importance and Sensitivity Analysis

    International Nuclear Information System (INIS)

    M. Wasiolek

    2004-01-01

    This report presents importance and sensitivity analysis for the environmental radiation model for Yucca Mountain, Nevada (ERMYN). ERMYN is a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis concerns the output of the model, biosphere dose conversion factors (BDCFs) for the groundwater, and the volcanic ash exposure scenarios. It identifies important processes and parameters that influence the BDCF values and distributions, enhances understanding of the relative importance of the physical and environmental processes on the outcome of the biosphere model, includes a detailed pathway analysis for key radionuclides, and evaluates the appropriateness of selected parameter values that are not site-specific or have large uncertainty

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

    Science.gov (United States)

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

    2016-06-14

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

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

    Directory of Open Access Journals (Sweden)

    Zhonghua Zhang

    2015-01-01

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

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

    Science.gov (United States)

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

    2017-11-27

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

  1. Sensitivity analysis in Gaussian Bayesian networks using a symbolic-numerical technique

    International Nuclear Information System (INIS)

    Castillo, Enrique; Kjaerulff, Uffe

    2003-01-01

    The paper discusses the problem of sensitivity analysis in Gaussian Bayesian networks. The algebraic structure of the conditional means and variances, as rational functions involving linear and quadratic functions of the parameters, are used to simplify the sensitivity analysis. In particular the probabilities of conditional variables exceeding given values and related probabilities are analyzed. Two examples of application are used to illustrate all the concepts and methods

  2. Modelling and simulation of a transketolase mediated reaction: Sensitivity analysis of kinetic parameters

    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...

  3. Global sensitivity analysis using emulators, with an example analysis of large fire plumes based on FDS simulations

    Energy Technology Data Exchange (ETDEWEB)

    Kelsey, Adrian [Health and Safety Laboratory, Harpur Hill, Buxton (United Kingdom)

    2015-12-15

    Uncertainty in model predictions of the behaviour of fires is an important issue in fire safety analysis in nuclear power plants. A global sensitivity analysis can help identify the input parameters or sub-models that have the most significant effect on model predictions. However, to perform a global sensitivity analysis using Monte Carlo sampling might require thousands of simulations to be performed and therefore would not be practical for an analysis based on a complex fire code using computational fluid dynamics (CFD). An alternative approach is to perform a global sensitivity analysis using an emulator. Gaussian process emulators can be built using a limited number of simulations and once built a global sensitivity analysis can be performed on an emulator, rather than using simulations directly. Typically reliable emulators can be built using ten simulations for each parameter under consideration, therefore allowing a global sensitivity analysis to be performed, even for a complex computer code. In this paper we use an example of a large scale pool fire to demonstrate an emulator based approach to global sensitivity analysis. In that work an emulator based global sensitivity analysis was used to identify the key uncertain model inputs affecting the entrainment rates and flame heights in large Liquefied Natural Gas (LNG) fire plumes. The pool fire simulations were performed using the Fire Dynamics Simulator (FDS) software. Five model inputs were varied: the fire diameter, burn rate, radiative fraction, computational grid cell size and choice of turbulence model. The ranges used for these parameters in the analysis were determined from experiment and literature. The Gaussian process emulators used in the analysis were created using 127 FDS simulations. The emulators were checked for reliability, and then used to perform a global sensitivity analysis and uncertainty analysis. Large-scale ignited releases of LNG on water were performed by Sandia National

  4. 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

  5. Sensitivity study of steam explosion characteristics to uncertain input parameters using TEXAS-V code

    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)

  6. Global sensitivity analysis by polynomial dimensional decomposition

    Energy Technology Data Exchange (ETDEWEB)

    Rahman, Sharif, E-mail: rahman@engineering.uiowa.ed [College of Engineering, The University of Iowa, Iowa City, IA 52242 (United States)

    2011-07-15

    This paper presents a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions. The method involves Fourier-polynomial expansions of lower-variate component functions of a stochastic response by measure-consistent orthonormal polynomial bases, analytical formulae for calculating the global sensitivity indices in terms of the expansion coefficients, and dimension-reduction integration for estimating the expansion coefficients. Due to identical dimensional structures of PDD and analysis-of-variance decomposition, the proposed method facilitates simple and direct calculation of the global sensitivity indices. Numerical results of the global sensitivity indices computed for smooth systems reveal significantly higher convergence rates of the PDD approximation than those from existing methods, including polynomial chaos expansion, random balance design, state-dependent parameter, improved Sobol's method, and sampling-based methods. However, for non-smooth functions, the convergence properties of the PDD solution deteriorate to a great extent, warranting further improvements. The computational complexity of the PDD method is polynomial, as opposed to exponential, thereby alleviating the curse of dimensionality to some extent.

  7. Sensitivity analysis of a low-level waste environmental transport code

    International Nuclear Information System (INIS)

    Hiromoto, G.

    1989-01-01

    Results are presented from a sensivity analysis of a computer code designed to simulate the environmental transport of radionuclides buried at shallow land waste repositories. A sensitivity analysis methodology, based on the surface response replacement and statistic sensitivity estimators, was developed to address the relative importance of the input parameters on the model output. Response surface replacement for the model was constructed by stepwise regression, after sampling input vectors from range and distribution of the input variables, and running the code to generate the associated output data. Sensitivity estimators were compute using the partial rank correlation coefficients and the standardized rank regression coefficients. The results showed that the tecniques employed in this work provides a feasible means to perform a sensitivity analysis of a general not-linear environmental radionuclides transport models. (author) [pt

  8. DAKOTA, a multilevel parellel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis:version 4.0 uers's manual.

    Energy Technology Data Exchange (ETDEWEB)

    Griffin, Joshua D. (Sandai National Labs, Livermore, CA); Eldred, Michael Scott; Martinez-Canales, Monica L. (Sandai National Labs, Livermore, CA); Watson, Jean-Paul; Kolda, Tamara Gibson (Sandai National Labs, Livermore, CA); Giunta, Anthony Andrew; Adams, Brian M.; Swiler, Laura Painton; Williams, Pamela J. (Sandai National Labs, Livermore, CA); Hough, Patricia Diane (Sandai National Labs, Livermore, CA); Gay, David M.; Dunlavy, Daniel M.; Eddy, John P.; Hart, William Eugene; Brown, Shannon L.

    2006-10-01

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the DAKOTA software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

  9. DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual.

    Energy Technology Data Exchange (ETDEWEB)

    Eldred, Michael Scott; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gay, David M.; Eddy, John P.; Haskell, Karen H.

    2010-05-01

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the DAKOTA software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

  10. Global sensitivity analysis of multiscale properties of porous materials

    Science.gov (United States)

    Um, Kimoon; Zhang, Xuan; Katsoulakis, Markos; Plechac, Petr; Tartakovsky, Daniel M.

    2018-02-01

    Ubiquitous uncertainty about pore geometry inevitably undermines the veracity of pore- and multi-scale simulations of transport phenomena in porous media. It raises two fundamental issues: sensitivity of effective material properties to pore-scale parameters and statistical parameterization of Darcy-scale models that accounts for pore-scale uncertainty. Homogenization-based maps of pore-scale parameters onto their Darcy-scale counterparts facilitate both sensitivity analysis (SA) and uncertainty quantification. We treat uncertain geometric characteristics of a hierarchical porous medium as random variables to conduct global SA and to derive probabilistic descriptors of effective diffusion coefficients and effective sorption rate. Our analysis is formulated in terms of solute transport diffusing through a fluid-filled pore space, while sorbing to the solid matrix. Yet it is sufficiently general to be applied to other multiscale porous media phenomena that are amenable to homogenization.

  11. Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis version 6.0 theory manual

    Energy Technology Data Exchange (ETDEWEB)

    Adams, Brian M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ebeida, Mohamed Salah [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Eldred, Michael S [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jakeman, John Davis [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Stephens, John Adam [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vigil, Dena M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wildey, Timothy Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bohnhoff, William J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Eddy, John P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hu, Kenneth T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Dalbey, Keith R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bauman, Lara E [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hough, Patricia Diane [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-05-01

    The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quanti cation, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.

  12. NODAL3 Sensitivity Analysis for NEACRP 3D LWR Core Transient Benchmark (PWR

    Directory of Open Access Journals (Sweden)

    Surian Pinem

    2016-01-01

    Full Text Available This paper reports the results of sensitivity analysis of the multidimension, multigroup neutron diffusion NODAL3 code for the NEACRP 3D LWR core transient benchmarks (PWR. The code input parameters covered in the sensitivity analysis are the radial and axial node sizes (the number of radial node per fuel assembly and the number of axial layers, heat conduction node size in the fuel pellet and cladding, and the maximum time step. The output parameters considered in this analysis followed the above-mentioned core transient benchmarks, that is, power peak, time of power peak, power, averaged Doppler temperature, maximum fuel centerline temperature, and coolant outlet temperature at the end of simulation (5 s. The sensitivity analysis results showed that the radial node size and maximum time step give a significant effect on the transient parameters, especially the time of power peak, for the HZP and HFP conditions. The number of ring divisions for fuel pellet and cladding gives negligible effect on the transient solutions. For productive work of the PWR transient analysis, based on the present sensitivity analysis results, we recommend NODAL3 users to use 2×2 radial nodes per assembly, 1×18 axial layers per assembly, the maximum time step of 10 ms, and 9 and 1 ring divisions for fuel pellet and cladding, respectively.

  13. The implication of sensitivity analysis on the safety and delayed-neutron parameters for fast breeder reactors

    International Nuclear Information System (INIS)

    Onega, R.J.; Florian, R.J.

    1983-01-01

    The delayed-neutron energy spectra for LMFBRs are not as well known as those for LWRs. These spectra are necessary for kinetics calculations which play an important role in safety and accident analyses. A sensitivity analysis was performed to study the response of the reactor power and power density to uncertainties in the delayed-neutron spectra during a rod-ejection accident. The accidents studied were central control-rod-ejections with ejection times of 2,10 and 30s. A two-energy group and two-precursor group model was formulated for the International Nuclear Fuel Cycle Evaluation (INFCE) reference design MOX-fueled LMFBR. The sensitivity analysis is based on the use of adjoints so that it is not necessary to repeatedly solve the governing (kinetics) equations to obtain the sensitivity derivatives. This is of particular importance when large systems of equations are used. The power and power-density responses were found to be most sensitive to uncertainties in the spectrum of the second delayed-neutron precursor group, resulting from the fission of 238 U, producing neutrons in the first energy group. It was found, for example, that for a rod-ejection time of 30s, and uncertainty of 7.2% in the fast components of the spectra resulted in a 24% uncertainty in the predicted power and power density. These responses were recalculated by repeatedly solving the kinetics equations. The maximum discrepancy between the recalculated and the sensitivity analysis response was only 1.6%. The results of the sensitivity analysis indicate the need for improved delayed-neutron spectral data in order to reduce the uncertainties in accident analyses. (author)

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

    International Nuclear Information System (INIS)

    Lamboni, Matieyendou; Monod, Herve; Makowski, David

    2011-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-04-15

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

  16. Sensitivity of reactor integral parameters to #betta##betta# parameter of resolved resonances of fertile isotopes and to the α values, in thermal and epithermal spectra

    International Nuclear Information System (INIS)

    Barroso, D.E.G.

    1982-01-01

    A sensitivity analysis of reactor integral parameter to more 10% variation in the resolved resonance parameters #betta##betta# of the fertile isotope and the variations of more 10% in the α values (#betta# sub(#betta#)/#betta# sub(f)) of fissile isotopes of PWR fuel elements, is done. The analysis is made with thermal and epithermal spectra, those last generated in a fuel cell with low V sub(M)/V sub(F). The HAMMER system, the interface programs HELP and LITHE and the HAMMER computer codes, were used as a base for this study. (E.G.) [pt

  17. Probabilistic sensitivity analysis of optimised preventive maintenance strategies for deteriorating infrastructure assets

    International Nuclear Information System (INIS)

    Daneshkhah, A.; Stocks, N.G.; Jeffrey, P.

    2017-01-01

    Efficient life-cycle management of civil infrastructure systems under continuous deterioration can be improved by studying the sensitivity of optimised preventive maintenance decisions with respect to changes in model parameters. Sensitivity analysis in maintenance optimisation problems is important because if the calculation of the cost of preventive maintenance strategies is not sufficiently robust, the use of the maintenance model can generate optimised maintenances strategies that are not cost-effective. Probabilistic sensitivity analysis methods (particularly variance based ones), only partially respond to this issue and their use is limited to evaluating the extent to which uncertainty in each input contributes to the overall output's variance. These methods do not take account of the decision-making problem in a straightforward manner. To address this issue, we use the concept of the Expected Value of Perfect Information (EVPI) to perform decision-informed sensitivity analysis: to identify the key parameters of the problem and quantify the value of learning about certain aspects of the life-cycle management of civil infrastructure system. This approach allows us to quantify the benefits of the maintenance strategies in terms of expected costs and in the light of accumulated information about the model parameters and aspects of the system, such as the ageing process. We use a Gamma process model to represent the uncertainty associated with asset deterioration, illustrating the use of EVPI to perform sensitivity analysis on the optimisation problem for age-based and condition-based preventive maintenance strategies. The evaluation of EVPI indices is computationally demanding and Markov Chain Monte Carlo techniques would not be helpful. To overcome this computational difficulty, we approximate the EVPI indices using Gaussian process emulators. The implications of the worked numerical examples discussed in the context of analytical efficiency and organisational

  18. Sensitivity analysis in a structural reliability context

    International Nuclear Information System (INIS)

    Lemaitre, Paul

    2014-01-01

    This thesis' subject is sensitivity analysis in a structural reliability context. The general framework is the study of a deterministic numerical model that allows to reproduce a complex physical phenomenon. The aim of a reliability study is to estimate the failure probability of the system from the numerical model and the uncertainties of the inputs. In this context, the quantification of the impact of the uncertainty of each input parameter on the output might be of interest. This step is called sensitivity analysis. Many scientific works deal with this topic but not in the reliability scope. This thesis' aim is to test existing sensitivity analysis methods, and to propose more efficient original methods. A bibliographical step on sensitivity analysis on one hand and on the estimation of small failure probabilities on the other hand is first proposed. This step raises the need to develop appropriate techniques. Two variables ranking methods are then explored. The first one proposes to make use of binary classifiers (random forests). The second one measures the departure, at each step of a subset method, between each input original density and the density given the subset reached. A more general and original methodology reflecting the impact of the input density modification on the failure probability is then explored. The proposed methods are then applied on the CWNR case, which motivates this thesis. (author)

  19. Contribution to the sample mean plot for graphical and numerical sensitivity analysis

    International Nuclear Information System (INIS)

    Bolado-Lavin, R.; Castaings, W.; Tarantola, S.

    2009-01-01

    The contribution to the sample mean plot, originally proposed by Sinclair, is revived and further developed as practical tool for global sensitivity analysis. The potentials of this simple and versatile graphical tool are discussed. Beyond the qualitative assessment provided by this approach, a statistical test is proposed for sensitivity analysis. A case study that simulates the transport of radionuclides through the geosphere from an underground disposal vault containing nuclear waste is considered as a benchmark. The new approach is tested against a very efficient sensitivity analysis method based on state dependent parameter meta-modelling

  20. 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

  1. 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.

  2. Sensitivity analysis of local uncertainties in large break loss-of-coolant accident (LB-LOCA) thermo-mechanical simulations

    Energy Technology Data Exchange (ETDEWEB)

    Arkoma, Asko, E-mail: asko.arkoma@vtt.fi; Ikonen, Timo

    2016-08-15

    Highlights: • A sensitivity analysis using the data from EPR LB-LOCA simulations is done. • A procedure to analyze such complex data is outlined. • Both visual and quantitative methods are used. • Input factors related to core design are identified as most significant. - Abstract: In this paper, a sensitivity analysis for the data originating from a large break loss-of-coolant accident (LB-LOCA) analysis of an EPR-type nuclear power plant is presented. In the preceding LOCA analysis, the number of failing fuel rods in the accident was established (Arkoma et al., 2015). However, the underlying causes for rod failures were not addressed. It is essential to bring out which input parameters and boundary conditions have significance to the outcome of the analysis, i.e. the ballooning and burst of the rods. Due to complexity of the existing data, the first part of the analysis consists of defining the relevant input parameters for the sensitivity analysis. Then, selected sensitivity measures are calculated between the chosen input and output parameters. The ultimate goal is to develop a systematic procedure for the sensitivity analysis of statistical LOCA simulation that takes into account the various sources of uncertainties in the calculation chain. In the current analysis, the most relevant parameters with respect to the cladding integrity are the decay heat power during the transient, the thermal hydraulic conditions in the rod’s location in reactor, and the steady-state irradiation history of the rod. Meanwhile, the tolerances in fuel manufacturing parameters were found to have negligible effect on cladding deformation.

  3. Mesh refinement and numerical sensitivity analysis for parameter calibration of partial differential equations

    Science.gov (United States)

    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.

  4. Correlation of 210Po implanted in glass with radon gas exposure: sensitivity analysis of critical parameters using a Monte-Carlo approach.

    Science.gov (United States)

    Walsh, C; McLaughlin, J P

    2001-05-14

    In recent years, 210Po implanted in glass artefacts has been used as an indicator of the mean radon gas concentration in dwellings in the past. Glass artefacts have been selected in many dwellings and the alpha-recoil implanted 210Po concentration has been measured using various techniques. Some of these retrospective techniques use a model to estimate the retrospective radon gas on the basis of this surface 210Po activity. The accumulation of 210Po on glass surfaces is determined by the deposition regime over the exposure period. The 210Po activity is determined not only by the radon progeny deposition velocities, but by other room parameters such as ventilation rate, aerosol conditions and the surface to volume ratio of the room. Up to now in using room models, a nominal or 'base-case' scenario is used, i.e. a single value is chosen for each input parameter. In this paper a Monte-Carlo analysis is presented in which a probability distribution for each parameter is chosen, based on measurements quoted in the literature. A 210Po surface activity is calculated using a single value drawn from each of the parameter distributions using a pseudo-random number generator. This process is repeated n times (up to 20,000), producing n independent scenarios with corresponding 210Po values. This process permits a sensitivity analysis to be carried out to see the effect of changes in inputs on the model output.

  5. Application of Sensitivity Analysis in Design of Sustainable Buildings

    DEFF Research Database (Denmark)

    Heiselberg, Per; Brohus, Henrik; Hesselholt, Allan Tind

    2007-01-01

    satisfies the design requirements and objectives. In the design of sustainable Buildings it is beneficial to identify the most important design parameters in order to develop more efficiently alternative design solutions or reach optimized design solutions. A sensitivity analysis makes it possible...

  6. Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system.

    Science.gov (United States)

    Lumen, Annie; McNally, Kevin; George, Nysia; Fisher, Jeffrey W; Loizou, George D

    2015-01-01

    A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local sensitivity analysis.

  7. Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system

    Directory of Open Access Journals (Sweden)

    Annie eLumen

    2015-05-01

    Full Text Available A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local

  8. An analysis of sensitivity and uncertainty associated with the use of the HSPF model for EIA applications

    Energy Technology Data Exchange (ETDEWEB)

    Biftu, G.F.; Beersing, A.; Wu, S.; Ade, F. [Golder Associates, Calgary, AB (Canada)

    2005-07-01

    An outline of a new approach to assessing the sensitivity and uncertainty associated with surface water modelling results using Hydrological Simulation Program-Fortran (HSPF) was presented, as well as the results of a sensitivity and uncertainty analysis. The HSPF model is often used to characterize the hydrological processes in watersheds within the oil sands region. Typical applications of HSPF included calibration of the model parameters using data from gauged watersheds, as well as validation of calibrated models with data sets. Additionally, simulations are often conducted to make flow predictions to support the environmental impact assessment (EIA) process. However, a key aspect of the modelling components of the EIA process is the sensitivity and uncertainty of the modelling results as compared to model parameters. Many of the variations in the HSPF model's outputs are caused by a small number of model parameters and outputs. A sensitivity analysis was performed to identify and focus on key parameters and assumptions that have the most influence on the model's outputs. Analysis entailed varying each parameter in turn, within a range, and examining the resulting relative changes in the model outputs. This analysis consisted of the selection of probability distributions to characterize the uncertainty in the model's key sensitive parameters, as well as the use of Monte Carlo and HSPF simulation to determine the uncertainty in model outputs. tabs, figs.

  9. Sensitivity analysis of periodic errors in heterodyne interferometry

    International Nuclear Information System (INIS)

    Ganguly, Vasishta; Kim, Nam Ho; Kim, Hyo Soo; Schmitz, Tony

    2011-01-01

    Periodic errors in heterodyne displacement measuring interferometry occur due to frequency mixing in the interferometer. These nonlinearities are typically characterized as first- and second-order periodic errors which cause a cyclical (non-cumulative) variation in the reported displacement about the true value. This study implements an existing analytical periodic error model in order to identify sensitivities of the first- and second-order periodic errors to the input parameters, including rotational misalignments of the polarizing beam splitter and mixing polarizer, non-orthogonality of the two laser frequencies, ellipticity in the polarizations of the two laser beams, and different transmission coefficients in the polarizing beam splitter. A local sensitivity analysis is first conducted to examine the sensitivities of the periodic errors with respect to each input parameter about the nominal input values. Next, a variance-based approach is used to study the global sensitivities of the periodic errors by calculating the Sobol' sensitivity indices using Monte Carlo simulation. The effect of variation in the input uncertainty on the computed sensitivity indices is examined. It is seen that the first-order periodic error is highly sensitive to non-orthogonality of the two linearly polarized laser frequencies, while the second-order error is most sensitive to the rotational misalignment between the laser beams and the polarizing beam splitter. A particle swarm optimization technique is finally used to predict the possible setup imperfections based on experimentally generated values for periodic errors

  10. Sensitivity analysis of periodic errors in heterodyne interferometry

    Science.gov (United States)

    Ganguly, Vasishta; Kim, Nam Ho; Kim, Hyo Soo; Schmitz, Tony

    2011-03-01

    Periodic errors in heterodyne displacement measuring interferometry occur due to frequency mixing in the interferometer. These nonlinearities are typically characterized as first- and second-order periodic errors which cause a cyclical (non-cumulative) variation in the reported displacement about the true value. This study implements an existing analytical periodic error model in order to identify sensitivities of the first- and second-order periodic errors to the input parameters, including rotational misalignments of the polarizing beam splitter and mixing polarizer, non-orthogonality of the two laser frequencies, ellipticity in the polarizations of the two laser beams, and different transmission coefficients in the polarizing beam splitter. A local sensitivity analysis is first conducted to examine the sensitivities of the periodic errors with respect to each input parameter about the nominal input values. Next, a variance-based approach is used to study the global sensitivities of the periodic errors by calculating the Sobol' sensitivity indices using Monte Carlo simulation. The effect of variation in the input uncertainty on the computed sensitivity indices is examined. It is seen that the first-order periodic error is highly sensitive to non-orthogonality of the two linearly polarized laser frequencies, while the second-order error is most sensitive to the rotational misalignment between the laser beams and the polarizing beam splitter. A particle swarm optimization technique is finally used to predict the possible setup imperfections based on experimentally generated values for periodic errors.

  11. Non-human biota dose assessment. Sensitivity analysis and knowledge quality assessment

    International Nuclear Information System (INIS)

    Smith, K.; Robinson, C.; Jackson, D.; La Cruz, I. de; Zinger, I.; Avila, R.

    2010-10-01

    This report provides a summary of a programme of work, commissioned within the BIOPROTA collaborative forum, to assess the quantitative and qualitative elements of uncertainty associated with biota dose assessment of potential impacts of long-term releases from geological disposal facilities (GDF). Quantitative and qualitative aspects of uncertainty were determined through sensitivity and knowledge quality assessments, respectively. Both assessments focused on default assessment parameters within the ERICA assessment approach. The sensitivity analysis was conducted within the EIKOS sensitivity analysis software tool and was run in both generic and test case modes. The knowledge quality assessment involved development of a questionnaire around the ERICA assessment approach, which was distributed to a range of experts in the fields of non-human biota dose assessment and radioactive waste disposal assessments. Combined, these assessments enabled critical model features and parameters that are both sensitive (i.e. have a large influence on model output) and of low knowledge quality to be identified for each of the three test cases. The output of this project is intended to provide information on those parameters that may need to be considered in more detail for prospective site-specific biota dose assessments for GDFs. Such information should help users to enhance the quality of their assessments and build greater confidence in the results. (orig.)

  12. Using sensitivity analysis to identify key factors for the propagation of a plant epidemic.

    Science.gov (United States)

    Rimbaud, Loup; Bruchou, Claude; Dallot, Sylvie; Pleydell, David R J; Jacquot, Emmanuel; Soubeyrand, Samuel; Thébaud, Gaël

    2018-01-01

    Identifying the key factors underlying the spread of a disease is an essential but challenging prerequisite to design management strategies. To tackle this issue, we propose an approach based on sensitivity analyses of a spatiotemporal stochastic model simulating the spread of a plant epidemic. This work is motivated by the spread of sharka, caused by plum pox virus , in a real landscape. We first carried out a broad-range sensitivity analysis, ignoring any prior information on six epidemiological parameters, to assess their intrinsic influence on model behaviour. A second analysis benefited from the available knowledge on sharka epidemiology and was thus restricted to more realistic values. The broad-range analysis revealed that the mean duration of the latent period is the most influential parameter of the model, whereas the sharka-specific analysis uncovered the strong impact of the connectivity of the first infected orchard. In addition to demonstrating the interest of sensitivity analyses for a stochastic model, this study highlights the impact of variation ranges of target parameters on the outcome of a sensitivity analysis. With regard to sharka management, our results suggest that sharka surveillance may benefit from paying closer attention to highly connected patches whose infection could trigger serious epidemics.

  13. Sensitivity study and parameter optimization of OCD tool for 14nm finFET process

    Science.gov (United States)

    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.

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

    International Nuclear Information System (INIS)

    Clifton, P.M.

    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

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

    Science.gov (United States)

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

    2015-11-01

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

  16. DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's reference manual.

    Energy Technology Data Exchange (ETDEWEB)

    Eldred, Michael Scott; Dalbey, Keith R.; Bohnhoff, William J.; Adams, Brian M.; Swiler, Laura Painton; Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gay, David M.; Eddy, John P.; Haskell, Karen H.

    2010-05-01

    The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a reference manual for the commands specification for the DAKOTA software, providing input overviews, option descriptions, and example specifications.

  17. Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection.

    Science.gov (United States)

    Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

    2015-01-01

    Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.

  18. Sensitivity and uncertainty analysis

    CERN Document Server

    Cacuci, Dan G; Navon, Ionel Michael

    2005-01-01

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

  19. Uncertainty and sensitivity analysis in a Probabilistic Safety Analysis level-1

    International Nuclear Information System (INIS)

    Nunez Mc Leod, Jorge E.; Rivera, Selva S.

    1996-01-01

    A methodology for sensitivity and uncertainty analysis, applicable to a Probabilistic Safety Assessment Level I has been presented. The work contents are: correct association of distributions to parameters, importance and qualification of expert opinions, generations of samples according to sample sizes, and study of the relationships among system variables and systems response. A series of statistical-mathematical techniques are recommended along the development of the analysis methodology, as well as different graphical visualization for the control of the study. (author)

  20. Application of decision tree technique to sensitivity analysis for results of radionuclide migration calculations. Research documents

    International Nuclear Information System (INIS)

    Nakajima, Kunihiko; Makino, Hitoshi

    2005-03-01

    Uncertainties are always present in the parameters used for the nuclide migration analysis in the geological disposal system. These uncertainties affect the result of such analyses, e.g., and the identification of dominant nuclides. It is very important to identify the parameters causing the significant impact on the results, and to investigate the influence of identified parameters in order to recognize R and D items with respect to the development of geological disposal system and understanding of the system performance. In our study, the decision tree analysis technique was examined in the sensitivity analysis as a method for investigation of the influences of the parameters and for complement existing sensitivity analysis. As a result, results obtained from Monte Carlo simulation with parameter uncertainties could be distinguished with not only important parameters but also with their quantitative conditions (e.g., ranges of parameter values). Furthermore, information obtained from the decision tree analysis could be used 1) to categorize the results obtained from the nuclide migration analysis for a given parameter set, 2) to show prospective effect of reduction to parameter uncertainties on the results. (author)

  1. 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

  2. Global sensitivity analysis in wind energy assessment

    Science.gov (United States)

    Tsvetkova, O.; Ouarda, T. B.

    2012-12-01

    Wind energy is one of the most promising renewable energy sources. Nevertheless, it is not yet a common source of energy, although there is enough wind potential to supply world's energy demand. One of the most prominent obstacles on the way of employing wind energy is the uncertainty associated with wind energy assessment. Global sensitivity analysis (SA) studies how the variation of input parameters in an abstract model effects the variation of the variable of interest or the output variable. It also provides ways to calculate explicit measures of importance of input variables (first order and total effect sensitivity indices) in regard to influence on the variation of the output variable. Two methods of determining the above mentioned indices were applied and compared: the brute force method and the best practice estimation procedure In this study a methodology for conducting global SA of wind energy assessment at a planning stage is proposed. Three sampling strategies which are a part of SA procedure were compared: sampling based on Sobol' sequences (SBSS), Latin hypercube sampling (LHS) and pseudo-random sampling (PRS). A case study of Masdar City, a showcase of sustainable living in the UAE, is used to exemplify application of the proposed methodology. Sources of uncertainty in wind energy assessment are very diverse. In the case study the following were identified as uncertain input parameters: the Weibull shape parameter, the Weibull scale parameter, availability of a wind turbine, lifetime of a turbine, air density, electrical losses, blade losses, ineffective time losses. Ineffective time losses are defined as losses during the time when the actual wind speed is lower than the cut-in speed or higher than the cut-out speed. The output variable in the case study is the lifetime energy production. Most influential factors for lifetime energy production are identified with the ranking of the total effect sensitivity indices. The results of the present

  3. SENSITIVITY ANALYSIS OF BIOME-BGC MODEL FOR DRY TROPICAL FORESTS OF VINDHYAN HIGHLANDS, INDIA

    OpenAIRE

    M. Kumar; A. S. Raghubanshi

    2012-01-01

    A process-based model BIOME-BGC was run for sensitivity analysis to see the effect of ecophysiological parameters on net primary production (NPP) of dry tropical forest of India. The sensitivity test reveals that the forest NPP was highly sensitive to the following ecophysiological parameters: Canopy light extinction coefficient (k), Canopy average specific leaf area (SLA), New stem C : New leaf C (SC:LC), Maximum stomatal conductance (gs,max), C:N of fine roots (C:Nfr), All-sided to...

  4. 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.

  5. 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.

  6. Methods for global sensitivity analysis in life cycle assessment

    NARCIS (Netherlands)

    Groen, Evelyne A.; Bokkers, Eddy; Heijungs, Reinout; Boer, de Imke J.M.

    2017-01-01

    Purpose: Input parameters required to quantify environmental impact in life cycle assessment (LCA) can be uncertain due to e.g. temporal variability or unknowns about the true value of emission factors. Uncertainty of environmental impact can be analysed by means of a global sensitivity analysis to

  7. Probabilistic Sensitivities for Fatigue Analysis of Turbine Engine Disks

    Directory of Open Access Journals (Sweden)

    Harry R. Millwater

    2006-01-01

    Full Text Available A methodology is developed and applied that determines the sensitivities of the probability-of-fracture of a gas turbine disk fatigue analysis with respect to the parameters of the probability distributions describing the random variables. The disk material is subject to initial anomalies, in either low- or high-frequency quantities, such that commonly used materials (titanium, nickel, powder nickel and common damage mechanisms (inherent defects or surface damage can be considered. The derivation is developed for Monte Carlo sampling such that the existing failure samples are used and the sensitivities are obtained with minimal additional computational time. Variance estimates and confidence bounds of the sensitivity estimates are developed. The methodology is demonstrated and verified using a multizone probabilistic fatigue analysis of a gas turbine compressor disk analysis considering stress scatter, crack growth propagation scatter, and initial crack size as random variables.

  8. Application of sensitivity analysis for optimized piping support design

    International Nuclear Information System (INIS)

    Tai, K.; Nakatogawa, T.; Hisada, T.; Noguchi, H.; Ichihashi, I.; Ogo, H.

    1993-01-01

    The objective of this study was to see if recent developments in non-linear sensitivity analysis could be applied to the design of nuclear piping systems which use non-linear supports and to develop a practical method of designing such piping systems. In the study presented in this paper, the seismic response of a typical piping system was analyzed using a dynamic non-linear FEM and a sensitivity analysis was carried out. Then optimization for the design of the piping system supports was investigated, selecting the support location and yield load of the non-linear supports (bi-linear model) as main design parameters. It was concluded that the optimized design was a matter of combining overall system reliability with the achievement of an efficient damping effect from the non-linear supports. The analysis also demonstrated sensitivity factors are useful in the planning stage of support design. (author)

  9. Sensitivity analysis of time-dependent laminar flows

    International Nuclear Information System (INIS)

    Hristova, H.; Etienne, S.; Pelletier, D.; Borggaard, J.

    2004-01-01

    This paper presents a general sensitivity equation method (SEM) for time dependent incompressible laminar flows. The SEM accounts for complex parameter dependence and is suitable for a wide range of problems. The formulation is verified on a problem with a closed form solution obtained by the method of manufactured solution. Systematic grid convergence studies confirm the theoretical rates of convergence in both space and time. The methodology is then applied to pulsatile flow around a square cylinder. Computations show that the flow starts with symmetrical vortex shedding followed by a transition to the traditional Von Karman street (alternate vortex shedding). Simulations show that the transition phase manifests itself earlier in the sensitivity fields than in the flow field itself. Sensitivities are then demonstrated for fast evaluation of nearby flows and uncertainty analysis. (author)

  10. Parametric sensitivity analysis for the helium dimers on a model potential

    Directory of Open Access Journals (Sweden)

    Nelson Henrique Teixeira Lemes

    2012-01-01

    Full Text Available Potential parameters sensitivity analysis for helium unlike molecules, HeNe, HeAr, HeKr and HeXe is the subject of this work. Number of bound states these rare gas dimers can support, for different angular momentum, will be presented and discussed. The variable phase method, together with the Levinson's theorem, is used to explore the quantum scattering process at very low collision energy using the Tang and Toennies potential. These diatomic dimers can support a bound state even for relative angular momentum equal to five, as in HeXe. Vibrational excited states, with zero angular momentum, are also possible for HeKr and HeXe. Results from sensitive analysis will give acceptable order of magnitude on potentials parameters.

  11. Nominal Range Sensitivity Analysis of peak radionuclide concentrations in randomly heterogeneous aquifers

    International Nuclear Information System (INIS)

    Cadini, F.; De Sanctis, J.; Cherubini, A.; Zio, E.; Riva, M.; Guadagnini, A.

    2012-01-01

    Highlights: ► Uncertainty quantification problem associated with the radionuclide migration. ► Groundwater transport processes simulated within a randomly heterogeneous aquifer. ► Development of an automatic sensitivity analysis for flow and transport parameters. ► Proposal of a Nominal Range Sensitivity Analysis approach. ► Analysis applied to the performance assessment of a nuclear waste repository. - Abstract: We consider the problem of quantification of uncertainty associated with radionuclide transport processes within a randomly heterogeneous aquifer system in the context of performance assessment of a near-surface radioactive waste repository. Radionuclide migration is simulated at the repository scale through a Monte Carlo scheme. The saturated groundwater flow and transport equations are then solved at the aquifer scale for the assessment of the expected radionuclide peak concentration at a location of interest. A procedure is presented to perform the sensitivity analysis of this target environmental variable to key parameters that characterize flow and transport processes in the subsurface. The proposed procedure is exemplified through an application to a realistic case study.

  12. Interactive Building Design Space Exploration Using Regionalized Sensitivity Analysis

    DEFF Research Database (Denmark)

    Østergård, Torben; Jensen, Rasmus Lund; Maagaard, Steffen

    2017-01-01

    simulation inputs are most important and which have negligible influence on the model output. Popular sensitivity methods include the Morris method, variance-based methods (e.g. Sobol’s), and regression methods (e.g. SRC). However, all these methods only address one output at a time, which makes it difficult...... in combination with the interactive parallel coordinate plot (PCP). The latter is an effective tool to explore stochastic simulations and to find high-performing building designs. The proposed methods help decision makers to focus their attention to the most important design parameters when exploring......Monte Carlo simulations combined with regionalized sensitivity analysis provide the means to explore a vast, multivariate design space in building design. Typically, sensitivity analysis shows how the variability of model output relates to the uncertainties in models inputs. This reveals which...

  13. Sensitivity analysis of efficiency thermal energy storage on selected rock mass and grout parameters using design of experiment method

    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

  14. Geochemical sensitivity analysis: Identification of important geochemical parameters for performance assessment studies

    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

  15. Sensitivity analysis and power for instrumental variable studies.

    Science.gov (United States)

    Wang, Xuran; Jiang, Yang; Zhang, Nancy R; Small, Dylan S

    2018-03-31

    In observational studies to estimate treatment effects, unmeasured confounding is often a concern. The instrumental variable (IV) method can control for unmeasured confounding when there is a valid IV. To be a valid IV, a variable needs to be independent of unmeasured confounders and only affect the outcome through affecting the treatment. When applying the IV method, there is often concern that a putative IV is invalid to some degree. We present an approach to sensitivity analysis for the IV method which examines the sensitivity of inferences to violations of IV validity. Specifically, we consider sensitivity when the magnitude of association between the putative IV and the unmeasured confounders and the direct effect of the IV on the outcome are limited in magnitude by a sensitivity parameter. Our approach is based on extending the Anderson-Rubin test and is valid regardless of the strength of the instrument. A power formula for this sensitivity analysis is presented. We illustrate its usage via examples about Mendelian randomization studies and its implications via a comparison of using rare versus common genetic variants as instruments. © 2018, The International Biometric Society.

  16. Sensitivity Analysis of Launch Vehicle Debris Risk Model

    Science.gov (United States)

    Gee, Ken; Lawrence, Scott L.

    2010-01-01

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

  17. Uncertainty and sensitivity analysis in nuclear accident consequence assessment

    International Nuclear Information System (INIS)

    Karlberg, Olof.

    1989-01-01

    This report contains the results of a four year project in research contracts with the Nordic Cooperation in Nuclear Safety and the National Institute for Radiation Protection. An uncertainty/sensitivity analysis methodology consisting of Latin Hypercube sampling and regression analysis was applied to an accident consequence model. A number of input parameters were selected and the uncertainties related to these parameter were estimated within a Nordic group of experts. Individual doses, collective dose, health effects and their related uncertainties were then calculated for three release scenarios and for a representative sample of meteorological situations. From two of the scenarios the acute phase after an accident were simulated and from one the long time consequences. The most significant parameters were identified. The outer limits of the calculated uncertainty distributions are large and will grow to several order of magnitudes for the low probability consequences. The uncertainty in the expectation values are typical a factor 2-5 (1 Sigma). The variation in the model responses due to the variation of the weather parameters is fairly equal to the parameter uncertainty induced variation. The most important parameters showed out to be different for each pathway of exposure, which could be expected. However, the overall most important parameters are the wet deposition coefficient and the shielding factors. A general discussion of the usefulness of uncertainty analysis in consequence analysis is also given. (au)

  18. A sensitivity analysis of a personalized pulse wave propagation model for arteriovenous fistula surgery. Part B: Identification of possible generic model parameters.

    Science.gov (United States)

    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.

  19. Parameter Uncertainty for Repository Thermal Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Hardin, Ernest [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hadgu, Teklu [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Greenberg, Harris [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Dupont, Mark [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2015-10-01

    This report is one follow-on to a study of reference geologic disposal design concepts (Hardin et al. 2011a). Based on an analysis of maximum temperatures, that study concluded that certain disposal concepts would require extended decay storage prior to emplacement, or the use of small waste packages, or both. The study used nominal values for thermal properties of host geologic media and engineered materials, demonstrating the need for uncertainty analysis to support the conclusions. This report is a first step that identifies the input parameters of the maximum temperature calculation, surveys published data on measured values, uses an analytical approach to determine which parameters are most important, and performs an example sensitivity analysis. Using results from this first step, temperature calculations planned for FY12 can focus on only the important parameters, and can use the uncertainty ranges reported here. The survey of published information on thermal properties of geologic media and engineered materials, is intended to be sufficient for use in generic calculations to evaluate the feasibility of reference disposal concepts. A full compendium of literature data is beyond the scope of this report. The term “uncertainty” is used here to represent both measurement uncertainty and spatial variability, or variability across host geologic units. For the most important parameters (e.g., buffer thermal conductivity) the extent of literature data surveyed samples these different forms of uncertainty and variability. Finally, this report is intended to be one chapter or section of a larger FY12 deliverable summarizing all the work on design concepts and thermal load management for geologic disposal (M3FT-12SN0804032, due 15Aug2012).

  20. Uncertainty and Sensitivity Analysis of Afterbody Radiative Heating Predictions for Earth Entry

    Science.gov (United States)

    West, Thomas K., IV; Johnston, Christopher O.; Hosder, Serhat

    2016-01-01

    The objective of this work was to perform sensitivity analysis and uncertainty quantification for afterbody radiative heating predictions of Stardust capsule during Earth entry at peak afterbody radiation conditions. The radiation environment in the afterbody region poses significant challenges for accurate uncertainty quantification and sensitivity analysis due to the complexity of the flow physics, computational cost, and large number of un-certain variables. In this study, first a sparse collocation non-intrusive polynomial chaos approach along with global non-linear sensitivity analysis was used to identify the most significant uncertain variables and reduce the dimensions of the stochastic problem. Then, a total order stochastic expansion was constructed over only the important parameters for an efficient and accurate estimate of the uncertainty in radiation. Based on previous work, 388 uncertain parameters were considered in the radiation model, which came from the thermodynamics, flow field chemistry, and radiation modeling. The sensitivity analysis showed that only four of these variables contributed significantly to afterbody radiation uncertainty, accounting for almost 95% of the uncertainty. These included the electronic- impact excitation rate for N between level 2 and level 5 and rates of three chemical reactions in uencing N, N(+), O, and O(+) number densities in the flow field.

  1. PREVALENCE OF METABOLIC SYNDROME IN YOUNG MEXICANS: A SENSITIVITY ANALYSIS ON ITS COMPONENTS.

    Science.gov (United States)

    Murguía-Romero, Miguel; Jiménez-Flores, J Rafael; Sigrist-Flores, Santiago C; Tapia-Pancardo, Diana C; Jiménez-Ramos, Arnulfo; Méndez-Cruz, A René; Villalobos-Molina, Rafael

    2015-07-28

    obesity is a worldwide epidemic, and the high prevalence of diabetes type II (DM2) and cardiovascular disease (CVD) is in great part a consequence of that epidemic. Metabolic syndrome is a useful tool to estimate the risk of a young population to evolve to DM2 and CVD. to estimate the MetS prevalence in young Mexicans, and to evaluate each parameter as an independent indicator through a sensitivity analysis. the prevalence of MetS was estimated in 6 063 young of the México City metropolitan area. A sensitivity analysis was conducted to estimate the performance of each one of the components of MetS, as an indicator of the presence of MetS itself. Five statistical of the sensitivity analysis were calculated for each MetS component and the other parameters included: sensitivity, specificity, positive predictive value or precision, negative predictive value, and accuracy. the prevalence of MetS in Mexican young population was estimated to be 13.4%. Waist circumference presented the highest sensitivity (96.8% women; 90.0% men), blood pressure presented the highest specificity for women (97.7%) and glucose for men (91.0%). When all the five statistical are considered triglycerides is the component with the highest values, showing a value of 75% or more in four of them. Differences by sex are detected for averages of all components of MetS in young without alterations. Mexican young are highly prone to acquire MetS: 71% have at least one and up to five MetS parameters altered, and 13.4% of them have MetS. From all the five components of MetS, waist circumference presented the highest sensitivity as a predictor of MetS, and triglycerides is the best parameter if a single factor is to be taken as sole predictor of MetS in Mexican young population, triglycerides is also the parameter with the highest accuracy. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

  2. Laryngeal High-Speed Videoendoscopy: Sensitivity of Objective Parameters towards Recording Frame Rate

    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.

  3. 2D Numerical Simulation and Sensitive Analysis of H-Darrieus Wind Turbine

    Directory of Open Access Journals (Sweden)

    Seyed Mohammad E. Saryazdi

    2018-02-01

    Full Text Available Recently, a lot of attention has been devoted to the use of Darrieus wind turbines in urban areas. The aerodynamics of a Darrieus turbine are very complex due to dynamic stall and changing forces on the turbine triggered by changing horizontal angles. In this study, the aerodynamics of H-rotor vertical axis wind turbine (VAWT has been studied using computational fluid dynamics via two different turbulence models. Shear stress transport (SST k-ω turbulence model was used to simulate a 2D unsteady model of the H-Darrieus turbine. In order to complete this simulation, sensitivity analysis of the effective turbine parameters such as solidity factor, airfoil shape, wind velocity and shaft diameter were done. To simulate the flow through the turbine, a 2D simplified computational domain has been generated. Then fine mesh for each case consisting of different turbulence models and dimensions has been generated. Each mesh in this simulation dependent on effective parameters consisted of domain size, mesh quality, time step and total revolution. The sliding mesh method was applied to evaluate the unsteady interaction between the stationary and rotating components. Previous works just simulated turbine, while in our study sensitivity analysis of effective parameters was done. The simulation results closely match the experimental data, providing an efficient and reliable foundation to study wind turbine aerodynamics. This also demonstrates computing the best value of the effective parameter. The sensitivity analysis revealed best value of the effective parameter that could be used in the process of designing turbine. This work provides the first step in developing an accurate 3D aerodynamic modeling of Darrieus wind turbines. Article History: Received :August 19th 2017; Received: December 15th 2017; Accepted: Januari 14th 2018; Available online How to Cite This Article: Saryazdi, S. M. E. and Boroushaki, M. (2018 2D Numerical Simulation and Sensitive

  4. WHAT IF (Sensitivity Analysis

    Directory of Open Access Journals (Sweden)

    Iulian N. BUJOREANU

    2011-01-01

    Full Text Available Sensitivity analysis represents such a well known and deeply analyzed subject that anyone to enter the field feels like not being able to add anything new. Still, there are so many facets to be taken into consideration.The paper introduces the reader to the various ways sensitivity analysis is implemented and the reasons for which it has to be implemented in most analyses in the decision making processes. Risk analysis is of outmost importance in dealing with resource allocation and is presented at the beginning of the paper as the initial cause to implement sensitivity analysis. Different views and approaches are added during the discussion about sensitivity analysis so that the reader develops an as thoroughly as possible opinion on the use and UTILITY of the sensitivity analysis. Finally, a round-up conclusion brings us to the question of the possibility of generating the future and analyzing it before it unfolds so that, when it happens it brings less uncertainty.

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

    Science.gov (United States)

    Kumar, M.; Raghubanshi, A. S.

    2011-08-01

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

  6. Sensitivity of the optimal parameter settings for a LTE packet scheduler

    NARCIS (Netherlands)

    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

  7. Testing of the derivative method and Kruskal-Wallis technique for sensitivity analysis of SYVAC

    International Nuclear Information System (INIS)

    Prust, J.O.; Edwards, H.H.

    1985-04-01

    The Kruskal-Wallis method of one-way analysis of variance by ranks has proved successful in identifying input parameters which have an important influence on dose. This technique was extended to test for first order interactions between parameters. In view of a number of practical difficulties and the computing resources required to carry out a large number of runs, this test is not recommended for detecting interactions between parameters. The derivative method of sensitivity analysis examines the partial derivative values of each input parameter with dose at various points across the parameter range. Important input parameters are associated with high derivatives and the results agreed well with previous sensitivity studies. The derivative values also provided information on the data generation distributions to be used for the input parameters in order to concentrate sampling in the high dose region of the parameter space to improve the sampling efficiency. Furthermore, the derivative values provided information on parameter interactions, the feasibility of developing a high dose algorithm and formed the basis for developing a regression equation. (author)

  8. Parametric sensitivity analysis of an agro-economic model of management of irrigation water

    Science.gov (United States)

    El Ouadi, Ihssan; Ouazar, Driss; El Menyari, Younesse

    2015-04-01

    The current work aims to build an analysis and decision support tool for policy options concerning the optimal allocation of water resources, while allowing a better reflection on the issue of valuation of water by the agricultural sector in particular. Thus, a model disaggregated by farm type was developed for the rural town of Ait Ben Yacoub located in the east Morocco. This model integrates economic, agronomic and hydraulic data and simulates agricultural gross margin across in this area taking into consideration changes in public policy and climatic conditions, taking into account the competition for collective resources. To identify the model input parameters that influence over the results of the model, a parametric sensitivity analysis is performed by the "One-Factor-At-A-Time" approach within the "Screening Designs" method. Preliminary results of this analysis show that among the 10 parameters analyzed, 6 parameters affect significantly the objective function of the model, it is in order of influence: i) Coefficient of crop yield response to water, ii) Average daily gain in weight of livestock, iii) Exchange of livestock reproduction, iv) maximum yield of crops, v) Supply of irrigation water and vi) precipitation. These 6 parameters register sensitivity indexes ranging between 0.22 and 1.28. Those results show high uncertainties on these parameters that can dramatically skew the results of the model or the need to pay particular attention to their estimates. Keywords: water, agriculture, modeling, optimal allocation, parametric sensitivity analysis, Screening Designs, One-Factor-At-A-Time, agricultural policy, climate change.

  9. Sensitivity analysis of a Pelton hydropower station based on a novel approach of turbine torque

    International Nuclear Information System (INIS)

    Xu, Beibei; Yan, Donglin; Chen, Diyi; Gao, Xiang; Wu, Changzhi

    2017-01-01

    Highlights: • A novel approach of the turbine torque is proposed. • A unify model is capable of the dynamic characteristics of Pelton hydropower stations. • Sensitivity analysis from hydraulic parameters, mechanic parameters and electric parameters are performed. • Numerical simulations show the sensitivity ranges of the above three parameters. - Abstract: Hydraulic turbine generator units with long-running operation may cause the values of hydraulic, mechanic or electric parameters changing gradually, which brings a new challenge, namely that whether the operating stability of these units will be changed in the next thirty or forty years. This paper is an attempt to seek a relatively unified model for sensitivity analysis from three aspects: hydraulic parameters (turbine flow and turbine head), mechanic parameters (axis coordinates and axial misalignment) and electric parameters (generator speed and excitation current). First, a novel approach of the Pelton turbine torque is proposed, which can make connections between the hydraulic turbine governing system and the shafting system of the hydro-turbine generator unit. Moreover, the correctness of this approach is verified by comparing with other three models of hydropower stations. Second, this latter is analyzed to obtain the sensitivity of electric parameter (excitation current), the mechanic parameters (axial misalignment, upper guide bearing rigidity, lower guide bearing rigidity, and turbine guide bearing rigidity) on hydraulic parameters on the operating stability of the unit. In addition to this, some critical values and ranges are proposed. Finally, these results can provide some bases for the design and stable operation of Peltonhydropower stations.

  10. Inverse modeling for seawater intrusion in coastal aquifers: Insights about parameter sensitivities, variances, correlations and estimation procedures derived from the Henry problem

    Science.gov (United States)

    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

  11. 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.

  12. Sensitivity Analysis Applied in Design of Low Energy Office Building

    DEFF Research Database (Denmark)

    Heiselberg, Per; Brohus, Henrik

    2008-01-01

    satisfies the design requirements and objectives. In the design of sustainable Buildings it is beneficial to identify the most important design parameters in order to develop more efficiently alternative design solutions or reach optimized design solutions. A sensitivity analysis makes it possible...

  13. Uncertainty and sensitivity analysis of the nuclear fuel thermal behavior

    Energy Technology Data Exchange (ETDEWEB)

    Boulore, A., E-mail: antoine.boulore@cea.fr [Commissariat a l' Energie Atomique (CEA), DEN, Fuel Research Department, 13108 Saint-Paul-lez-Durance (France); Struzik, C. [Commissariat a l' Energie Atomique (CEA), DEN, Fuel Research Department, 13108 Saint-Paul-lez-Durance (France); Gaudier, F. [Commissariat a l' Energie Atomique (CEA), DEN, Systems and Structure Modeling Department, 91191 Gif-sur-Yvette (France)

    2012-12-15

    Highlights: Black-Right-Pointing-Pointer A complete quantitative method for uncertainty propagation and sensitivity analysis is applied. Black-Right-Pointing-Pointer The thermal conductivity of UO{sub 2} is modeled as a random variable. Black-Right-Pointing-Pointer The first source of uncertainty is the linear heat rate. Black-Right-Pointing-Pointer The second source of uncertainty is the thermal conductivity of the fuel. - Abstract: In the global framework of nuclear fuel behavior simulation, the response of the models describing the physical phenomena occurring during the irradiation in reactor is mainly conditioned by the confidence in the calculated temperature of the fuel. Amongst all parameters influencing the temperature calculation in our fuel rod simulation code (METEOR V2), several sources of uncertainty have been identified as being the most sensitive: thermal conductivity of UO{sub 2}, radial distribution of power in the fuel pellet, local linear heat rate in the fuel rod, geometry of the pellet and thermal transfer in the gap. Expert judgment and inverse methods have been used to model the uncertainty of these parameters using theoretical distributions and correlation matrices. Propagation of these uncertainties in the METEOR V2 code using the URANIE framework and a Monte-Carlo technique has been performed in different experimental irradiations of UO{sub 2} fuel. At every time step of the simulated experiments, we get a temperature statistical distribution which results from the initial distributions of the uncertain parameters. We then can estimate confidence intervals of the calculated temperature. In order to quantify the sensitivity of the calculated temperature to each of the uncertain input parameters and data, we have also performed a sensitivity analysis using the Sobol' indices at first order.

  14. Transcranial magnetic stimulation (TMS): compared sensitivity of different motor response parameters in ALS.

    Science.gov (United States)

    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.

  15. A sensitivity analysis and assessment on the reactivity, economics and resorce implications of reactor systems and cycles with respect to uncertainity in nuclear data and other reactor parameters

    International Nuclear Information System (INIS)

    Quan, B.L.

    1980-01-01

    A general sensitivity analysis system for analyzing the effects of uncertainity in nuclear data and reactor parameters on fuel cycle economics, resources and physics has been developed. The sensitivity analysis has been performed on various reactor systems and cycles such as the thorium cycles, plutonium cycles, CANDU reactor fuel cycles and alternate once-through LWR cycles such as the 18 month cycle. Sensitivity coefficients were generated for a variety of materials pertinent to the LWR fuel cycle using a series of fast running codes developed for this purpose and running on a local PDP-15 computer. Their relative order of importance were assessed and the reasons explaining this difference were examined. This work is a result of EPRI project in determining the data needs for the LWR industry and should be valuable in identifying areas in which data improvements are worthwhile

  16. Sensitivity analysis of numerical results of one- and two-dimensional advection-diffusion problems

    International Nuclear Information System (INIS)

    Motoyama, Yasunori; Tanaka, Nobuatsu

    2005-01-01

    Numerical simulation has been playing an increasingly important role in the fields of science and engineering. However, every numerical result contains errors such as modeling, truncation, and computing errors, and the magnitude of the errors that are quantitatively contained in the results is unknown. This situation causes a large design margin in designing by analyses and prevents further cost reduction by optimizing design. To overcome this situation, we developed a new method to numerically analyze the quantitative error of a numerical solution by using the sensitivity analysis method and modified equation approach. If a reference case of typical parameters is calculated once by this method, then no additional calculation is required to estimate the results of other numerical parameters such as those of parameters with higher resolutions. Furthermore, we can predict the exact solution from the sensitivity analysis results and can quantitatively evaluate the error of numerical solutions. Since the method incorporates the features of the conventional sensitivity analysis method, it can evaluate the effect of the modeling error as well as the truncation error. In this study, we confirm the effectiveness of the method through some numerical benchmark problems of one- and two-dimensional advection-diffusion problems. (author)

  17. Sensitivity analysis on a dose-calculation model for the terrestrial food-chain pathway

    International Nuclear Information System (INIS)

    Abdel-Aal, M.M.

    1994-01-01

    Parameter uncertainty and sensitivity were applied to the U.S. Regulatory Commission's (NRC) Regulatory Guide 1.109 (1977) models for calculating the ingestion dose via a terrestrial food-chain pathway in order to assess the transport of chronically released, low-level effluents from light-water reactors. In the analysis, we used the generation of latin hypercube samples (LHS) and employed a constrained sampling scheme. The generation of these samples is based on information supplied to the LHS program for variables or parameters. The actually sampled values are used to form vectors of variables that are commonly used as inputs to computer models for the purpose of sensitivity and uncertainty analysis. Regulatory models consider the concentrations of radionuclides that are deposited on plant tissues or lead to root uptake of nuclides initially deposited on soil. We also consider concentrations in milk and beef as a consequence of grazing on contaminated pasture or ingestion of contaminated feed by dairy and beef cattle. The radionuclides Sr-90 and Cs-137 were selected for evaluation. The most sensitive input parameters for the model were the ground-dispersion parameter, release rates of radionuclides, and soil-to-plant transfer coefficients of radionuclides. (Author)

  18. Application of Latin hypercube sampling to RADTRAN 4 truck accident risk sensitivity analysis

    International Nuclear Information System (INIS)

    Mills, G.S.; Neuhauser, K.S.; Kanipe, F.L.

    1994-01-01

    The sensitivity of calculated dose estimates to various RADTRAN 4 inputs is an available output for incident-free analysis because the defining equations are linear and sensitivity to each variable can be calculated in closed mathematical form. However, the necessary linearity is not characteristic of the equations used in calculation of accident dose risk, making a similar tabulation of sensitivity for RADTRAN 4 accident analysis impossible. Therefore, a study of sensitivity of accident risk results to variation of input parameters was performed using representative routes, isotopic inventories, and packagings. It was determined that, of the approximately two dozen RADTRAN 4 input parameters pertinent to accident analysis, only a subset of five or six has significant influence on typical analyses or is subject to random uncertainties. These five or six variables were selected as candidates for Latin Hypercube Sampling applications. To make the effect of input uncertainties on calculated accident risk more explicit, distributions and limits were determined for two variables which had approximately proportional effects on calculated doses: Pasquill Category probability (PSPROB) and link population density (LPOPD). These distributions and limits were used as input parameters to Sandia's Latin Hypercube Sampling code to generate 50 sets of RADTRAN 4 input parameters used together with point estimates of other necessary inputs to calculate 50 observations of estimated accident dose risk.Tabulations of the RADTRAN 4 accident risk input variables and their influence on output plus illustrative examples of the LHS calculations, for truck transport situations that are typical of past experience, will be presented

  19. 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

  20. 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....

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

    Science.gov (United States)

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

    2012-04-01

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

  2. Sensitivity analysis of thermal hydraulic response in containment at core meltdown accident

    International Nuclear Information System (INIS)

    Kobayashi, Kensuke; Ishigami, Tsutomu; Horii, Hideo; Chiba, Takemi.

    1985-01-01

    A sensitivity analysis of thermal hydraulic response in a containment during a 'station blackout' (the loss of all AC power) accident at Browns Ferry unit one plant was performed with the computer code MARCH 1.0. In the analysis, the plant station batteries were assumed to be available for 4h after the initiation of the accident. The thermal hydraulic response in the containment was calculated by varying several input data for MARCH 1.0 independently and the deviation among calculated results were investigated. The sensitivity analysis showed that (a) the containment would fail due to the overtemperature without any operator actions for plant recovery, which would be strongly dependent on the model of the debris-concrete interaction and the input parameters for specifying the containment failure modes in MARCH 1.0, (b) a core melting temperature and an amount of water left in a primary system at the end of the meltdown were identified as important parameters which influenced the time of the containment failure, and (c) experimental works regarding the parameters mentioned above could be recommended. (author)

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

    International Nuclear Information System (INIS)

    Hirschberg, S.; Knochenhauer, M.

    1986-01-01

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

  4. On uncertainty and local sensitivity analysis for transient conjugate heat transfer problems

    International Nuclear Information System (INIS)

    Rauch, Christian

    2012-01-01

    The need for simulating real-world behavior of automobiles has led to more and more sophisticated models being added of various physical phenomena for being coupled together. This increases the number of parameters to be set and, consequently, the required knowledge of their relative importance for the solution and the theory behind them. Sensitivity and uncertainty analysis provides the knowledge of parameter importance. In this paper a thermal radiation solver is considered that performs conduction calculations and receives heat transfer coefficient and fluid temperate at a thermal node. The equations of local, discrete, and transient sensitivities for the conjugate heat transfer model solved by the finite difference method are being derived for some parameters. In the past, formulations for the finite element method have been published. This paper builds on the steady-state formulation published previously by the author. A numerical analysis on the stability of the solution matrix is being conducted. From those normalized sensitivity coefficients are calculated dimensionless uncertainty factors. On a simplified example the relative importance of the heat transfer modes at various locations is then investigated by those uncertainty factors and their changes over time

  5. High order effects in cross section sensitivity analysis

    International Nuclear Information System (INIS)

    Greenspan, E.; Karni, Y.; Gilai, D.

    1978-01-01

    Two types of high order effects associated with perturbations in the flux shape are considered: Spectral Fine Structure Effects (SFSE) and non-linearity between changes in performance parameters and data uncertainties. SFSE are investigated in Part I using a simple single resonance model. Results obtained for each of the resolved and for representative unresolved resonances of 238 U in a ZPR-6/7 like environment indicate that SFSE can have a significant contribution to the sensitivity of group constants to resonance parameters. Methods to account for SFSE both for the propagation of uncertainties and for the adjustment of nuclear data are discussed. A Second Order Sensitivity Theory (SOST) is presented, and its accuracy relative to that of the first order sensitivity theory and of the direct substitution method is investigated in Part II. The investigation is done for the non-linear problem of the effect of changes in the 297 keV sodium minimum cross section on the transport of neutrons in a deep-penetration problem. It is found that the SOST provides a satisfactory accuracy for cross section uncertainty analysis. For the same degree of accuracy, the SOST can be significantly more efficient than the direct substitution method

  6. Sensitivity analysis techniques applied to a system of hyperbolic conservation laws

    International Nuclear Information System (INIS)

    Weirs, V. Gregory; Kamm, James R.; Swiler, Laura P.; Tarantola, Stefano; Ratto, Marco; Adams, Brian M.; Rider, William J.; Eldred, Michael S.

    2012-01-01

    Sensitivity analysis is comprised of techniques to quantify the effects of the input variables on a set of outputs. In particular, sensitivity indices can be used to infer which input parameters most significantly affect the results of a computational model. With continually increasing computing power, sensitivity analysis has become an important technique by which to understand the behavior of large-scale computer simulations. Many sensitivity analysis methods rely on sampling from distributions of the inputs. Such sampling-based methods can be computationally expensive, requiring many evaluations of the simulation; in this case, the Sobol' method provides an easy and accurate way to compute variance-based measures, provided a sufficient number of model evaluations are available. As an alternative, meta-modeling approaches have been devised to approximate the response surface and estimate various measures of sensitivity. In this work, we consider a variety of sensitivity analysis methods, including different sampling strategies, different meta-models, and different ways of evaluating variance-based sensitivity indices. The problem we consider is the 1-D Riemann problem. By a careful choice of inputs, discontinuous solutions are obtained, leading to discontinuous response surfaces; such surfaces can be particularly problematic for meta-modeling approaches. The goal of this study is to compare the estimated sensitivity indices with exact values and to evaluate the convergence of these estimates with increasing samples sizes and under an increasing number of meta-model evaluations. - Highlights: ► Sensitivity analysis techniques for a model shock physics problem are compared. ► The model problem and the sensitivity analysis problem have exact solutions. ► Subtle details of the method for computing sensitivity indices can affect the results.

  7. Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems.

    Science.gov (United States)

    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.

  8. Method-independent, Computationally Frugal Convergence Testing for Sensitivity Analysis Techniques

    Science.gov (United States)

    Mai, J.; Tolson, B.

    2017-12-01

    The increasing complexity and runtime of environmental models lead to the current situation that the calibration of all model parameters or the estimation of all of their uncertainty is often computationally infeasible. Hence, techniques to determine the sensitivity of model parameters are used to identify most important parameters. All subsequent model calibrations or uncertainty estimation procedures focus then only on these subsets of parameters and are hence less computational demanding. While the examination of the convergence of calibration and uncertainty methods is state-of-the-art, the convergence of the sensitivity methods is usually not checked. If any, bootstrapping of the sensitivity results is used to determine the reliability of the estimated indexes. Bootstrapping, however, might as well become computationally expensive in case of large model outputs and a high number of bootstraps. We, therefore, present a Model Variable Augmentation (MVA) approach to check the convergence of sensitivity indexes without performing any additional model run. This technique is method- and model-independent. It can be applied either during the sensitivity analysis (SA) or afterwards. The latter case enables the checking of already processed sensitivity indexes. To demonstrate the method's independency of the convergence testing method, we applied it to two widely used, global SA methods: the screening method known as Morris method or Elementary Effects (Morris 1991) and the variance-based Sobol' method (Solbol' 1993). The new convergence testing method is first scrutinized using 12 analytical benchmark functions (Cuntz & Mai et al. 2015) where the true indexes of aforementioned three methods are known. This proof of principle shows that the method reliably determines the uncertainty of the SA results when different budgets are used for the SA. The results show that the new frugal method is able to test the convergence and therefore the reliability of SA results in an

  9. Uncertainty and sensitivity analysis of parameters affecting water hammer pressure wave behaviour

    International Nuclear Information System (INIS)

    Kaliatka, A.; Uspuras, E.; Vaisnoras, M.

    2006-01-01

    Pressure surges occurring in pipeline systems may be caused by fast control interference, start up and shut down processes and operation failure. They lead to water hammer upstream the closing valve and cavitational hammer downstream the valve, which may cause considerable damages to the pipeline and the support structures. Appearance of water hammer in thermal-hydraulic systems was widely studied employing different state-of-the-art thermal-hydraulic codes in many organizations. For the analysis water hammer test performed at Fraunhofer Institute for Environmental, Safety and Energy Technology (UMSICHT) at Oberhausen was considered. This paper presents the comparison of UMSICHT test facility experiment calculations employing the best estimate system code RELAP5/Mod3.3 to measured water hammer values after fast closure of a valve. The analysis revealed that the calculated first pressure peak, which has the highest value, matches the measured value very well. The performed analysis (as well as any other analyses) as a results of each individual calculation always contains uncertainty owing to initial conditions of installations, errors of measuring systems, errors caused by nodalization of objects at modelling, code correlations, etc. In this connection, results of uncertainty and sensitivity analysis of the initial conditions and code-selected models are shown in the paper. (orig.)

  10. Irradiation and gamma-ray spectrometric parameters for 129I neutron-activation analysis

    International Nuclear Information System (INIS)

    Brauer, F.P.; Strebin, R.S. Jr.; Mitzlaff, W.A.; Kaye, J.H.

    1983-09-01

    This paper describes the influence of reactor neutron irradiation facilities on low-level 129 I analysis methodology. Three reactors are compared - the HFIR at ORNL, the N-Reactor at Hanford, and a 1-MW research reactor at Washington State University, Pullman, WA. Parameters compared include sensitivity for 129 I and natural iodine and interference effects due to high levels of 127 I in irradiated samples. Selection of detector systems for off-site use at HFIR is discussed. A comparison of neutron activation analysis with other sensitive detection methods for measurement of 129 I is given

  11. Sensitivity analysis of reactive ecological dynamics.

    Science.gov (United States)

    Verdy, Ariane; Caswell, Hal

    2008-08-01

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

  12. Sensitivity analysis with respect to observations in variational data assimilation for parameter estimation

    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.

  13. An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    S. Razmyan

    2012-01-01

    Full Text Available Discriminant analysis (DA is used for the measurement of estimates of a discriminant function by minimizing their group misclassifications to predict group membership of newly sampled data. A major source of misclassification in DA is due to the overlapping of groups. The uncertainty in the input variables and model parameters needs to be properly characterized in decision making. This study combines DEA-DA with a sensitivity analysis approach to an assessment of the influence of banks’ variables on the overall variance in overlap in a DA in order to determine which variables are most significant. A Monte-Carlo-based sensitivity analysis is considered for computing the set of first-order sensitivity indices of the variables to estimate the contribution of each uncertain variable. The results show that the uncertainties in the loans granted and different deposit variables are more significant than uncertainties in other banks’ variables in decision making.

  14. Sensitivity Analysis of OECD Benchmark Tests in BISON

    Energy Technology Data Exchange (ETDEWEB)

    Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gamble, Kyle [Idaho National Lab. (INL), Idaho Falls, ID (United States); Schmidt, Rodney C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Williamson, Richard [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-09-01

    This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on sensitivity analysis of a fuels performance benchmark problem. The benchmark problem was defined by the Uncertainty Analysis in Modeling working group of the Nuclear Science Committee, part of the Nuclear Energy Agency of the Organization for Economic Cooperation and Development (OECD ). The benchmark problem involv ed steady - state behavior of a fuel pin in a Pressurized Water Reactor (PWR). The problem was created in the BISON Fuels Performance code. Dakota was used to generate and analyze 300 samples of 17 input parameters defining core boundary conditions, manuf acturing tolerances , and fuel properties. There were 24 responses of interest, including fuel centerline temperatures at a variety of locations and burnup levels, fission gas released, axial elongation of the fuel pin, etc. Pearson and Spearman correlatio n coefficients and Sobol' variance - based indices were used to perform the sensitivity analysis. This report summarizes the process and presents results from this study.

  15. An easily implemented static condensation method for structural sensitivity analysis

    Science.gov (United States)

    Gangadharan, S. N.; Haftka, R. T.; Nikolaidis, E.

    1990-01-01

    A black-box approach to static condensation for sensitivity analysis is presented with illustrative examples of a cube and a car structure. The sensitivity of the structural response with respect to joint stiffness parameter is calculated using the direct method, forward-difference, and central-difference schemes. The efficiency of the various methods for identifying joint stiffness parameters from measured static deflections of these structures is compared. The results indicate that the use of static condensation can reduce computation times significantly and the black-box approach is only slightly less efficient than the standard implementation of static condensation. The ease of implementation of the black-box approach recommends it for use with general-purpose finite element codes that do not have a built-in facility for static condensation.

  16. Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems?

    Science.gov (United States)

    Safaei, S.; Haghnegahdar, A.; Razavi, S.

    2016-12-01

    Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.

  17. Sensitivity analysis for unobserved confounding of direct and indirect effects using uncertainty intervals.

    Science.gov (United States)

    Lindmark, Anita; de Luna, Xavier; Eriksson, Marie

    2018-05-10

    To estimate direct and indirect effects of an exposure on an outcome from observed data, strong assumptions about unconfoundedness are required. Since these assumptions cannot be tested using the observed data, a mediation analysis should always be accompanied by a sensitivity analysis of the resulting estimates. In this article, we propose a sensitivity analysis method for parametric estimation of direct and indirect effects when the exposure, mediator, and outcome are all binary. The sensitivity parameters consist of the correlations between the error terms of the exposure, mediator, and outcome models. These correlations are incorporated into the estimation of the model parameters and identification sets are then obtained for the direct and indirect effects for a range of plausible correlation values. We take the sampling variability into account through the construction of uncertainty intervals. The proposed method is able to assess sensitivity to both mediator-outcome confounding and confounding involving the exposure. To illustrate the method, we apply it to a mediation study based on the data from the Swedish Stroke Register (Riksstroke). An R package that implements the proposed method is available. Copyright © 2018 John Wiley & Sons, Ltd.

  18. Parameter Analysis of the VPIN (Volume synchronized Probability of Informed Trading) Metric

    Energy Technology Data Exchange (ETDEWEB)

    Song, Jung Heon; Wu, Kesheng; Simon, Horst D.

    2014-03-01

    VPIN (Volume synchronized Probability of Informed trading) is a leading indicator of liquidity-induced volatility. It is best known for having produced a signal more than hours before the Flash Crash of 2010. On that day, the market saw the biggest one-day point decline in the Dow Jones Industrial Average, which culminated to the market value of $1 trillion disappearing, but only to recover those losses twenty minutes later (Lauricella 2010). The computation of VPIN requires the user to set up a handful of free parameters. The values of these parameters significantly affect the effectiveness of VPIN as measured by the false positive rate (FPR). An earlier publication reported that a brute-force search of simple parameter combinations yielded a number of parameter combinations with FPR of 7%. This work is a systematic attempt to find an optimal parameter set using an optimization package, NOMAD (Nonlinear Optimization by Mesh Adaptive Direct Search) by Audet, le digabel, and tribes (2009) and le digabel (2011). We have implemented a number of techniques to reduce the computation time with NOMAD. Tests show that we can reduce the FPR to only 2%. To better understand the parameter choices, we have conducted a series of sensitivity analysis via uncertainty quantification on the parameter spaces using UQTK (Uncertainty Quantification Toolkit). Results have shown dominance of 2 parameters in the computation of FPR. Using the outputs from NOMAD optimization and sensitivity analysis, We recommend A range of values for each of the free parameters that perform well on a large set of futures trading records.

  19. Sensitivity analysis methods and a biosphere test case implemented in EIKOS

    Energy Technology Data Exchange (ETDEWEB)

    Ekstroem, P.A.; Broed, R. [Facilia AB, Stockholm, (Sweden)

    2006-05-15

    Computer-based models can be used to approximate real life processes. These models are usually based on mathematical equations, which are dependent on several variables. The predictive capability of models is therefore limited by the uncertainty in the value of these. Sensitivity analysis is used to apportion the relative importance each uncertain input parameter has on the output variation. Sensitivity analysis is therefore an essential tool in simulation modelling and for performing risk assessments. Simple sensitivity analysis techniques based on fitting the output to a linear equation are often used, for example correlation or linear regression coefficients. These methods work well for linear models, but for non-linear models their sensitivity estimations are not accurate. Usually models of complex natural systems are non-linear. Within the scope of this work, various sensitivity analysis methods, which can cope with linear, non-linear, as well as non-monotone problems, have been implemented, in a software package, EIKOS, written in Matlab language. The following sensitivity analysis methods are supported by EIKOS: Pearson product moment correlation coefficient (CC), Spearman Rank Correlation Coefficient (RCC), Partial (Rank) Correlation Coefficients (PCC), Standardized (Rank) Regression Coefficients (SRC), Sobol' method, Jansen's alternative, Extended Fourier Amplitude Sensitivity Test (EFAST) as well as the classical FAST method and the Smirnov and the Cramer-von Mises tests. A graphical user interface has also been developed, from which the user easily can load or call the model and perform a sensitivity analysis as well as uncertainty analysis. The implemented sensitivity analysis methods has been benchmarked with well-known test functions and compared with other sensitivity analysis software, with successful results. An illustration of the applicability of EIKOS is added to the report. The test case used is a landscape model consisting of several

  20. Sensitivity analysis methods and a biosphere test case implemented in EIKOS

    International Nuclear Information System (INIS)

    Ekstroem, P.A.; Broed, R.

    2006-05-01

    Computer-based models can be used to approximate real life processes. These models are usually based on mathematical equations, which are dependent on several variables. The predictive capability of models is therefore limited by the uncertainty in the value of these. Sensitivity analysis is used to apportion the relative importance each uncertain input parameter has on the output variation. Sensitivity analysis is therefore an essential tool in simulation modelling and for performing risk assessments. Simple sensitivity analysis techniques based on fitting the output to a linear equation are often used, for example correlation or linear regression coefficients. These methods work well for linear models, but for non-linear models their sensitivity estimations are not accurate. Usually models of complex natural systems are non-linear. Within the scope of this work, various sensitivity analysis methods, which can cope with linear, non-linear, as well as non-monotone problems, have been implemented, in a software package, EIKOS, written in Matlab language. The following sensitivity analysis methods are supported by EIKOS: Pearson product moment correlation coefficient (CC), Spearman Rank Correlation Coefficient (RCC), Partial (Rank) Correlation Coefficients (PCC), Standardized (Rank) Regression Coefficients (SRC), Sobol' method, Jansen's alternative, Extended Fourier Amplitude Sensitivity Test (EFAST) as well as the classical FAST method and the Smirnov and the Cramer-von Mises tests. A graphical user interface has also been developed, from which the user easily can load or call the model and perform a sensitivity analysis as well as uncertainty analysis. The implemented sensitivity analysis methods has been benchmarked with well-known test functions and compared with other sensitivity analysis software, with successful results. An illustration of the applicability of EIKOS is added to the report. The test case used is a landscape model consisting of several linked

  1. Uncertainty and sensitivity analysis: Mathematical model of coupled heat and mass transfer for a contact baking process

    DEFF Research Database (Denmark)

    Feyissa, Aberham Hailu; Gernaey, Krist; Adler-Nissen, Jens

    2012-01-01

    to uncertainty in the model predictions. The aim of the current paper is to address this uncertainty challenge in the modelling of food production processes using a combination of uncertainty and sensitivity analysis, where the uncertainty analysis and global sensitivity analysis were applied to a heat and mass......Similar to other processes, the modelling of heat and mass transfer during food processing involves uncertainty in the values of input parameters (heat and mass transfer coefficients, evaporation rate parameters, thermo-physical properties, initial and boundary conditions) which leads...

  2. Thermal-Hydraulic Sensitivity Study of Intermediate Loop Parameters for Nuclear Hydrogen Production System

    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.

  3. 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

  4. Simplified procedures for fast reactor fuel cycle and sensitivity analysis

    International Nuclear Information System (INIS)

    Badruzzaman, A.

    1979-01-01

    The Continuous Slowing Down-Integral Transport Theory has been extended to perform criticality calculations in a Fast Reactor Core-blanket system achieving excellent prediction of the spectrum and the eigenvalue. The integral transport parameters did not need recalculation with source iteration and were found to be relatively constant with exposure. Fuel cycle parameters were accurately predicted when these were not varied, thus reducing a principal potential penalty of the Intergal Transport approach where considerable effort may be required to calculate transport parameters in more complicated geometries. The small variation of the spectrum in the central core region, and its weak dependence on exposure for both this region, the core blanket interface and blanket region led to the extension and development of inexpensive simplified procedures to complement exact methods. These procedures gave accurate predictions of the key fuel cycle parameters such as cost and their sensitivity to variation in spectrum-averaged and multigroup cross sections. They also predicted the implications of design variation on these parameters very well. The accuracy of these procedures and their use in analyzing a wide variety of sensitivities demonstrate the potential utility of survey calculations in Fast Reactor analysis and fuel management

  5. BEMUSE Phase III Report - Uncertainty and Sensitivity Analysis of the LOFT L2-5 Test

    International Nuclear Information System (INIS)

    Bazin, P.; Crecy, A. de; Glaeser, H.; Skorek, T.; Joucla, J.; Probst, P.; Chung, B.; Oh, D.Y.; Kyncl, M.; Pernica, R.; Macek, J.; Meca, R.; Macian, R.; D'Auria, F.; Petruzzi, A.; Perez, M.; Reventos, F.; Fujioka, K.

    2007-02-01

    This report summarises the various contributions (ten participants) for phase 3 of BEMUSE: Uncertainty and Sensitivity Analyses of the LOFT L2-5 experiment, a Large-Break Loss-of-Coolant-Accident (LB-LOCA). For this phase, precise requirements step by step were provided to the participants. Four main parts are defined, which are: 1. List and uncertainties of the input uncertain parameters. 2. Uncertainty analysis results. 3. Sensitivity analysis results. 4. Improved methods, assessment of the methods (optional). 5% and 95% percentiles have to be estimated for 6 output parameters, which are of two kinds: 1. Scalar output parameters (First Peak Cladding Temperature (PCT), Second Peak Cladding Temperature, Time of accumulator injection, Time of complete quenching); 2. Time trends output parameters (Maximum cladding temperature, Upper plenum pressure). The main lessons learnt from phase 3 of the BEMUSE programme are the following: - for uncertainty analysis, all the participants use a probabilistic method associated with the use of Wilks' formula, except for UNIPI with its CIAU method (Code with the Capability of Internal Assessment of Uncertainty). Use of both methods has been successfully mastered. - Compared with the experiment, the results of uncertainty analysis are good on the whole. For example, for the cladding temperature-type output parameters (1. PCT, 2. PCT, time of complete quenching, maximum cladding temperature), 8 participants out of 10 find upper and lower bounds which envelop the experimental data. - Sensitivity analysis has been successfully performed by all the participants using the probabilistic method. All the used influence measures include the range of variation of the input parameters. Synthesis tables of the most influential phenomena and parameters have been plotted and participants will be able to use them for the continuation of the BEMUSE programme

  6. SENSIT: a cross-section and design sensitivity and uncertainty analysis code. [In FORTRAN for CDC-7600, IBM 360

    Energy Technology Data Exchange (ETDEWEB)

    Gerstl, S.A.W.

    1980-01-01

    SENSIT computes the sensitivity and uncertainty of a calculated integral response (such as a dose rate) due to input cross sections and their uncertainties. Sensitivity profiles are computed for neutron and gamma-ray reaction cross sections of standard multigroup cross section sets and for secondary energy distributions (SEDs) of multigroup scattering matrices. In the design sensitivity mode, SENSIT computes changes in an integral response due to design changes and gives the appropriate sensitivity coefficients. Cross section uncertainty analyses are performed for three types of input data uncertainties: cross-section covariance matrices for pairs of multigroup reaction cross sections, spectral shape uncertainty parameters for secondary energy distributions (integral SED uncertainties), and covariance matrices for energy-dependent response functions. For all three types of data uncertainties SENSIT computes the resulting variance and estimated standard deviation in an integral response of interest, on the basis of generalized perturbation theory. SENSIT attempts to be more comprehensive than earlier sensitivity analysis codes, such as SWANLAKE.

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

    Directory of Open Access Journals (Sweden)

    Elaine O Nsoesie

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

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

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  9. Design optimization of structural parameters for highly sensitive photonic crystal label-free biosensors.

    Science.gov (United States)

    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.

  10. Design Optimization of Structural Parameters for Highly Sensitive Photonic Crystal Label-Free Biosensors

    Directory of Open Access Journals (Sweden)

    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.

  11. Comparison of global sensitivity analysis methods – Application to fuel behavior modeling

    Energy Technology Data Exchange (ETDEWEB)

    Ikonen, Timo, E-mail: timo.ikonen@vtt.fi

    2016-02-15

    Highlights: • Several global sensitivity analysis methods are compared. • The methods’ applicability to nuclear fuel performance simulations is assessed. • The implications of large input uncertainties and complex models are discussed. • Alternative strategies to perform sensitivity analyses are proposed. - Abstract: Fuel performance codes have two characteristics that make their sensitivity analysis challenging: large uncertainties in input parameters and complex, non-linear and non-additive structure of the models. The complex structure of the code leads to interactions between inputs that show as cross terms in the sensitivity analysis. Due to the large uncertainties of the inputs these interactions are significant, sometimes even dominating the sensitivity analysis. For the same reason, standard linearization techniques do not usually perform well in the analysis of fuel performance codes. More sophisticated methods are typically needed in the analysis. To this end, we compare the performance of several sensitivity analysis methods in the analysis of a steady state FRAPCON simulation. The comparison of importance rankings obtained with the various methods shows that even the simplest methods can be sufficient for the analysis of fuel maximum temperature. However, the analysis of the gap conductance requires more powerful methods that take into account the interactions of the inputs. In some cases, moment-independent methods are needed. We also investigate the computational cost of the various methods and present recommendations as to which methods to use in the analysis.

  12. Application of Wielandt method in continuous-energy nuclear data sensitivity analysis with RMC code

    International Nuclear Information System (INIS)

    Qiu Yishu; Wang Kan; She Ding

    2015-01-01

    The Iterated Fission Probability (IFP) method, an accurate method to estimate adjoint-weighted quantities in the continuous-energy Monte Carlo criticality calculations, has been widely used for calculating kinetic parameters and nuclear data sensitivity coefficients. By using a strategy of waiting, however, this method faces the challenge of high memory usage to store the tallies of original contributions which size is proportional to the number of particle histories in each cycle. Recently, the Wielandt method, applied by Monte Carlo code McCARD to calculate kinetic parameters, estimates adjoint fluxes in a single particle history and thus can save memory usage. In this work, the Wielandt method has been applied in Rector Monte Carlo code RMC for nuclear data sensitivity analysis. The methodology and algorithm of applying Wielandt method in estimation of adjoint-based sensitivity coefficients are discussed. Verification is performed by comparing the sensitivity coefficients calculated by Wielandt method with analytical solutions, those computed by IFP method which is also implemented in RMC code for sensitivity analysis, and those from the multi-group TSUNAMI-3D module in SCALE code package. (author)

  13. Development and Sensitivity Analysis of a Fully Kinetic Model of Sequential Reductive Dechlorination in Groundwater

    DEFF Research Database (Denmark)

    Malaguerra, Flavio; Chambon, Julie Claire Claudia; Bjerg, Poul Løgstrup

    2011-01-01

    experiments of complete trichloroethene (TCE) degradation in natural sediments. Global sensitivity analysis was performed using the Morris method and Sobol sensitivity indices to identify the most influential model parameters. Results show that the sulfate concentration and fermentation kinetics are the most...

  14. Sensitivity Analysis of Multidisciplinary Rotorcraft Simulations

    Science.gov (United States)

    Wang, Li; Diskin, Boris; Biedron, Robert T.; Nielsen, Eric J.; Bauchau, Olivier A.

    2017-01-01

    A multidisciplinary sensitivity analysis of rotorcraft simulations involving tightly coupled high-fidelity computational fluid dynamics and comprehensive analysis solvers is presented and evaluated. An unstructured sensitivity-enabled Navier-Stokes solver, FUN3D, and a nonlinear flexible multibody dynamics solver, DYMORE, are coupled to predict the aerodynamic loads and structural responses of helicopter rotor blades. A discretely-consistent adjoint-based sensitivity analysis available in FUN3D provides sensitivities arising from unsteady turbulent flows and unstructured dynamic overset meshes, while a complex-variable approach is used to compute DYMORE structural sensitivities with respect to aerodynamic loads. The multidisciplinary sensitivity analysis is conducted through integrating the sensitivity components from each discipline of the coupled system. Numerical results verify accuracy of the FUN3D/DYMORE system by conducting simulations for a benchmark rotorcraft test model and comparing solutions with established analyses and experimental data. Complex-variable implementation of sensitivity analysis of DYMORE and the coupled FUN3D/DYMORE system is verified by comparing with real-valued analysis and sensitivities. Correctness of adjoint formulations for FUN3D/DYMORE interfaces is verified by comparing adjoint-based and complex-variable sensitivities. Finally, sensitivities of the lift and drag functions obtained by complex-variable FUN3D/DYMORE simulations are compared with sensitivities computed by the multidisciplinary sensitivity analysis, which couples adjoint-based flow and grid sensitivities of FUN3D and FUN3D/DYMORE interfaces with complex-variable sensitivities of DYMORE structural responses.

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

    Directory of Open Access Journals (Sweden)

    Z. Xu

    2018-01-01

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

  16. Sensitivity analysis of system parameters on the performance of the Organic Rankine Cycle system for binary-cycle geothermal power plants

    International Nuclear Information System (INIS)

    Liu, Xiaomin; Wang, Xing; Zhang, Chuhua

    2014-01-01

    The main purpose of this paper is to analyze the sensitivity of system parameters to the performance of the Organic Rankine Cycle (ORC) system quantitatively. A thermodynamic model of the ORC system for binary-cycle geothermal power plants has been developed and verified. The system parameters, such as working fluid, superheat temperature, pinch temperature difference in evaporator and condenser, evaporating temperature, the isentropic efficiencies of the cycle pump and radial inflow turbine are selected as six factors for orthogonal design. The order of factors sensitivity on performance indices of the net power output of the ORC system, the thermal efficiency, the size parameter of radial inflow turbine, the power decrease factor of the pump and the total heat transfer capacity are determined by the range obtained from the orthogonal design. At different geothermal temperatures, the ranges of the six factors corresponding to performance indices are analyzed respectively. The results show that the geothermal temperature influences the range of the factors to the net power output, SP factor of radial inflow turbine, and the total heat transfer capacity, but it has no effect for the range of the factors for the thermal efficiency and the power decrease factor of the pump. The evaporating temperature is always the primary or secondary factor that influence the thermodynamic and economic performance of the ORC system. This study would provide useful references for determining the proper design variables in the performance optimization of the ORC system at different geothermal temperatures. - Highlights: • Evaporating temperature has significant effect on performance of ORC system. • Order of system parameters' sensitivity to the performance of ORC is revealed. • Effect of system parameters on performance indices vary with geothermal temperature. • Geothermal temperature has no effect on range of six factors to the size of turbine

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

    Science.gov (United States)

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

  18. Demonstration of uncertainty quantification and sensitivity analysis for PWR fuel performance with BISON

    International Nuclear Information System (INIS)

    Zhang, Hongbin; Zhao, Haihua; Zou, Ling; Burns, Douglas; Ladd, Jacob

    2017-01-01

    BISON is an advanced fuels performance code being developed at Idaho National Laboratory and is the code of choice for fuels performance by the U.S. Department of Energy (DOE)’s Consortium for Advanced Simulation of Light Water Reactors (CASL) Program. An approach to uncertainty quantification and sensitivity analysis with BISON was developed and a new toolkit was created. A PWR fuel rod model was developed and simulated by BISON, and uncertainty quantification and sensitivity analysis were performed with eighteen uncertain input parameters. The maximum fuel temperature and gap conductance were selected as the figures of merit (FOM). Pearson, Spearman, and partial correlation coefficients were considered for all of the figures of merit in sensitivity analysis. (author)

  19. Demonstration of Uncertainty Quantification and Sensitivity Analysis for PWR Fuel Performance with BISON

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Hongbin; Ladd, Jacob; Zhao, Haihua; Zou, Ling; Burns, Douglas

    2015-11-01

    BISON is an advanced fuels performance code being developed at Idaho National Laboratory and is the code of choice for fuels performance by the U.S. Department of Energy (DOE)’s Consortium for Advanced Simulation of Light Water Reactors (CASL) Program. An approach to uncertainty quantification and sensitivity analysis with BISON was developed and a new toolkit was created. A PWR fuel rod model was developed and simulated by BISON, and uncertainty quantification and sensitivity analysis were performed with eighteen uncertain input parameters. The maximum fuel temperature and gap conductance were selected as the figures of merit (FOM). Pearson, Spearman, and partial correlation coefficients were considered for all of the figures of merit in sensitivity analysis.

  20. Analysis of Hydrological Sensitivity for Flood Risk Assessment

    Directory of Open Access Journals (Sweden)

    Sanjay Kumar Sharma

    2018-02-01

    Full Text Available In order for the Indian government to maximize Integrated Water Resource Management (IWRM, the Brahmaputra River has played an important role in the undertaking of the Pilot Basin Study (PBS due to the Brahmaputra River’s annual regional flooding. The selected Kulsi River—a part of Brahmaputra sub-basin—experienced severe floods in 2007 and 2008. In this study, the Rainfall-Runoff-Inundation (RRI hydrological model was used to simulate the recent historical flood in order to understand and improve the integrated flood risk management plan. The ultimate objective was to evaluate the sensitivity of hydrologic simulation using different Digital Elevation Model (DEM resources, coupled with DEM smoothing techniques, with a particular focus on the comparison of river discharge and flood inundation extent. As a result, the sensitivity analysis showed that, among the input parameters, the RRI model is highly sensitive to Manning’s roughness coefficient values for flood plains, followed by the source of the DEM, and then soil depth. After optimizing its parameters, the simulated inundation extent showed that the smoothing filter was more influential than its simulated discharge at the outlet. Finally, the calibrated and validated RRI model simulations agreed well with the observed discharge and the Moderate Imaging Spectroradiometer (MODIS-detected flood extents.

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

    International Nuclear Information System (INIS)

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

    2015-09-01

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

  2. Sensitivity Analysis of Dynamic Tariff Method for Congestion Management in Distribution Networks

    DEFF Research Database (Denmark)

    Huang, Shaojun; Wu, Qiuwei; Liu, Zhaoxi

    2015-01-01

    The dynamic tariff (DT) method is designed for the distribution system operator (DSO) to alleviate the congestions that might occur in a distribution network with high penetration of distribute energy resources (DERs). Sensitivity analysis of the DT method is crucial because of its decentralized...... control manner. The sensitivity analysis can obtain the changes of the optimal energy planning and thereby the line loading profiles over the infinitely small changes of parameters by differentiating the KKT conditions of the convex quadratic programming, over which the DT method is formed. Three case...

  3. 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)

  4. Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

    Science.gov (United States)

    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.

  5. Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

    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.

  6. Manufacturing error sensitivity analysis and optimal design method of cable-network antenna structures

    Science.gov (United States)

    Zong, Yali; Hu, Naigang; Duan, Baoyan; Yang, Guigeng; Cao, Hongjun; Xu, Wanye

    2016-03-01

    Inevitable manufacturing errors and inconsistency between assumed and actual boundary conditions can affect the shape precision and cable tensions of a cable-network antenna, and even result in failure of the structure in service. In this paper, an analytical sensitivity analysis method of the shape precision and cable tensions with respect to the parameters carrying uncertainty was studied. Based on the sensitivity analysis, an optimal design procedure was proposed to alleviate the effects of the parameters that carry uncertainty. The validity of the calculated sensitivities is examined by those computed by a finite difference method. Comparison with a traditional design method shows that the presented design procedure can remarkably reduce the influence of the uncertainties on the antenna performance. Moreover, the results suggest that especially slender front net cables, thick tension ties, relatively slender boundary cables and high tension level can improve the ability of cable-network antenna structures to resist the effects of the uncertainties on the antenna performance.

  7. Procedures for uncertainty and sensitivity analysis in repository performance assessment

    International Nuclear Information System (INIS)

    Poern, K.; Aakerlund, O.

    1985-10-01

    The objective of the project was mainly a literature study of available methods for the treatment of parameter uncertainty propagation and sensitivity aspects in complete models such as those concerning geologic disposal of radioactive waste. The study, which has run parallel with the development of a code package (PROPER) for computer assisted analysis of function, also aims at the choice of accurate, cost-affective methods for uncertainty and sensitivity analysis. Such a choice depends on several factors like the number of input parameters, the capacity of the model and the computer reresources required to use the model. Two basic approaches are addressed in the report. In one of these the model of interest is directly simulated by an efficient sampling technique to generate an output distribution. Applying the other basic method the model is replaced by an approximating analytical response surface, which is then used in the sampling phase or in moment matching to generate the output distribution. Both approaches are illustrated by simple examples in the report. (author)

  8. Probabilistic Sensitivities for Fatigue Analysis of Turbine Engine Disks

    OpenAIRE

    Harry R. Millwater; R. Wesley Osborn

    2006-01-01

    A methodology is developed and applied that determines the sensitivities of the probability-of-fracture of a gas turbine disk fatigue analysis with respect to the parameters of the probability distributions describing the random variables. The disk material is subject to initial anomalies, in either low- or high-frequency quantities, such that commonly used materials (titanium, nickel, powder nickel) and common damage mechanisms (inherent defects or su...

  9. Significance of uncertainties derived from settling tank model structure and parameters on predicting WWTP performance - A global sensitivity analysis study

    DEFF Research Database (Denmark)

    Ramin, Elham; Sin, Gürkan; Mikkelsen, Peter Steen

    2011-01-01

    Uncertainty derived from one of the process models – such as one-dimensional secondary settling tank (SST) models – can impact the output of the other process models, e.g., biokinetic (ASM1), as well as the integrated wastewater treatment plant (WWTP) models. The model structure and parameter...... and from the last aerobic bioreactor upstream to the SST (Garrett/hydraulic method). For model structure uncertainty, two one-dimensional secondary settling tank (1-D SST) models are assessed, including a first-order model (the widely used Takács-model), in which the feasibility of using measured...... uncertainty of settler models can therefore propagate, and add to the uncertainties in prediction of any plant performance criteria. Here we present an assessment of the relative significance of secondary settling model performance in WWTP simulations. We perform a global sensitivity analysis (GSA) based...

  10. Sensitivity Analysis on Elbow Piping Components in Seismically Isolated NPP under Seismic Loading

    Energy Technology Data Exchange (ETDEWEB)

    Ju, Hee Kun; Hahm, Dae Gi; Kim, Min Kyu [KAERI, Daejeon (Korea, Republic of); Jeon, Bub Gyu; Kim, Nam Sik [Pusan National University, Busan (Korea, Republic of)

    2016-05-15

    In this study, the FE model is verified using specimen test results and simulation with parameter variations are conducted. Effective parameters will randomly sampled and used as input values for simulations to be applied to the fragility analysis. pipelines are representative of them because they could undergo larger displacements when they are supported on both isolated and non-isolated structures simultaneously. Especially elbows are critical components of pipes under severed loading conditions such as earthquake action because strain is accumulated on them during the repeated bending of the pipe. Therefore, seismic performance of pipe elbow components should be examined thoroughly based on the fragility analysis. Fragility assessment of interface pipe should take different sources of uncertainty into account. However, selection of important sources and repeated tests with many random input values are very time consuming and expensive, so numerical analysis is commonly used. In the present study, finite element (FE) model of elbow component will be validated using the dynamic test results of elbow components. Using the verified model, sensitivity analysis will be implemented as a preliminary process of seismic fragility of piping system. Several important input parameters are selected and how the uncertainty of them are apportioned to the uncertainty of the elbow response is to be studied. Piping elbows are critical components under cyclic loading conditions as they are subjected large displacement. In a seismically isolated NPP, seismic capacity of piping system should be evaluated with caution. Seismic fragility assessment preliminarily needs parameter sensitivity analysis about the output of interest with different input parameter values.

  11. Sensitivity Analysis of Core Neutronic Parameters in Electron Accelerator-driven Subcritical Advanced Liquid Metal Reactor

    Directory of Open Access Journals (Sweden)

    Marziye Ebrahimkhani

    2016-02-01

    Full Text Available Calculation of the core neutronic parameters is one of the key components in all nuclear reactors. In this research, the energy spectrum and spatial distribution of the neutron flux in a uranium target have been calculated. In addition, sensitivity of the core neutronic parameters in accelerator-driven subcritical advanced liquid metal reactors, such as electron beam energy (Ee and source multiplication coefficient (ks, has been investigated. A Monte Carlo code (MCNPX_2.6 has been used to calculate neutronic parameters such as effective multiplication coefficient (keff, net neutron multiplication (M, neutron yield (Yn/e, energy constant gain (G0, energy gain (G, importance of neutron source (φ∗, axial and radial distributions of neutron flux, and power peaking factor (Pmax/Pave in two axial and radial directions of the reactor core for four fuel loading patterns. According to the results, safety margin and accelerator current (Ie have been decreased in the highest case of ks, but G and φ∗ have increased by 88.9% and 21.6%, respectively. In addition, for LP1 loading pattern, with increasing Ee from 100 MeV up to 1 GeV, Yn/e and G improved by 91.09% and 10.21%, and Ie and Pacc decreased by 91.05% and 10.57%, respectively. The results indicate that placement of the Np–Pu assemblies on the periphery allows for a consistent keff because the Np–Pu assemblies experience less burn-up.

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  14. 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

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

    International Nuclear Information System (INIS)

    Clifton, P.M.

    1984-12-01

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

  16. Biosphere assessment for high-level radioactive waste disposal: modelling experiences and discussion on key parameters by sensitivity analysis in JNC

    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)

  17. Sensitivity of Austempering Heat Treatment of Ductile Irons to Changes in Process Parameters

    Science.gov (United States)

    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.

  18. Sensitivity of Austempering Heat Treatment of Ductile Irons to Changes in Process Parameters

    Science.gov (United States)

    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.

  19. A Sensitivity Analysis Approach to Identify Key Environmental Performance Factors

    Directory of Open Access Journals (Sweden)

    Xi Yu

    2014-01-01

    Full Text Available Life cycle assessment (LCA is widely used in design phase to reduce the product’s environmental impacts through the whole product life cycle (PLC during the last two decades. The traditional LCA is restricted to assessing the environmental impacts of a product and the results cannot reflect the effects of changes within the life cycle. In order to improve the quality of ecodesign, it is a growing need to develop an approach which can reflect the changes between the design parameters and product’s environmental impacts. A sensitivity analysis approach based on LCA and ecodesign is proposed in this paper. The key environmental performance factors which have significant influence on the products’ environmental impacts can be identified by analyzing the relationship between environmental impacts and the design parameters. Users without much environmental knowledge can use this approach to determine which design parameter should be first considered when (redesigning a product. A printed circuit board (PCB case study is conducted; eight design parameters are chosen to be analyzed by our approach. The result shows that the carbon dioxide emission during the PCB manufacture is highly sensitive to the area of PCB panel.

  20. Best estimate analysis of LOFT L2-5 with CATHARE: uncertainty and sensitivity analysis

    Energy Technology Data Exchange (ETDEWEB)

    JOUCLA, Jerome; PROBST, Pierre [Institute for Radiological Protection and Nuclear Safety, Fontenay-aux-Roses (France); FOUET, Fabrice [APTUS, Versailles (France)

    2008-07-01

    The revision of the 10 CFR50.46 in 1988 has made possible the use of best-estimate codes. They may be used in safety demonstration and licensing, provided that uncertainties are added to the relevant output parameters before comparing them with the acceptance criteria. In the safety analysis of the large break loss of coolant accident, it was agreed that the 95. percentile estimated with a high degree of confidence should be lower than the acceptance criteria. It appeared necessary to IRSN, technical support of the French Safety Authority, to get more insight into these strategies which are being developed not only in thermal-hydraulics but in other fields such as in neutronics. To estimate the 95. percentile with a high confidence level, we propose to use rank statistics or bootstrap. Toward the objective of assessing uncertainty, it is useful to determine and to classify the main input parameters. We suggest approximating the code by a surrogate model, the Kriging model, which will be used to make a sensitivity analysis with the SOBOL methodology. This paper presents the application of two new methodologies of how to make the uncertainty and sensitivity analysis on the maximum peak cladding temperature of the LOFT L2-5 test with the CATHARE code. (authors)

  1. Sensitivity analysis of recovery efficiency in high-temperature aquifer thermal energy storage with single well

    International Nuclear Information System (INIS)

    Jeon, Jun-Seo; Lee, Seung-Rae; Pasquinelli, Lisa; Fabricius, Ida Lykke

    2015-01-01

    High-temperature aquifer thermal energy storage system usually shows higher performance than other borehole thermal energy storage systems. Although there is a limitation in the widespread use of the HT-ATES system because of several technical problems such as clogging, corrosion, etc., it is getting more attention as these issues are gradually alleviated. In this study, a sensitivity analysis of recovery efficiency in two cases of HT-ATES system with a single well is conducted to select key parameters. For a fractional factorial design used to choose input parameters with uniformity, the optimal Latin hypercube sampling with an enhanced stochastic evolutionary algorithm is considered. Then, the recovery efficiency is obtained using a computer model developed by COMSOL Multiphysics. With input and output variables, the surrogate modeling technique, namely the Gaussian-Kriging method with Smoothly Clopped Absolute Deviation Penalty, is utilized. Finally, the sensitivity analysis is performed based on the variation decomposition. According to the result of sensitivity analysis, the most important input variables are selected and confirmed to consider the interaction effects for each case and it is confirmed that key parameters vary with the experiment domain of hydraulic and thermal properties as well as the number of input variables. - Highlights: • Main and interaction effects on recovery efficiency in HT-ATES was investigated. • Reliability depended on fractional factorial design and interaction effects. • Hydraulic permeability of aquifer had an important impact on recovery efficiency. • Site-specific sensitivity analysis of HT-ATES was recommended.

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  3. A sensitivity analysis of the WIPP disposal room model: Phase 1

    Energy Technology Data Exchange (ETDEWEB)

    Labreche, D.A.; Beikmann, M.A. [RE/SPEC, Inc., Albuquerque, NM (United States); Osnes, J.D. [RE/SPEC, Inc., Rapid City, SD (United States); Butcher, B.M. [Sandia National Labs., Albuquerque, NM (United States)

    1995-07-01

    The WIPP Disposal Room Model (DRM) is a numerical model with three major components constitutive models of TRU waste, crushed salt backfill, and intact halite -- and several secondary components, including air gap elements, slidelines, and assumptions on symmetry and geometry. A sensitivity analysis of the Disposal Room Model was initiated on two of the three major components (waste and backfill models) and on several secondary components as a group. The immediate goal of this component sensitivity analysis (Phase I) was to sort (rank) model parameters in terms of their relative importance to model response so that a Monte Carlo analysis on a reduced set of DRM parameters could be performed under Phase II. The goal of the Phase II analysis will be to develop a probabilistic definition of a disposal room porosity surface (porosity, gas volume, time) that could be used in WIPP Performance Assessment analyses. This report documents a literature survey which quantifies the relative importance of the secondary room components to room closure, a differential analysis of the creep consolidation model and definition of a follow-up Monte Carlo analysis of the model, and an analysis and refitting of the waste component data on which a volumetric plasticity model of TRU drum waste is based. A summary, evaluation of progress, and recommendations for future work conclude the report.

  4. Statistical MOSFET Parameter Extraction with Parameter Selection for Minimal Point Measurement

    Directory of Open Access Journals (Sweden)

    Marga Alisjahbana

    2013-11-01

    Full Text Available A method to statistically extract MOSFET model parameters from a minimal number of transistor I(V characteristic curve measurements, taken during fabrication process monitoring. It includes a sensitivity analysis of the model, test/measurement point selection, and a parameter extraction experiment on the process data. The actual extraction is based on a linear error model, the sensitivity of the MOSFET model with respect to the parameters, and Newton-Raphson iterations. Simulated results showed good accuracy of parameter extraction and I(V curve fit for parameter deviations of up 20% from nominal values, including for a process shift of 10% from nominal.

  5. 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...

  6. Sensitivity Analysis of a Riparian Vegetation Growth Model

    Directory of Open Access Journals (Sweden)

    Michael Nones

    2016-11-01

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

  7. Global sensitivity analysis using a Gaussian Radial Basis Function metamodel

    International Nuclear Information System (INIS)

    Wu, Zeping; Wang, Donghui; Okolo N, Patrick; Hu, Fan; Zhang, Weihua

    2016-01-01

    Sensitivity analysis plays an important role in exploring the actual impact of adjustable parameters on response variables. Amongst the wide range of documented studies on sensitivity measures and analysis, Sobol' indices have received greater portion of attention due to the fact that they can provide accurate information for most models. In this paper, a novel analytical expression to compute the Sobol' indices is derived by introducing a method which uses the Gaussian Radial Basis Function to build metamodels of computationally expensive computer codes. Performance of the proposed method is validated against various analytical functions and also a structural simulation scenario. Results demonstrate that the proposed method is an efficient approach, requiring a computational cost of one to two orders of magnitude less when compared to the traditional Quasi Monte Carlo-based evaluation of Sobol' indices. - Highlights: • RBF based sensitivity analysis method is proposed. • Sobol' decomposition of Gaussian RBF metamodel is obtained. • Sobol' indices of Gaussian RBF metamodel are derived based on the decomposition. • The efficiency of proposed method is validated by some numerical examples.

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

    International Nuclear Information System (INIS)

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

    1988-01-01

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

  9. MOESHA: A genetic algorithm for automatic calibration and estimation of parameter uncertainty and sensitivity of hydrologic models

    Science.gov (United States)

    Characterization of uncertainty and sensitivity of model parameters is an essential and often overlooked facet of hydrological modeling. This paper introduces an algorithm called MOESHA that combines input parameter sensitivity analyses with a genetic algorithm calibration routin...

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

    International Nuclear Information System (INIS)

    Li, W. B.; Hoeschen, C.

    2010-01-01

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

  11. [Simulation of carbon cycle in Qianyanzhou artificial masson pine forest ecosystem and sensitivity analysis of model parameters].

    Science.gov (United States)

    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

  12. Reduction and Uncertainty Analysis of Chemical Mechanisms Based on Local and Global Sensitivities

    Science.gov (United States)

    Esposito, Gaetano

    Numerical simulations of critical reacting flow phenomena in hypersonic propulsion devices require accurate representation of finite-rate chemical kinetics. The chemical kinetic models available for hydrocarbon fuel combustion are rather large, involving hundreds of species and thousands of reactions. As a consequence, they cannot be used in multi-dimensional computational fluid dynamic calculations in the foreseeable future due to the prohibitive computational cost. In addition to the computational difficulties, it is also known that some fundamental chemical kinetic parameters of detailed models have significant level of uncertainty due to limited experimental data available and to poor understanding of interactions among kinetic parameters. In the present investigation, local and global sensitivity analysis techniques are employed to develop a systematic approach of reducing and analyzing detailed chemical kinetic models. Unlike previous studies in which skeletal model reduction was based on the separate analysis of simple cases, in this work a novel strategy based on Principal Component Analysis of local sensitivity values is presented. This new approach is capable of simultaneously taking into account all the relevant canonical combustion configurations over different composition, temperature and pressure conditions. Moreover, the procedure developed in this work represents the first documented inclusion of non-premixed extinction phenomena, which is of great relevance in hypersonic combustors, in an automated reduction algorithm. The application of the skeletal reduction to a detailed kinetic model consisting of 111 species in 784 reactions is demonstrated. The resulting reduced skeletal model of 37--38 species showed that the global ignition/propagation/extinction phenomena of ethylene-air mixtures can be predicted within an accuracy of 2% of the full detailed model. The problems of both understanding non-linear interactions between kinetic parameters and

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

    International Nuclear Information System (INIS)

    Saltelli, Andrea; Sobol', Ilya M

    1995-01-01

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

  14. Data fusion qualitative sensitivity analysis

    International Nuclear Information System (INIS)

    Clayton, E.A.; Lewis, R.E.

    1995-09-01

    Pacific Northwest Laboratory was tasked with testing, debugging, and refining the Hanford Site data fusion workstation (DFW), with the assistance of Coleman Research Corporation (CRC), before delivering the DFW to the environmental restoration client at the Hanford Site. Data fusion is the mathematical combination (or fusion) of disparate data sets into a single interpretation. The data fusion software used in this study was developed by CRC. The data fusion software developed by CRC was initially demonstrated on a data set collected at the Hanford Site where three types of data were combined. These data were (1) seismic reflection, (2) seismic refraction, and (3) depth to geologic horizons. The fused results included a contour map of the top of a low-permeability horizon. This report discusses the results of a sensitivity analysis of data fusion software to variations in its input parameters. The data fusion software developed by CRC has a large number of input parameters that can be varied by the user and that influence the results of data fusion. Many of these parameters are defined as part of the earth model. The earth model is a series of 3-dimensional polynomials with horizontal spatial coordinates as the independent variables and either subsurface layer depth or values of various properties within these layers (e.g., compression wave velocity, resistivity) as the dependent variables

  15. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-12-08

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

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

    Science.gov (United States)

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

    2018-03-01

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

  17. Sensitivity Analysis for Steady State Groundwater Flow Using Adjoint Operators

    Science.gov (United States)

    Sykes, J. F.; Wilson, J. L.; Andrews, R. W.

    1985-03-01

    Adjoint sensitivity theory is currently being considered as a potential method for calculating the sensitivity of nuclear waste repository performance measures to the parameters of the system. For groundwater flow systems, performance measures of interest include piezometric heads in the vicinity of a waste site, velocities or travel time in aquifers, and mass discharge to biosphere points. The parameters include recharge-discharge rates, prescribed boundary heads or fluxes, formation thicknesses, and hydraulic conductivities. The derivative of a performance measure with respect to the system parameters is usually taken as a measure of sensitivity. To calculate sensitivities, adjoint sensitivity equations are formulated from the equations describing the primary problem. The solution of the primary problem and the adjoint sensitivity problem enables the determination of all of the required derivatives and hence related sensitivity coefficients. In this study, adjoint sensitivity theory is developed for equations of two-dimensional steady state flow in a confined aquifer. Both the primary flow equation and the adjoint sensitivity equation are solved using the Galerkin finite element method. The developed computer code is used to investigate the regional flow parameters of the Leadville Formation of the Paradox Basin in Utah. The results illustrate the sensitivity of calculated local heads to the boundary conditions. Alternatively, local velocity related performance measures are more sensitive to hydraulic conductivities.

  18. Computational Methods for Sensitivity and Uncertainty Analysis in Criticality Safety

    International Nuclear Information System (INIS)

    Broadhead, B.L.; Childs, R.L.; Rearden, B.T.

    1999-01-01

    Interest in the sensitivity methods that were developed and widely used in the 1970s (the FORSS methodology at ORNL among others) has increased recently as a result of potential use in the area of criticality safety data validation procedures to define computational bias, uncertainties and area(s) of applicability. Functional forms of the resulting sensitivity coefficients can be used as formal parameters in the determination of applicability of benchmark experiments to their corresponding industrial application areas. In order for these techniques to be generally useful to the criticality safety practitioner, the procedures governing their use had to be updated and simplified. This paper will describe the resulting sensitivity analysis tools that have been generated for potential use by the criticality safety community

  19. Synthesis, Characterization, and Sensitivity Analysis of Urea Nitrate (UN)

    Science.gov (United States)

    2015-04-01

    determined. From the results of the study, UN is safe to store under normal operating conditions. 15. SUBJECT TERMS urea, nitrate , sensitivity, thermal ...HNO3). Due to its simple composition, ease of manufacture, and higher detonation parameters than ammonium nitrate , it has become one of the...an H50 value of 10.054 ± 0.620 inches. 5. Conclusions From the results of the thermal analysis study, it can be concluded that urea nitrate is

  20. Parametric sensitivity analysis for stochastic molecular systems using information theoretic metrics

    Energy Technology Data Exchange (ETDEWEB)

    Tsourtis, Anastasios, E-mail: tsourtis@uoc.gr [Department of Mathematics and Applied Mathematics, University of Crete, Crete (Greece); Pantazis, Yannis, E-mail: pantazis@math.umass.edu; Katsoulakis, Markos A., E-mail: markos@math.umass.edu [Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003 (United States); Harmandaris, Vagelis, E-mail: harman@uoc.gr [Department of Mathematics and Applied Mathematics, University of Crete, and Institute of Applied and Computational Mathematics (IACM), Foundation for Research and Technology Hellas (FORTH), GR-70013 Heraklion, Crete (Greece)

    2015-07-07

    In this paper, we present a parametric sensitivity analysis (SA) methodology for continuous time and continuous space Markov processes represented by stochastic differential equations. Particularly, we focus on stochastic molecular dynamics as described by the Langevin equation. The utilized SA method is based on the computation of the information-theoretic (and thermodynamic) quantity of relative entropy rate (RER) and the associated Fisher information matrix (FIM) between path distributions, and it is an extension of the work proposed by Y. Pantazis and M. A. Katsoulakis [J. Chem. Phys. 138, 054115 (2013)]. A major advantage of the pathwise SA method is that both RER and pathwise FIM depend only on averages of the force field; therefore, they are tractable and computable as ergodic averages from a single run of the molecular dynamics simulation both in equilibrium and in non-equilibrium steady state regimes. We validate the performance of the extended SA method to two different molecular stochastic systems, a standard Lennard-Jones fluid and an all-atom methane liquid, and compare the obtained parameter sensitivities with parameter sensitivities on three popular and well-studied observable functions, namely, the radial distribution function, the mean squared displacement, and the pressure. Results show that the RER-based sensitivities are highly correlated with the observable-based sensitivities.

  1. 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

  2. Sensitivity and Uncertainty Analysis for Streamflow Prediction Using Different Objective Functions and Optimization Algorithms: San Joaquin California

    Science.gov (United States)

    Paul, M.; Negahban-Azar, M.

    2017-12-01

    The hydrologic models usually need to be calibrated against observed streamflow at the outlet of a particular drainage area through a careful model calibration. However, a large number of parameters are required to fit in the model due to their unavailability of the field measurement. Therefore, it is difficult to calibrate the model for a large number of potential uncertain model parameters. This even becomes more challenging if the model is for a large watershed with multiple land uses and various geophysical characteristics. Sensitivity analysis (SA) can be used as a tool to identify most sensitive model parameters which affect the calibrated model performance. There are many different calibration and uncertainty analysis algorithms which can be performed with different objective functions. By incorporating sensitive parameters in streamflow simulation, effects of the suitable algorithm in improving model performance can be demonstrated by the Soil and Water Assessment Tool (SWAT) modeling. In this study, the SWAT was applied in the San Joaquin Watershed in California covering 19704 km2 to calibrate the daily streamflow. Recently, sever water stress escalating due to intensified climate variability, prolonged drought and depleting groundwater for agricultural irrigation in this watershed. Therefore it is important to perform a proper uncertainty analysis given the uncertainties inherent in hydrologic modeling to predict the spatial and temporal variation of the hydrologic process to evaluate the impacts of different hydrologic variables. The purpose of this study was to evaluate the sensitivity and uncertainty of the calibrated parameters for predicting streamflow. To evaluate the sensitivity of the calibrated parameters three different optimization algorithms (Sequential Uncertainty Fitting- SUFI-2, Generalized Likelihood Uncertainty Estimation- GLUE and Parameter Solution- ParaSol) were used with four different objective functions (coefficient of determination

  3. Sensitivity analysis of coupled processes and parameters on the performance of enhanced geothermal systems.

    Science.gov (United States)

    Pandey, S N; Vishal, Vikram

    2017-12-06

    3-D modeling of coupled thermo-hydro-mechanical (THM) processes in enhanced geothermal systems using the control volume finite element code was done. In a first, a comparative analysis on the effects of coupled processes, operational parameters and reservoir parameters on heat extraction was conducted. We found that significant temperature drop and fluid overpressure occurred inside the reservoirs/fracture that affected the transport behavior of the fracture. The spatio-temporal variations of fracture aperture greatly impacted the thermal drawdown and consequently the net energy output. The results showed that maximum aperture evolution occurred near the injection zone instead of the production zone. Opening of the fracture reduced the injection pressure required to circulate a fixed mass of water. The thermal breakthrough and heat extraction strongly depend on the injection mass flow rate, well distances, reservoir permeability and geothermal gradients. High permeability caused higher water loss, leading to reduced heat extraction. From the results of TH vs THM process simulations, we conclude that appropriate coupling is vital and can impact the estimates of net heat extraction. This study can help in identifying the critical operational parameters, and process optimization for enhanced energy extraction from a geothermal system.

  4. A global sensitivity analysis of crop virtual water content

    Science.gov (United States)

    Tamea, S.; Tuninetti, M.; D'Odorico, P.; Laio, F.; Ridolfi, L.

    2015-12-01

    The concepts of virtual water and water footprint are becoming widely used in the scientific literature and they are proving their usefulness in a number of multidisciplinary contexts. With such growing interest a measure of data reliability (and uncertainty) is becoming pressing but, as of today, assessments of data sensitivity to model parameters, performed at the global scale, are not known. This contribution aims at filling this gap. Starting point of this study is the evaluation of the green and blue virtual water content (VWC) of four staple crops (i.e. wheat, rice, maize, and soybean) at a global high resolution scale. In each grid cell, the crop VWC is given by the ratio between the total crop evapotranspiration over the growing season and the crop actual yield, where evapotranspiration is determined with a detailed daily soil water balance and actual yield is estimated using country-based data, adjusted to account for spatial variability. The model provides estimates of the VWC at a 5x5 arc minutes and it improves on previous works by using the newest available data and including multi-cropping practices in the evaluation. The model is then used as the basis for a sensitivity analysis, in order to evaluate the role of model parameters in affecting the VWC and to understand how uncertainties in input data propagate and impact the VWC accounting. In each cell, small changes are exerted to one parameter at a time, and a sensitivity index is determined as the ratio between the relative change of VWC and the relative change of the input parameter with respect to its reference value. At the global scale, VWC is found to be most sensitive to the planting date, with a positive (direct) or negative (inverse) sensitivity index depending on the typical season of crop planting date. VWC is also markedly dependent on the length of the growing period, with an increase in length always producing an increase of VWC, but with higher spatial variability for rice than for

  5. Sensitivity Analysis of the Scattering-Based SARBM3D Despeckling Algorithm.

    Science.gov (United States)

    Di Simone, Alessio

    2016-06-25

    Synthetic Aperture Radar (SAR) imagery greatly suffers from multiplicative speckle noise, typical of coherent image acquisition sensors, such as SAR systems. Therefore, a proper and accurate despeckling preprocessing step is almost mandatory to aid the interpretation and processing of SAR data by human users and computer algorithms, respectively. Very recently, a scattering-oriented version of the popular SAR Block-Matching 3D (SARBM3D) despeckling filter, named Scattering-Based (SB)-SARBM3D, was proposed. The new filter is based on the a priori knowledge of the local topography of the scene. In this paper, an experimental sensitivity analysis of the above-mentioned despeckling algorithm is carried out, and the main results are shown and discussed. In particular, the role of both electromagnetic and geometrical parameters of the surface and the impact of its scattering behavior are investigated. Furthermore, a comprehensive sensitivity analysis of the SB-SARBM3D filter against the Digital Elevation Model (DEM) resolution and the SAR image-DEM coregistration step is also provided. The sensitivity analysis shows a significant robustness of the algorithm against most of the surface parameters, while the DEM resolution plays a key role in the despeckling process. Furthermore, the SB-SARBM3D algorithm outperforms the original SARBM3D in the presence of the most realistic scattering behaviors of the surface. An actual scenario is also presented to assess the DEM role in real-life conditions.

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

    International Nuclear Information System (INIS)

    Cormenzana, J. L.

    2013-08-01

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

  7. Relative sensitivity analysis of the predictive properties of sloppy models.

    Science.gov (United States)

    Myasnikova, Ekaterina; Spirov, Alexander

    2018-01-25

    Commonly among the model parameters characterizing complex biological systems are those that do not significantly influence the quality of the fit to experimental data, so-called "sloppy" parameters. The sloppiness can be mathematically expressed through saturating response functions (Hill's, sigmoid) thereby embodying biological mechanisms responsible for the system robustness to external perturbations. However, if a sloppy model is used for the prediction of the system behavior at the altered input (e.g. knock out mutations, natural expression variability), it may demonstrate the poor predictive power due to the ambiguity in the parameter estimates. We introduce a method of the predictive power evaluation under the parameter estimation uncertainty, Relative Sensitivity Analysis. The prediction problem is addressed in the context of gene circuit models describing the dynamics of segmentation gene expression in Drosophila embryo. Gene regulation in these models is introduced by a saturating sigmoid function of the concentrations of the regulatory gene products. We show how our approach can be applied to characterize the essential difference between the sensitivity properties of robust and non-robust solutions and select among the existing solutions those providing the correct system behavior at any reasonable input. In general, the method allows to uncover the sources of incorrect predictions and proposes the way to overcome the estimation uncertainties.

  8. Sensitivity of Hurst parameter estimation to periodic signals in time series and filtering approaches

    Science.gov (United States)

    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.

  9. Sensitivity Analysis of Multi-objective Optimization for Solid Waste Management: A Case Study of Dar es Salaam, Tanzania

    Directory of Open Access Journals (Sweden)

    Halidi Lyeme

    2017-11-01

    Full Text Available In this study, a sensitivity analysis of a multi-objective optimization model for solid waste management (SWM for Dar es Salaam city in Tanzania is considered. Our objectives were to identify the most sensitive parameters and effect of other input data to the model output. Five scenarios were considered by varying their associated parameter values. The results showed that the decrease of total cost for the SWM system in all scenarios was observed compared to the baseline solution when the single landfill was considered. Furthermore, the analysis shows that the variable cost parameter for the processing facilities is very sensitivity in such a way that if you increase the variable cost then, there is a rapid increase of total cost for the SWM system and the vice versa is true. The relevant suggestions to the decision makers were also discussed.

  10. Sensitivity analysis of a radionuclide transfer model describing contaminated vegetation in Fukushima prefecture, using Morris and Sobol' - Application of sensitivity analysis on a radionuclides transfer model in the environment describing weeds contamination in Fukushima Prefecture, using Morris method and Sobol' indices indices

    Energy Technology Data Exchange (ETDEWEB)

    Nicoulaud-Gouin, V.; Metivier, J.M.; Gonze, M.A. [Institut de Radioprotection et de Surete Nucleaire-PRP-ENV/SERIS/LM2E (France); Garcia-Sanchez, L. [Institut de Radioprotection et de Surete Nucleaire-PRPENV/SERIS/L2BT (France)

    2014-07-01

    The increasing spatial and temporal complexity of models demands methods capable of ranking the influence of their large numbers of parameters. This question specifically arises in assessment studies on the consequences of the Fukushima accident. Sensitivity analysis aims at measuring the influence of input variability on the output response. Generally, two main approaches are distinguished (Saltelli, 2001, Iooss, 2011): - Screening approach, less expensive in computation time and allowing to identify non influential parameters; - Measures of importance, introducing finer quantitative indices. In this category, there are regression-based methods, assuming a linear or monotonic response (Pearson coefficient, Spearman coefficient), and variance-based methods, without assumptions on the model but requiring an increasingly prohibitive number of evaluations when the number of parameters increases. These approaches are available in various statistical programs (notably R) but are still poorly integrated in modelling platforms of radioecological risk assessment. This work aimed at illustrating the benefits of sensitivity analysis in the course of radioecological risk assessments This study used two complementary state-of-art global sensitivity analysis methods: - The screening method of Morris (Morris, 1991; Campolongo et al., 2007) based on limited model evaluations with a one-at-a-time (OAT) design; - The variance-based Sobol' sensitivity analysis (Saltelli, 2002) based a large number of model evaluations in the parameter space with a quasi-random sampling (Owen, 2003). Sensitivity analyses were applied on a dynamic Soil-Plant Deposition Model (Gonze et al., submitted to this conference) predicting foliar concentration in weeds after atmospheric radionuclide fallout. The Soil-Plant Deposition Model considers two foliage pools and a root pool, and describes foliar biomass growth with a Verhulst model. The developed semi-analytic formulation of foliar concentration

  11. Sensitivity analysis for heat diffusion in a fin on a nuclear fuel element

    International Nuclear Information System (INIS)

    Tito, Max Werner de Carvalho

    2001-11-01

    The modern thermal systems generally present a growing complexity, as is in the case of nuclear power plants. It seems that is necessary the use of complex computation and mathematical tools in order to increase the efficiency of the operations, reduce costs and maximize profits while maintaining the integrity of its components. The use of sensitivity calculations plays an important role in this process providing relevant information regarding the resultant influence of variation or perturbation of its parameters as the system works. This technique is better known as sensitivity analysis and through its use makes possible the understanding of the effects of the parameters, which are fundamental for the project preparation, and for the development of preventive and corrective handling measurements of many pieces of equipment of modern engineering. The sensitivity calculation methodology is based generally on the response surface technique (graphic description of the functions of interest based in the results obtained from the system parameter variation). This method presents a lot of disadvantages and sometimes is even impracticable since many parameters can cause alterations or perturbations to the system and the model to analyse it can be very complex as well. The utilization of perturbative methods result appropriate as a practical solution to this problem especially in the presence of complex equations. Also it reduces the resultant computational calculus time considerably. The use of these methods becomes an essential tool to simplify the sensitivity analysis. In this dissertation, the differential perturbative method is applied in a heat conduction problem within a thermal system, made up of a one-dimensional circumferential fin on a nuclear fuel element. The fins are used to extend the thermal surfaces where convection occurs; thus increasing the heat transfer to many thermal pieces of equipment in order to obtain better results. The finned claddings are

  12. Adaptation of an urban land surface model to a tropical suburban area: Offline evaluation, sensitivity analysis, and optimization of TEB/ISBA (SURFEX)

    Science.gov (United States)

    Harshan, Suraj

    The main objective of the present thesis is the improvement of the TEB/ISBA (SURFEX) urban land surface model (ULSM) through comprehensive evaluation, sensitivity analysis, and optimization experiments using energy balance and radiative and air temperature data observed during 11 months at a tropical sub-urban site in Singapore. Overall the performance of the model is satisfactory, with a small underestimation of net radiation and an overestimation of sensible heat flux. Weaknesses in predicting the latent heat flux are apparent with smaller model values during daytime and the model also significantly underpredicts both the daytime peak and nighttime storage heat. Surface temperatures of all facets are generally overpredicted. Significant variation exists in the model behaviour between dry and wet seasons. The vegetation parametrization used in the model is inadequate to represent the moisture dynamics, producing unrealistically low latent heat fluxes during a particularly dry period. The comprehensive evaluation of the USLM shows the need for accurate estimation of input parameter values for present site. Since obtaining many of these parameters through empirical methods is not feasible, the present study employed a two step approach aimed at providing information about the most sensitive parameters and an optimized parameter set from model calibration. Two well established sensitivity analysis methods (global: Sobol and local: Morris) and a state-of-the-art multiobjective evolutionary algorithm (Borg) were employed for sensitivity analysis and parameter estimation. Experiments were carried out for three different weather periods. The analysis indicates that roof related parameters are the most important ones in controlling the behaviour of the sensible heat flux and net radiation flux, with roof and road albedo as the most influential parameters. Soil moisture initialization parameters are important in controlling the latent heat flux. The built (town) fraction

  13. Ultra-Weak Fiber Bragg Grating Sensing Network Coated with Sensitive Material for Multi-Parameter Measurements

    Directory of Open Access Journals (Sweden)

    Wei Bai

    2017-06-01

    Full Text Available A multi-parameter measurement system based on ultra-weak fiber Bragg grating (UFBG array with sensitive material was proposed and experimentally demonstrated. The UFBG array interrogation principle is time division multiplex technology with two semiconductor optical amplifiers as timing units. Experimental results showed that the performance of the proposed UFBG system is almost equal to that of traditional FBG, while the UFBG array system has obvious superiority with potential multiplexing ability for multi-point and multi-parameter measurement. The system experimented on a 144 UFBG array with the reflectivity of UFBG ~0.04% for the four target parameters: hydrogen, humidity, temperature and salinity. Moreover, a uniform solution was customized to divide the cross-sensitivity between temperature and other target parameters. It is expected that this scheme will be capable of handling thousands of multi-parameter sensors in a single fiber.

  14. Ultra-Weak Fiber Bragg Grating Sensing Network Coated with Sensitive Material for Multi-Parameter Measurements.

    Science.gov (United States)

    Bai, Wei; Yang, Minghong; Hu, Chenyuan; Dai, Jixiang; Zhong, Xuexiang; Huang, Shuai; Wang, Gaopeng

    2017-06-26

    A multi-parameter measurement system based on ultra-weak fiber Bragg grating (UFBG) array with sensitive material was proposed and experimentally demonstrated. The UFBG array interrogation principle is time division multiplex technology with two semiconductor optical amplifiers as timing units. Experimental results showed that the performance of the proposed UFBG system is almost equal to that of traditional FBG, while the UFBG array system has obvious superiority with potential multiplexing ability for multi-point and multi-parameter measurement. The system experimented on a 144 UFBG array with the reflectivity of UFBG ~0.04% for the four target parameters: hydrogen, humidity, temperature and salinity. Moreover, a uniform solution was customized to divide the cross-sensitivity between temperature and other target parameters. It is expected that this scheme will be capable of handling thousands of multi-parameter sensors in a single fiber.

  15. Effect of parameters in moving average method for event detection enhancement using phase sensitive OTDR

    Science.gov (United States)

    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.

  16. Coupled code analysis of uncertainty and sensitivity of Kalinin-3 benchmark

    Energy Technology Data Exchange (ETDEWEB)

    Pasichnyk, Ihor; Zwermann, Winfried; Velkov, Kiril [Gesellschaft fuer Anlagen- und Reaktorsicherheit (GRS) gGmbH, Garching (Germany); Nikonov, Sergey [VNIIAES, Moscow (Russian Federation)

    2016-09-15

    An uncertainty and sensitivity analysis is performed for the OECD/NEA coolant transient Benchmark (K-3) on measured data at Kalinin-3 Nuclear Power Plant (NPP). A switch off of one main coolant pump (MCP) at nominal reactor power is calculated using a coupled thermohydraulic and neutron-kinetic ATHLET-PARCS code. The objectives are to study uncertainty of total reactor power and to identify the main sources of reactor power uncertainty. The GRS uncertainty and sensitivity software package XSUSA is applied to propagate uncertainties in nuclear data libraries to the full core coupled transient calculations. A set of most important thermal-hydraulic parameters of the primary circuit is identified and a total of 23 thermohydraulic parameters are statistically varied using GRS code SUSA. The ATHLET model contains also a balance-of-plant (BOP) model which is simulated using ATHLET GCSM module. In particular the operation of the main steam generator regulators is modelled in detail. A set of 200 varied coupled ATHLET-PARCS calculations is analyzed. The results obtained show a clustering effect in the behavior of global reactor parameters. It is found that the GCSM system together with varied input parameters strongly influence the overall nuclear power plant behavior and can even lead to a new scenario. Possible reasons of the clustering effect are discussed in the paper. This work is a step forward in establishing a ''best-estimate calculations in combination with performing uncertainty analysis'' methodology for coupled full core calculations.

  17. Subset simulation for structural reliability sensitivity analysis

    International Nuclear Information System (INIS)

    Song Shufang; Lu Zhenzhou; Qiao Hongwei

    2009-01-01

    Based on two procedures for efficiently generating conditional samples, i.e. Markov chain Monte Carlo (MCMC) simulation and importance sampling (IS), two reliability sensitivity (RS) algorithms are presented. On the basis of reliability analysis of Subset simulation (Subsim), the RS of the failure probability with respect to the distribution parameter of the basic variable is transformed as a set of RS of conditional failure probabilities with respect to the distribution parameter of the basic variable. By use of the conditional samples generated by MCMC simulation and IS, procedures are established to estimate the RS of the conditional failure probabilities. The formulae of the RS estimator, its variance and its coefficient of variation are derived in detail. The results of the illustrations show high efficiency and high precision of the presented algorithms, and it is suitable for highly nonlinear limit state equation and structural system with single and multiple failure modes

  18. Sensitivity analysis of the kinetic behaviour of a Gas Cooled Fast Reactor to variations of the delayed neutron parameters

    International Nuclear Information System (INIS)

    Van Rooijen, W. F. G.; Lathouwers, D.

    2007-01-01

    In advanced Generation IV (fast) reactors an integral fuel cycle is envisaged, where all Heavy Metal is recycled in the reactor. This leads to a nuclear fuel with a considerable content of Minor Actinides. For many of these isotopes the nuclear data is not very well known. In this paper the sensitivity of the kinetic behaviour of the reactor to the dynamic parameters λ k , β k and the delayed spectrum χ d,k is studied using first order perturbation theory. In the current study, feedback due to Doppler and/or thermohydraulic effects are not treated. The theoretical framework is applied to a Generation IV Gas Cooled Fast Reactor. The results indicate that the first-order approach is satisfactory for small variations of the data. Sensitivities to delayed neutron data are similar for increasing and decreasing transients. Sensitivities generally increase with reactivity for increasing transients. For decreasing transients, there are less clearly defined trends, although the sensitivity to the delayed neutron spectrum decreases with larger sub-criticality, as expected. For this research, an adjoint capable version of the time-dependent diffusion code DALTON is under development. (authors)

  19. Transient analysis of intercalation electrodes for parameter estimation

    Science.gov (United States)

    Devan, Sheba

    An essential part of integrating batteries as power sources in any application, be it a large scale automotive application or a small scale portable application, is an efficient Battery Management System (BMS). The combination of a battery with the microprocessor based BMS (called "smart battery") helps prolong the life of the battery by operating in the optimal regime and provides accurate information regarding the battery to the end user. The main purposes of BMS are cell protection, monitoring and control, and communication between different components. These purposes are fulfilled by tracking the change in the parameters of the intercalation electrodes in the batteries. Consequently, the functions of the BMS should be prompt, which requires the methodology of extracting the parameters to be efficient in time. The traditional transient techniques applied so far may not be suitable due to reasons such as the inability to apply these techniques when the battery is under operation, long experimental time, etc. The primary aim of this research work is to design a fast, accurate and reliable technique that can be used to extract parameter values of the intercalation electrodes. A methodology based on analysis of the short time response to a sinusoidal input perturbation, in the time domain is demonstrated using a porous electrode model for an intercalation electrode. It is shown that the parameters associated with the interfacial processes occurring in the electrode can be determined rapidly, within a few milliseconds, by measuring the response in the transient region. The short time analysis in the time domain is then extended to a single particle model that involves bulk diffusion in the solid phase in addition to interfacial processes. A systematic procedure for sequential parameter estimation using sensitivity analysis is described. Further, the short time response and the input perturbation are transformed into the frequency domain using Fast Fourier Transform

  20. Stability, performance and sensitivity analysis of I.I.D. jump linear systems

    Science.gov (United States)

    Chávez Fuentes, Jorge R.; González, Oscar R.; Gray, W. Steven

    2018-06-01

    This paper presents a symmetric Kronecker product analysis of independent and identically distributed jump linear systems to develop new, lower dimensional equations for the stability and performance analysis of this type of systems than what is currently available. In addition, new closed form expressions characterising multi-parameter relative sensitivity functions for performance metrics are introduced. The analysis technique is illustrated with a distributed fault-tolerant flight control example where the communication links are allowed to fail randomly.

  1. A cross-section sensitivity and uncertainty analysis on fusion reactor blankets with SAD/SED effect

    International Nuclear Information System (INIS)

    Furuta, Kazuo; Oka, Yoshiaki; Kondo, Shunsuke

    1986-01-01

    A cross-section sensitivity and uncertainty analysis on four types of fusion reactor blankets has been performed, based on cross-section covariance matrices. The design parameters investigated in the analysis include the tritium breeding ratio, the neutron heating and the fast neutron leakage flux from the inboard shield. Uncertainities in Secondary Angular Distribution (SAD) and Secondary Energy Distribution (SED) of scattered neutrons have been considered for lithium. The collective standard deviation, due to uncertainties in the evaluated cross-section data presently available, is 2-4% in the tritium breeding ratio, 2-3% in the neutron heating, and 10-20% in the fast neutron leakage flux. Contributions from SAD/SED uncertainties are significant for some parameters, such as those investigated in the present study. SAD/SED uncertainties should be considered in the sensitivity and uncertainty analysis on nuclear design of fusion reactors. (orig.)

  2. 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.

  3. Automated sensitivity analysis of the radionuclide migration code UCBNE10.2

    International Nuclear Information System (INIS)

    Pin, F.G.; Worley, B.A.; Oblow, E.M.; Wright, R.Q.; Harper, W.V.

    1985-01-01

    The Salt Repository Project (SRP) of the US Department of Energy is performing ongoing performance assessment analyses for the eventual licensing of an underground high-level nuclear waste repository in salt. As part of these studies, sensitivity and uncertainty analysis play a major role in the identification of important parameters, and in the identification of specific data needs for site characterization. Oak Ridge National Laboratory has supported the SRP in this effort resulting in the development of an automated procedure for performing large-scale sensitivity analysis using computer calculus. GRESS, Gradient Enhanced Software System, is a pre-compiler that can process FORTRAN computer codes and add derivative taking capabilities to the normal calculated results. The GRESS code is described and applied to the code UCB-NE-10.2 which simulates the migration through an adsorptive medium of the radionuclide members of a decay chain. Conclusions are drawn relative to the applicability of GRESS for more general large-scale modeling sensitivity studies, and the role of such techniques in the overall SRP sensitivity/uncertainty program is detailed. 6 refs., 2 figs., 3 tabs

  4. Global Sensitivity Analysis of High Speed Shaft Subsystem of a Wind Turbine Drive Train

    Directory of Open Access Journals (Sweden)

    Saeed Asadi

    2018-01-01

    Full Text Available The wind turbine dynamics are complex and critical area of study for the wind industry. Quantification of the effective factors to wind turbine performance is valuable for making improvements to both power performance and turbine health. In this paper, the global sensitivity analysis of validated mathematical model for high speed shaft drive train test rig has been developed in order to evaluate the contribution of systems input parameters to the specified objective functions. The drive train in this study consists of a 3-phase induction motor, flexible shafts, shafts’ coupling, bearing housing, and disk with an eccentric mass. The governing equations were derived by using the Lagrangian formalism and were solved numerically by Newmark method. The variance based global sensitivity indices are introduced to evaluate the contribution of input structural parameters correlated to the objective functions. The conclusion from the current research provides informative beneficial data in terms of design and optimization of a drive train setup and also can provide better understanding of wind turbine drive train system dynamics with respect to different structural parameters, ultimately designing more efficient drive trains. Finally, the proposed global sensitivity analysis (GSA methodology demonstrates the detectability of faults in different components.

  5. Assessing uncertainty and sensitivity of model parameterizations and parameters in WRF affecting simulated surface fluxes and land-atmosphere coupling over the Amazon region

    Science.gov (United States)

    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

  6. Sensitivity analysis on retardation effect of natural barriers against radionuclide transport

    International Nuclear Information System (INIS)

    Hatanaka, K.

    1994-01-01

    The generic performance assessment of the geological disposal system for high level waste (HLW) in Japan has been carried out by the Power Reactor and Nuclear Fuel Development Corporation (PNC) in accordance with the overall HLW management program defined by the Atomic Energy Commission of Japan. The Japanese concept of the geological disposal system is based on a multi-barrier system which is composed of vitrified waste, carbon steel overpack, thick bentonite buffer and a variety of realistic geological conditions. The main objectives of the study are the detailed analysis of the performance of engineered barrier system (EBS) and the analysis of the performance of natural barrier system (NBS) and the evaluation of its compliance with the required overall system performance. Sensitivity analysis was carried out for the objectives to investigate the way and extent of the retardation in the release to biosphere by the effect of NBS, and to clarify the conditions which is sufficient to ensure that the overall system meets safety requirement. The radionuclide transport model in geological media, the sensitivity analysis, and the calculated results of the retardation effect of NBS in terms of the sensitivity parameters are reported. (K.I.)

  7. Sensitivity Analysis for Hydraulic Behavior of Shiraz Plain Aquifer Using PMWIN

    Directory of Open Access Journals (Sweden)

    Ahmad Reza karimipour

    2011-07-01

    Full Text Available In this study, hydraulic behavior of Shirazplain aquifer, with an area of ~300 km2, was simulated using PMWIN model. The performance of recently constructed drainage system in the plain was modeled and parameters affecting hydraulic behavior of the aquifer were analyzed. Measured rainfall and evaporation rates in the plain, recharge and discharge rates through the aqueducts, Khoshk and Chenar Rahdar rivers, as well as amount of water discharged from production wells and recharge due to returned wastewater were considered in the model. Plain hydrodynamic coefficients were estimated via calibration and sensitivity analysis of the model was performed for four important parameters. Results showed that the model is most sensitive to recharge rate and hydraulic conductivity, respectively, such that a small variation in these two parameters causes a dramatic change in hydraulic head distribution in the plain. Furthermore, specific yield coefficient influences the seasonal water level fluctuations, but the aqueducts conductance coefficient only affects the aqueduct radius of influence with little effect on the overall hydraulic behavior of the plain.

  8. A hybrid approach for global sensitivity analysis

    International Nuclear Information System (INIS)

    Chakraborty, Souvik; Chowdhury, Rajib

    2017-01-01

    Distribution based sensitivity analysis (DSA) computes sensitivity of the input random variables with respect to the change in distribution of output response. Although DSA is widely appreciated as the best tool for sensitivity analysis, the computational issue associated with this method prohibits its use for complex structures involving costly finite element analysis. For addressing this issue, this paper presents a method that couples polynomial correlated function expansion (PCFE) with DSA. PCFE is a fully equivalent operational model which integrates the concepts of analysis of variance decomposition, extended bases and homotopy algorithm. By integrating PCFE into DSA, it is possible to considerably alleviate the computational burden. Three examples are presented to demonstrate the performance of the proposed approach for sensitivity analysis. For all the problems, proposed approach yields excellent results with significantly reduced computational effort. The results obtained, to some extent, indicate that proposed approach can be utilized for sensitivity analysis of large scale structures. - Highlights: • A hybrid approach for global sensitivity analysis is proposed. • Proposed approach integrates PCFE within distribution based sensitivity analysis. • Proposed approach is highly efficient.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-11-01

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

  10. Maternal sensitivity: a concept analysis.

    Science.gov (United States)

    Shin, Hyunjeong; Park, Young-Joo; Ryu, Hosihn; Seomun, Gyeong-Ae

    2008-11-01

    The aim of this paper is to report a concept analysis of maternal sensitivity. Maternal sensitivity is a broad concept encompassing a variety of interrelated affective and behavioural caregiving attributes. It is used interchangeably with the terms maternal responsiveness or maternal competency, with no consistency of use. There is a need to clarify the concept of maternal sensitivity for research and practice. A search was performed on the CINAHL and Ovid MEDLINE databases using 'maternal sensitivity', 'maternal responsiveness' and 'sensitive mothering' as key words. The searches yielded 54 records for the years 1981-2007. Rodgers' method of evolutionary concept analysis was used to analyse the material. Four critical attributes of maternal sensitivity were identified: (a) dynamic process involving maternal abilities; (b) reciprocal give-and-take with the infant; (c) contingency on the infant's behaviour and (d) quality of maternal behaviours. Maternal identity and infant's needs and cues are antecedents for these attributes. The consequences are infant's comfort, mother-infant attachment and infant development. In addition, three positive affecting factors (social support, maternal-foetal attachment and high self-esteem) and three negative affecting factors (maternal depression, maternal stress and maternal anxiety) were identified. A clear understanding of the concept of maternal sensitivity could be useful for developing ways to enhance maternal sensitivity and to maximize the developmental potential of infants. Knowledge of the attributes of maternal sensitivity identified in this concept analysis may be helpful for constructing measuring items or dimensions.

  11. Sensitivity analysis on the zirconium ignition in a postulated SFP loss of coolant accident

    International Nuclear Information System (INIS)

    Park, Sanggil; Lee, Jaeyoung; Kim, Sun-ki; Chun, Tae-hyun; Bang, Je-geon

    2016-01-01

    From both SFP complete LOCA experiments, it was observed that zirconium alloy cladding temperature was abruptly increased at a certain point and the cladding was almost fully oxidized. To capture this phenomenon, the concept of air oxidation breakaway model was adopted in MELCOR code. This paper examines this air oxidation breakaway model by comparing the SFP project test data and MELCOR code calculation results by using this model. The air oxidation model parameters are slightly altered to see their sensitivities on the occurrence of the zirconium ignition. Through such sensitivity analysis, limitations of the air oxidation breakaway model are revealed in comparison to the actual zirconium ignition phenomenon during air ingress scenarios. In addition, ways to overcome the identified limitations of the air oxidation model are recommended to estimate better the zirconium ignition phenomenon in SFP sequences. In this paper, the zirconium ignition phenomenon was reviewed and the model to capture this phenomenon was investigated. The model is the air oxidation breakaway model in MELCOR code, and its sensitivity of the model parameters on the time to ignition was studied. From the sensitivity analysis, the slight change of model parameters induce the large variation of the time to ignition. The model itself includes its weakness to fully represent both the air oxidation breakaway phenomenon and the followed zirconium ignition behavior. Furthermore, this model considers no effect of N2 on the cladding degradation and its promoted exothermic heat release

  12. Sensitivity analysis on the zirconium ignition in a postulated SFP loss of coolant accident

    Energy Technology Data Exchange (ETDEWEB)

    Park, Sanggil; Lee, Jaeyoung [Handong Global Univ., Pohang (Korea, Republic of); Kim, Sun-ki; Chun, Tae-hyun; Bang, Je-geon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    From both SFP complete LOCA experiments, it was observed that zirconium alloy cladding temperature was abruptly increased at a certain point and the cladding was almost fully oxidized. To capture this phenomenon, the concept of air oxidation breakaway model was adopted in MELCOR code. This paper examines this air oxidation breakaway model by comparing the SFP project test data and MELCOR code calculation results by using this model. The air oxidation model parameters are slightly altered to see their sensitivities on the occurrence of the zirconium ignition. Through such sensitivity analysis, limitations of the air oxidation breakaway model are revealed in comparison to the actual zirconium ignition phenomenon during air ingress scenarios. In addition, ways to overcome the identified limitations of the air oxidation model are recommended to estimate better the zirconium ignition phenomenon in SFP sequences. In this paper, the zirconium ignition phenomenon was reviewed and the model to capture this phenomenon was investigated. The model is the air oxidation breakaway model in MELCOR code, and its sensitivity of the model parameters on the time to ignition was studied. From the sensitivity analysis, the slight change of model parameters induce the large variation of the time to ignition. The model itself includes its weakness to fully represent both the air oxidation breakaway phenomenon and the followed zirconium ignition behavior. Furthermore, this model considers no effect of N2 on the cladding degradation and its promoted exothermic heat release.

  13. Technique for sensitivity analysis of space- and energy-dependent burn-up calculations

    International Nuclear Information System (INIS)

    Williams, M.L.; White, J.R.

    1979-01-01

    A practical method is presented for sensitivity analysis of the very complex, space-energy dependent burn-up equations, in which the neutron and nuclide fields are coupled nonlinearly. The adjoint burn-up equations that are given are in a form which can be directly implemented into multi-dimensional depletion codes, such as VENTURE/BURNER. The data sensitivity coefficients can be used to determine the effect of data uncertainties on time-dependent depletion responses. Initial condition sensitivity coefficients provide a very effective method for computing the change in end of cycle parameters (such as k/sub eff/, fissile inventory, etc.) due to changes in nuclide concentrations at beginning of cycle

  14. Sensitivity Analysis of Fatigue Crack Growth Model for API Steels in Gaseous Hydrogen.

    Science.gov (United States)

    Amaro, Robert L; Rustagi, Neha; Drexler, Elizabeth S; Slifka, Andrew J

    2014-01-01

    A model to predict fatigue crack growth of API pipeline steels in high pressure gaseous hydrogen has been developed and is presented elsewhere. The model currently has several parameters that must be calibrated for each pipeline steel of interest. This work provides a sensitivity analysis of the model parameters in order to provide (a) insight to the underlying mathematical and mechanistic aspects of the model, and (b) guidance for model calibration of other API steels.

  15. 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

  16. 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)

  17. Dynamic Simulation, Sensitivity and Uncertainty Analysis of a Demonstration Scale Lignocellulosic Enzymatic Hydrolysis Process

    DEFF Research Database (Denmark)

    Prunescu, Remus Mihail; Sin, Gürkan

    2014-01-01

    This study presents the uncertainty and sensitivity analysis of a lignocellulosic enzymatic hydrolysis model considering both model and feed parameters as sources of uncertainty. The dynamic model is parametrized for accommodating various types of biomass, and different enzymatic complexes...

  18. Adjoint sensitivity analysis of the thermomechanical behavior of repositories

    International Nuclear Information System (INIS)

    Wilson, J.L.; Thompson, B.M.

    1984-01-01

    The adjoint sensitivity method is applied to thermomechanical models for the first time. The method provides an efficient and inexpensive answer to the question: how sensitive are thermomechanical predictions to assumed parameters. The answer is exact, in the sense that it yields exact derivatives of response measures to parameters, and approximate, in the sense that projections of the response fo other parameter assumptions are only first order correct. The method is applied to linear finite element models of thermomechanical behavior. Extensions to more complicated models are straight-forward but often laborious. An illustration of the method with a two-dimensional repository corridor model reveals that the chosen stress response measure was most sensitive to Poisson's ratio for the rock matrix

  19. Optimizing human activity patterns using global sensitivity analysis.

    Science.gov (United States)

    Fairchild, Geoffrey; Hickmann, Kyle S; Mniszewski, Susan M; Del Valle, Sara Y; Hyman, James M

    2014-12-01

    Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule's regularity for a population. We show how to tune an activity's regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.

  20. Sensitive analysis of low-flow parameters using the hourly hydrological model for two mountainous basins in Japan

    Science.gov (United States)

    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

  1. 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

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

    Science.gov (United States)

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

    2014-02-01

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

  3. Simulation-Based Stochastic Sensitivity Analysis of a Mach 4.5 Mixed-Compression Intake Performance

    Science.gov (United States)

    Kato, H.; Ito, K.

    2009-01-01

    A sensitivity analysis of a supersonic mixed-compression intake of a variable-cycle turbine-based combined cycle (TBCC) engine is presented. The TBCC engine is de- signed to power a long-range Mach 4.5 transport capable of antipodal missions studied in the framework of an EU FP6 project, LAPCAT. The nominal intake geometry was designed using DLR abpi cycle analysis pro- gram by taking into account various operating require- ments of a typical mission profile. The intake consists of two movable external compression ramps followed by an isolator section with bleed channel. The compressed air is then diffused through a rectangular-to-circular subsonic diffuser. A multi-block Reynolds-averaged Navier- Stokes (RANS) solver with Srinivasan-Tannehill equilibrium air model was used to compute the total pressure recovery and mass capture fraction. While RANS simulation of the nominal intake configuration provides more realistic performance characteristics of the intake than the cycle analysis program, the intake design must also take into account in-flight uncertainties for robust intake performance. In this study, we focus on the effects of the geometric uncertainties on pressure recovery and mass capture fraction, and propose a practical approach to simulation-based sensitivity analysis. The method begins by constructing a light-weight analytical model, a radial-basis function (RBF) network, trained via adaptively sampled RANS simulation results. Using the RBF network as the response surface approximation, stochastic sensitivity analysis is performed using analysis of variance (ANOVA) technique by Sobol. This approach makes it possible to perform a generalized multi-input- multi-output sensitivity analysis based on high-fidelity RANS simulation. The resulting Sobol's influence indices allow the engineer to identify dominant parameters as well as the degree of interaction among multiple parameters, which can then be fed back into the design cycle.

  4. Modeling and sensitivity analysis of mass transfer in active multilayer polymeric film for food applications

    Science.gov (United States)

    Bedane, T.; Di Maio, L.; Scarfato, P.; Incarnato, L.; Marra, F.

    2015-12-01

    The barrier performance of multilayer polymeric films for food applications has been significantly improved by incorporating oxygen scavenging materials. The scavenging activity depends on parameters such as diffusion coefficient, solubility, concentration of scavenger loaded and the number of available reactive sites. These parameters influence the barrier performance of the film in different ways. Virtualization of the process is useful to characterize, design and optimize the barrier performance based on physical configuration of the films. Also, the knowledge of values of parameters is important to predict the performances. Inverse modeling and sensitivity analysis are sole way to find reasonable values of poorly defined, unmeasured parameters and to analyze the most influencing parameters. Thus, the objective of this work was to develop a model to predict barrier properties of multilayer film incorporated with reactive layers and to analyze and characterize their performances. Polymeric film based on three layers of Polyethylene terephthalate (PET), with a core reactive layer, at different thickness configurations was considered in the model. A one dimensional diffusion equation with reaction was solved numerically to predict the concentration of oxygen diffused into the polymer taking into account the reactive ability of the core layer. The model was solved using commercial software for different film layer configurations and sensitivity analysis based on inverse modeling was carried out to understand the effect of physical parameters. The results have shown that the use of sensitivity analysis can provide physical understanding of the parameters which highly affect the gas permeation into the film. Solubility and the number of available reactive sites were the factors mainly influencing the barrier performance of three layered polymeric film. Multilayer films slightly modified the steady transport properties in comparison to net PET, giving a small reduction

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  6. Sensitivities of surface wave velocities to the medium parameters in a radially anisotropic spherical Earth and inversion strategies

    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.

  7. LHS (latin hypercubes) sampling of the material properties of steels for the analysis of the global sensitivity in welding numerical simulation

    International Nuclear Information System (INIS)

    Petelet, Matthieu; Asserin, Olivier; Iooss, Bertrand; Petelet, Matthieu; Loredo, Alexandre

    2006-01-01

    In this work, the method of sensitivity analysis allowing to identify the inlet data the most influential on the variability of the responses (residual stresses and distortions). Classically, the sensitivity analysis is carried out locally what limits its validity domain to a given material. A global sensitivity analysis method is proposed; it allows to cover a material domain as wide as those of the steels series. A probabilistic modeling giving the variability of the material parameters in the steels series is proposed. The original aspect of this work consists in the use of the sampling method by latin hypercubes (LHS) of the material parameters which forms the inlet data (dependent of temperature) of the numerical simulations. Thus, a statistical approach has been applied to the welding numerical simulation: LHS sampling of the material properties, global sensitivity analysis what has allowed the reduction of the material parameterization. (O.M.)

  8. Implementation of a methodology to perform the uncertainty and sensitivity analysis of the control rod drop in a BWR

    Energy Technology Data Exchange (ETDEWEB)

    Reyes F, M. del C.

    2015-07-01

    A methodology to perform uncertainty and sensitivity analysis for the cross sections used in a Trace/PARCS coupled model for a control rod drop transient of a BWR-5 reactor was implemented with the neutronics code PARCS. A model of the nuclear reactor detailing all assemblies located in the core was developed. However, the thermohydraulic model designed in Trace was a simple model, where one channel representing all the types of assemblies located in the core, it was located inside a simple vessel model and boundary conditions were established. The thermohydraulic model was coupled with the neutronics model, first for the steady state and then a Control Rod Drop (CRD) transient was performed, in order to carry out the uncertainty and sensitivity analysis. To perform the analysis of the cross sections used in the Trace/PARCS coupled model during the transient, Probability Density Functions (PDFs) were generated for the 22 parameters cross sections selected from the neutronics parameters that PARCS requires, thus obtaining 100 different cases for the Trace/PARCS coupled model, each with a database of different cross sections. All these cases were executed with the coupled model, therefore obtaining 100 different outputs for the CRD transient with special emphasis on 4 responses per output: 1) The reactivity, 2) the percentage of rated power, 3) the average fuel temperature and 4) the average coolant density. For each response during the transient an uncertainty analysis was performed in which the corresponding uncertainty bands were generated. With this analysis it is possible to observe the results ranges of the responses chose by varying the uncertainty parameters selected. This is very useful and important for maintaining the safety in the nuclear power plants, also to verify if the uncertainty band is within of safety margins. The sensitivity analysis complements the uncertainty analysis identifying the parameter or parameters with the most influence on the

  9. Implementation of a methodology to perform the uncertainty and sensitivity analysis of the control rod drop in a BWR

    International Nuclear Information System (INIS)

    Reyes F, M. del C.

    2015-01-01

    A methodology to perform uncertainty and sensitivity analysis for the cross sections used in a Trace/PARCS coupled model for a control rod drop transient of a BWR-5 reactor was implemented with the neutronics code PARCS. A model of the nuclear reactor detailing all assemblies located in the core was developed. However, the thermohydraulic model designed in Trace was a simple model, where one channel representing all the types of assemblies located in the core, it was located inside a simple vessel model and boundary conditions were established. The thermohydraulic model was coupled with the neutronics model, first for the steady state and then a Control Rod Drop (CRD) transient was performed, in order to carry out the uncertainty and sensitivity analysis. To perform the analysis of the cross sections used in the Trace/PARCS coupled model during the transient, Probability Density Functions (PDFs) were generated for the 22 parameters cross sections selected from the neutronics parameters that PARCS requires, thus obtaining 100 different cases for the Trace/PARCS coupled model, each with a database of different cross sections. All these cases were executed with the coupled model, therefore obtaining 100 different outputs for the CRD transient with special emphasis on 4 responses per output: 1) The reactivity, 2) the percentage of rated power, 3) the average fuel temperature and 4) the average coolant density. For each response during the transient an uncertainty analysis was performed in which the corresponding uncertainty bands were generated. With this analysis it is possible to observe the results ranges of the responses chose by varying the uncertainty parameters selected. This is very useful and important for maintaining the safety in the nuclear power plants, also to verify if the uncertainty band is within of safety margins. The sensitivity analysis complements the uncertainty analysis identifying the parameter or parameters with the most influence on the

  10. The Sensitivity of the Input Impedance Parameters of Track Circuits to Changes in the Parameters of the Track

    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.

  11. Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters.

    Science.gov (United States)

    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.

  12. Global sensitivity analysis in the identification of cohesive models using full-field kinematic data

    KAUST Repository

    Alfano, Marco; Lubineau, Gilles; Paulino, Glá ucio Hermogenes

    2015-01-01

    Failure of adhesive bonded structures often occurs concurrent with the formation of a non-negligible fracture process zone in front of a macroscopic crack. For this reason, the analysis of damage and fracture is effectively carried out using the cohesive zone model (CZM). The crucial aspect of the CZM approach is the precise determination of the traction-separation relation. Yet it is usually determined empirically, by using calibration procedures combining experimental data, such as load-displacement or crack length data, with finite element simulation of fracture. Thanks to the recent progress in image processing, and the availability of low-cost CCD cameras, it is nowadays relatively easy to access surface displacements across the fracture process zone using for instance Digital Image Correlation (DIC). The rich information provided by correlation techniques prompted the development of versatile inverse parameter identification procedures combining finite element (FE) simulations and full field kinematic data. The focus of the present paper is to assess the effectiveness of these methods in the identification of cohesive zone models. In particular, the analysis is developed in the framework of the variance based global sensitivity analysis. The sensitivity of kinematic data to the sought cohesive properties is explored through the computation of the so-called Sobol sensitivity indexes. The results show that the global sensitivity analysis can help to ascertain the most influential cohesive parameters which need to be incorporated in the identification process. In addition, it is shown that suitable displacement sampling in time and space can lead to optimized measurements for identification purposes.

  13. Global sensitivity analysis in the identification of cohesive models using full-field kinematic data

    KAUST Repository

    Alfano, Marco

    2015-03-01

    Failure of adhesive bonded structures often occurs concurrent with the formation of a non-negligible fracture process zone in front of a macroscopic crack. For this reason, the analysis of damage and fracture is effectively carried out using the cohesive zone model (CZM). The crucial aspect of the CZM approach is the precise determination of the traction-separation relation. Yet it is usually determined empirically, by using calibration procedures combining experimental data, such as load-displacement or crack length data, with finite element simulation of fracture. Thanks to the recent progress in image processing, and the availability of low-cost CCD cameras, it is nowadays relatively easy to access surface displacements across the fracture process zone using for instance Digital Image Correlation (DIC). The rich information provided by correlation techniques prompted the development of versatile inverse parameter identification procedures combining finite element (FE) simulations and full field kinematic data. The focus of the present paper is to assess the effectiveness of these methods in the identification of cohesive zone models. In particular, the analysis is developed in the framework of the variance based global sensitivity analysis. The sensitivity of kinematic data to the sought cohesive properties is explored through the computation of the so-called Sobol sensitivity indexes. The results show that the global sensitivity analysis can help to ascertain the most influential cohesive parameters which need to be incorporated in the identification process. In addition, it is shown that suitable displacement sampling in time and space can lead to optimized measurements for identification purposes.

  14. B1 -sensitivity analysis of quantitative magnetization transfer imaging.

    Science.gov (United States)

    Boudreau, Mathieu; Stikov, Nikola; Pike, G Bruce

    2018-01-01

    To evaluate the sensitivity of quantitative magnetization transfer (qMT) fitted parameters to B 1 inaccuracies, focusing on the difference between two categories of T 1 mapping techniques: B 1 -independent and B 1 -dependent. The B 1 -sensitivity of qMT was investigated and compared using two T 1 measurement methods: inversion recovery (IR) (B 1 -independent) and variable flip angle (VFA), B 1 -dependent). The study was separated into four stages: 1) numerical simulations, 2) sensitivity analysis of the Z-spectra, 3) healthy subjects at 3T, and 4) comparison using three different B 1 imaging techniques. For typical B 1 variations in the brain at 3T (±30%), the simulations resulted in errors of the pool-size ratio (F) ranging from -3% to 7% for VFA, and -40% to > 100% for IR, agreeing with the Z-spectra sensitivity analysis. In healthy subjects, pooled whole-brain Pearson correlation coefficients for F (comparing measured double angle and nominal flip angle B 1 maps) were ρ = 0.97/0.81 for VFA/IR. This work describes the B 1 -sensitivity characteristics of qMT, demonstrating that it varies substantially on the B 1 -dependency of the T 1 mapping method. Particularly, the pool-size ratio is more robust against B 1 inaccuracies if VFA T 1 mapping is used, so much so that B 1 mapping could be omitted without substantially biasing F. Magn Reson Med 79:276-285, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  15. Sensitivity of probability-of-failure estimates with respect to probability of detection curve parameters

    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.

  16. Sensitivity of probability-of-failure estimates with respect to probability of detection curve parameters

    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.

  17. Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models

    Directory of Open Access Journals (Sweden)

    J. D. Herman

    2013-07-01

    Full Text Available The increase in spatially distributed hydrologic modeling warrants a corresponding increase in diagnostic methods capable of analyzing complex models with large numbers of parameters. Sobol' sensitivity analysis has proven to be a valuable tool for diagnostic analyses of hydrologic models. However, for many spatially distributed models, the Sobol' method requires a prohibitive number of model evaluations to reliably decompose output variance across the full set of parameters. We investigate the potential of the method of Morris, a screening-based sensitivity approach, to provide results sufficiently similar to those of the Sobol' method at a greatly reduced computational expense. The methods are benchmarked on the Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM over a six-month period in the Blue River watershed, Oklahoma, USA. The Sobol' method required over six million model evaluations to ensure reliable sensitivity indices, corresponding to more than 30 000 computing hours and roughly 180 gigabytes of storage space. We find that the method of Morris is able to correctly screen the most and least sensitive parameters with 300 times fewer model evaluations, requiring only 100 computing hours and 1 gigabyte of storage space. The method of Morris proves to be a promising diagnostic approach for global sensitivity analysis of highly parameterized, spatially distributed hydrologic models.

  18. A Monte Carlo/response surface strategy for sensitivity analysis: application to a dynamic model of vegetative plant growth

    Science.gov (United States)

    Lim, J. T.; Gold, H. J.; Wilkerson, G. G.; Raper, C. D. Jr; Raper CD, J. r. (Principal Investigator)

    1989-01-01

    We describe the application of a strategy for conducting a sensitivity analysis for a complex dynamic model. The procedure involves preliminary screening of parameter sensitivities by numerical estimation of linear sensitivity coefficients, followed by generation of a response surface based on Monte Carlo simulation. Application is to a physiological model of the vegetative growth of soybean plants. The analysis provides insights as to the relative importance of certain physiological processes in controlling plant growth. Advantages and disadvantages of the strategy are discussed.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-01-15

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

  20. Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations

    International Nuclear Information System (INIS)

    Arampatzis, Georgios; Katsoulakis, Markos A.

    2014-01-01

    In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo (KMC). Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the mean value of samples from a finite difference scheme. Instead of using independent samples the proposed algorithm reduces the variance of the estimator by developing a strongly correlated-“coupled”- stochastic process for both the perturbed and unperturbed stochastic processes, defined in a common state space. The novelty of our construction is that the new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz–Kalos–Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary

  1. Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations.

    Science.gov (United States)

    Arampatzis, Georgios; Katsoulakis, Markos A

    2014-03-28

    In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo (KMC). Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the mean value of samples from a finite difference scheme. Instead of using independent samples the proposed algorithm reduces the variance of the estimator by developing a strongly correlated-"coupled"- stochastic process for both the perturbed and unperturbed stochastic processes, defined in a common state space. The novelty of our construction is that the new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz-Kalos-Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary MATLAB

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  3. Examining the accuracy of the infinite order sudden approximation using sensitivity analysis

    Science.gov (United States)

    Eno, Larry; Rabitz, Herschel

    1981-08-01

    A method is developed for assessing the accuracy of scattering observables calculated within the framework of the infinite order sudden (IOS) approximation. In particular, we focus on the energy sudden assumption of the IOS method and our approach involves the determination of the sensitivity of the IOS scattering matrix SIOS with respect to a parameter which reintroduces the internal energy operator ?0 into the IOS Hamiltonian. This procedure is an example of sensitivity analysis of missing model components (?0 in this case) in the reference Hamiltonian. In contrast to simple first-order perturbation theory a finite result is obtained for the effect of ?0 on SIOS. As an illustration, our method of analysis is applied to integral state-to-state cross sections for the scattering of an atom and rigid rotor. Results are generated within the He+H2 system and a comparison is made between IOS and coupled states cross sections and the corresponding IOS sensitivities. It is found that the sensitivity coefficients are very useful indicators of the accuracy of the IOS results. Finally, further developments and applications are discussed.

  4. Failure analysis of parameter-induced simulation crashes in climate models

    Science.gov (United States)

    Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

    2013-08-01

    Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative 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 crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

  5. Sensitivity of the model error parameter specification in weak-constraint four-dimensional variational data assimilation

    Science.gov (United States)

    Shaw, Jeremy A.; Daescu, Dacian N.

    2017-08-01

    This article presents the mathematical framework to evaluate the sensitivity of a forecast error aspect to the input parameters of a weak-constraint four-dimensional variational data assimilation system (w4D-Var DAS), extending the established theory from strong-constraint 4D-Var. Emphasis is placed on the derivation of the equations for evaluating the forecast sensitivity to parameters in the DAS representation of the model error statistics, including bias, standard deviation, and correlation structure. A novel adjoint-based procedure for adaptive tuning of the specified model error covariance matrix is introduced. Results from numerical convergence tests establish the validity of the model error sensitivity equations. Preliminary experiments providing a proof-of-concept are performed using the Lorenz multi-scale model to illustrate the theoretical concepts and potential benefits for practical applications.

  6. Influence of parameter values on the oscillation sensitivities of two p53-Mdm2 models.

    Science.gov (United States)

    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.

  7. Interference and Sensitivity Analysis.

    Science.gov (United States)

    VanderWeele, Tyler J; Tchetgen Tchetgen, Eric J; Halloran, M Elizabeth

    2014-11-01

    Causal inference with interference is a rapidly growing area. The literature has begun to relax the "no-interference" assumption that the treatment received by one individual does not affect the outcomes of other individuals. In this paper we briefly review the literature on causal inference in the presence of interference when treatments have been randomized. We then consider settings in which causal effects in the presence of interference are not identified, either because randomization alone does not suffice for identification, or because treatment is not randomized and there may be unmeasured confounders of the treatment-outcome relationship. We develop sensitivity analysis techniques for these settings. We describe several sensitivity analysis techniques for the infectiousness effect which, in a vaccine trial, captures the effect of the vaccine of one person on protecting a second person from infection even if the first is infected. We also develop two sensitivity analysis techniques for causal effects in the presence of unmeasured confounding which generalize analogous techniques when interference is absent. These two techniques for unmeasured confounding are compared and contrasted.

  8. 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.

  9. Optimization of parameters for the analysis of the decabrominated diphenylether using PTV and split/splitless injectors and the consecutive setup of a dual column analysis method

    Energy Technology Data Exchange (ETDEWEB)

    Krumwiede, D.; Muenster, H.; Griep-Raming, J. [Thermo Electron Corporation, Bremen (Germany)

    2004-09-15

    Brominated diphenyl ethers (BDEs) are widely used as flame retardants in electronics industry. However, for the following reasons the mass spectrometric analysis of BDEs by high resolution magnetic sector mass spectrometry is more complicated than e.g. analysis of polychlorinated dioxins and furans: i) a high mass range from m/z 248 (mono-BDE) to m/z 960 (deca-BDE) is required, therefore demanding a reference compound that provides sufficient intensity on high m/z ions, ii) large electric jumps are necessary for window defining measurements, which demands for a stable and rugged electric mass calibration, and iii) the Deca-BDE being thermally labile, requiring optimized chromatographic methods. The first and second complication can be overcome by the correct selection of instrument parameters and by proper selection of the reference compound. Probably the most severe complication is that the deca-BDE is thermally labile, and decomposes during GC analysis. Optimized chromatographic parameters are needed in order to achieve good sensitivity for deca BDE. However, such chromatographic parameters usually sacrifice separation efficiency for the other congeners. In the following it will be shown how different chromatographic parameters influence the analytical sensitivity for the thermolabile deca BDE. Furthermore a method setup is presented, which combines optimum sensitivity for the deca BDE and at the same time good separation efficiency for mono to hepta BDE.

  10. Sensitivity analysis in economic evaluation: an audit of NICE current practice and a review of its use and value in decision-making.

    Science.gov (United States)

    Andronis, L; Barton, P; Bryan, S

    2009-06-01

    To determine how we define good practice in sensitivity analysis in general and probabilistic sensitivity analysis (PSA) in particular, and to what extent it has been adhered to in the independent economic evaluations undertaken for the National Institute for Health and Clinical Excellence (NICE) over recent years; to establish what policy impact sensitivity analysis has in the context of NICE, and policy-makers' views on sensitivity analysis and uncertainty, and what use is made of sensitivity analysis in policy decision-making. Three major electronic databases, MEDLINE, EMBASE and the NHS Economic Evaluation Database, were searched from inception to February 2008. The meaning of 'good practice' in the broad area of sensitivity analysis was explored through a review of the literature. An audit was undertaken of the 15 most recent NICE multiple technology appraisal judgements and their related reports to assess how sensitivity analysis has been undertaken by independent academic teams for NICE. A review of the policy and guidance documents issued by NICE aimed to assess the policy impact of the sensitivity analysis and the PSA in particular. Qualitative interview data from NICE Technology Appraisal Committee members, collected as part of an earlier study, were also analysed to assess the value attached to the sensitivity analysis components of the economic analyses conducted for NICE. All forms of sensitivity analysis, notably both deterministic and probabilistic approaches, have their supporters and their detractors. Practice in relation to univariate sensitivity analysis is highly variable, with considerable lack of clarity in relation to the methods used and the basis of the ranges employed. In relation to PSA, there is a high level of variability in the form of distribution used for similar parameters, and the justification for such choices is rarely given. Virtually all analyses failed to consider correlations within the PSA, and this is an area of concern

  11. Post-liquefaction soil-structure interaction for buried structures: Sensitivity analysis studies

    International Nuclear Information System (INIS)

    Pires, J.A.; Ang, H.S.; Katayama, I.; Satoh, M.

    1993-01-01

    The post liquefaction behavior of buried conduits is analyzed and sensitivity analysis is conducted to investigate the damage potential of the forces induced in the buried lifelines following seismically induced liquefaction of the surrounding soil. Various lifeline configurations and loading conditions are considered. The loading conditions considered are: buoyancy forces and permanent ground displacements parallel to the lifeline axis. Pertinent parameters for the soil-lifeline interaction following liquefaction are identified. (author)

  12. Sensitivity Analysis of features in tolerancing based on constraint function level sets

    International Nuclear Information System (INIS)

    Ziegler, Philipp; Wartzack, Sandro

    2015-01-01

    Usually, the geometry of the manufactured product inherently varies from the nominal geometry. This may negatively affect the product functions and properties (such as quality and reliability), as well as the assemblability of the single components. In order to avoid this, the geometric variation of these component surfaces and associated geometry elements (like hole axes) are restricted by tolerances. Since tighter tolerances lead to significant higher manufacturing costs, tolerances should be specified carefully. Therefore, the impact of deviating component surfaces on functions, properties and assemblability of the product has to be analyzed. As physical experiments are expensive, methods of statistical tolerance analysis tools are widely used in engineering design. Current tolerance simulation tools lack of an appropriate indicator for the impact of deviating component surfaces. In the adoption of Sensitivity Analysis methods, there are several challenges, which arise from the specific framework in tolerancing. This paper presents an approach to adopt Sensitivity Analysis methods on current tolerance simulations with an interface module, which bases on level sets of constraint functions for parameters of the simulation model. The paper is an extension and generalization of Ziegler and Wartzack [1]. Mathematical properties of the constraint functions (convexity, homogeneity), which are important for the computational costs of the Sensitivity Analysis, are shown. The practical use of the method is illustrated in a case study of a plain bearing. - Highlights: • Alternative definition of Deviation Domains. • Proof of mathematical properties of the Deviation Domains. • Definition of the interface between Deviation Domains and Sensitivity Analysis. • Sensitivity analysis of a gearbox to show the methods practical use

  13. Estimating Sobol Sensitivity Indices Using Correlations

    Science.gov (United States)

    Sensitivity analysis is a crucial tool in the development and evaluation of complex mathematical models. Sobol's method is a variance-based global sensitivity analysis technique that has been applied to computational models to assess the relative importance of input parameters on...

  14. Sensitivity of control times in function of core parameters and oscillations control in thermal nuclear systems

    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

  15. Key Parameters for Urban Heat Island Assessment in A Mediterranean Context: A Sensitivity Analysis Using the Urban Weather Generator Model

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    1975-01-01

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

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  18. Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters

    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)

  19. Contributions to sensitivity analysis and generalized discriminant analysis

    International Nuclear Information System (INIS)

    Jacques, J.

    2005-12-01

    Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)

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

    Science.gov (United States)

    Lee, Yeonok; Wu, Hulin

    2012-01-01

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