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Sample records for sensitivity analysis based

  1. Survey of sampling-based methods for uncertainty and sensitivity analysis

    International Nuclear Information System (INIS)

    Helton, J.C.; Johnson, J.D.; Sallaberry, C.J.; Storlie, C.B.

    2006-01-01

    Sampling-based methods for uncertainty and sensitivity analysis are reviewed. The following topics are considered: (i) definition of probability distributions to characterize epistemic uncertainty in analysis inputs (ii) generation of samples from uncertain analysis inputs (iii) propagation of sampled inputs through an analysis (iv) presentation of uncertainty analysis results, and (v) determination of sensitivity analysis results. Special attention is given to the determination of sensitivity analysis results, with brief descriptions and illustrations given for the following procedures/techniques: examination of scatterplots, correlation analysis, regression analysis, partial correlation analysis, rank transformations, statistical tests for patterns based on gridding, entropy tests for patterns based on gridding, nonparametric regression analysis, squared rank differences/rank correlation coefficient test, two-dimensional Kolmogorov-Smirnov test, tests for patterns based on distance measures, top down coefficient of concordance, and variance decomposition

  2. Survey of sampling-based methods for uncertainty and sensitivity analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, Jay Dean; Helton, Jon Craig; Sallaberry, Cedric J. PhD. (.; .); Storlie, Curt B. (Colorado State University, Fort Collins, CO)

    2006-06-01

    Sampling-based methods for uncertainty and sensitivity analysis are reviewed. The following topics are considered: (1) Definition of probability distributions to characterize epistemic uncertainty in analysis inputs, (2) Generation of samples from uncertain analysis inputs, (3) Propagation of sampled inputs through an analysis, (4) Presentation of uncertainty analysis results, and (5) Determination of sensitivity analysis results. Special attention is given to the determination of sensitivity analysis results, with brief descriptions and illustrations given for the following procedures/techniques: examination of scatterplots, correlation analysis, regression analysis, partial correlation analysis, rank transformations, statistical tests for patterns based on gridding, entropy tests for patterns based on gridding, nonparametric regression analysis, squared rank differences/rank correlation coefficient test, two dimensional Kolmogorov-Smirnov test, tests for patterns based on distance measures, top down coefficient of concordance, and variance decomposition.

  3. 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.

  4. Beyond the GUM: variance-based sensitivity analysis in metrology

    International Nuclear Information System (INIS)

    Lira, I

    2016-01-01

    Variance-based sensitivity analysis is a well established tool for evaluating the contribution of the uncertainties in the inputs to the uncertainty in the output of a general mathematical model. While the literature on this subject is quite extensive, it has not found widespread use in metrological applications. In this article we present a succinct review of the fundamentals of sensitivity analysis, in a form that should be useful to most people familiarized with the Guide to the Expression of Uncertainty in Measurement (GUM). Through two examples, it is shown that in linear measurement models, no new knowledge is gained by using sensitivity analysis that is not already available after the terms in the so-called ‘law of propagation of uncertainties’ have been computed. However, if the model behaves non-linearly in the neighbourhood of the best estimates of the input quantities—and if these quantities are assumed to be statistically independent—sensitivity analysis is definitely advantageous for gaining insight into how they can be ranked according to their importance in establishing the uncertainty of the measurand. (paper)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-10-15

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

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

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  7. Thermodynamics-based Metabolite Sensitivity Analysis in metabolic networks.

    Science.gov (United States)

    Kiparissides, A; Hatzimanikatis, V

    2017-01-01

    The increasing availability of large metabolomics datasets enhances the need for computational methodologies that can organize the data in a way that can lead to the inference of meaningful relationships. Knowledge of the metabolic state of a cell and how it responds to various stimuli and extracellular conditions can offer significant insight in the regulatory functions and how to manipulate them. Constraint based methods, such as Flux Balance Analysis (FBA) and Thermodynamics-based flux analysis (TFA), are commonly used to estimate the flow of metabolites through genome-wide metabolic networks, making it possible to identify the ranges of flux values that are consistent with the studied physiological and thermodynamic conditions. However, unless key intracellular fluxes and metabolite concentrations are known, constraint-based models lead to underdetermined problem formulations. This lack of information propagates as uncertainty in the estimation of fluxes and basic reaction properties such as the determination of reaction directionalities. Therefore, knowledge of which metabolites, if measured, would contribute the most to reducing this uncertainty can significantly improve our ability to define the internal state of the cell. In the present work we combine constraint based modeling, Design of Experiments (DoE) and Global Sensitivity Analysis (GSA) into the Thermodynamics-based Metabolite Sensitivity Analysis (TMSA) method. TMSA ranks metabolites comprising a metabolic network based on their ability to constrain the gamut of possible solutions to a limited, thermodynamically consistent set of internal states. TMSA is modular and can be applied to a single reaction, a metabolic pathway or an entire metabolic network. This is, to our knowledge, the first attempt to use metabolic modeling in order to provide a significance ranking of metabolites to guide experimental measurements. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier

  8. 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

  9. 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

  10. 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.

  11. 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

  12. 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.

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

    Science.gov (United States)

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

    2014-02-01

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

  14. Adjoint-based sensitivity analysis of low-order thermoacoustic networks using a wave-based approach

    Science.gov (United States)

    Aguilar, José G.; Magri, Luca; Juniper, Matthew P.

    2017-07-01

    Strict pollutant emission regulations are pushing gas turbine manufacturers to develop devices that operate in lean conditions, with the downside that combustion instabilities are more likely to occur. Methods to predict and control unstable modes inside combustion chambers have been developed in the last decades but, in some cases, they are computationally expensive. Sensitivity analysis aided by adjoint methods provides valuable sensitivity information at a low computational cost. This paper introduces adjoint methods and their application in wave-based low order network models, which are used as industrial tools, to predict and control thermoacoustic oscillations. Two thermoacoustic models of interest are analyzed. First, in the zero Mach number limit, a nonlinear eigenvalue problem is derived, and continuous and discrete adjoint methods are used to obtain the sensitivities of the system to small modifications. Sensitivities to base-state modification and feedback devices are presented. Second, a more general case with non-zero Mach number, a moving flame front and choked outlet, is presented. The influence of the entropy waves on the computed sensitivities is shown.

  15. 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.

  16. 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

  17. A comparison of approximation techniques for variance-based sensitivity analysis of biochemical reaction systems

    Directory of Open Access Journals (Sweden)

    Goutsias John

    2010-05-01

    Full Text Available Abstract Background Sensitivity analysis is an indispensable tool for the analysis of complex systems. In a recent paper, we have introduced a thermodynamically consistent variance-based sensitivity analysis approach for studying the robustness and fragility properties of biochemical reaction systems under uncertainty in the standard chemical potentials of the activated complexes of the reactions and the standard chemical potentials of the molecular species. In that approach, key sensitivity indices were estimated by Monte Carlo sampling, which is computationally very demanding and impractical for large biochemical reaction systems. Computationally efficient algorithms are needed to make variance-based sensitivity analysis applicable to realistic cellular networks, modeled by biochemical reaction systems that consist of a large number of reactions and molecular species. Results We present four techniques, derivative approximation (DA, polynomial approximation (PA, Gauss-Hermite integration (GHI, and orthonormal Hermite approximation (OHA, for analytically approximating the variance-based sensitivity indices associated with a biochemical reaction system. By using a well-known model of the mitogen-activated protein kinase signaling cascade as a case study, we numerically compare the approximation quality of these techniques against traditional Monte Carlo sampling. Our results indicate that, although DA is computationally the most attractive technique, special care should be exercised when using it for sensitivity analysis, since it may only be accurate at low levels of uncertainty. On the other hand, PA, GHI, and OHA are computationally more demanding than DA but can work well at high levels of uncertainty. GHI results in a slightly better accuracy than PA, but it is more difficult to implement. OHA produces the most accurate approximation results and can be implemented in a straightforward manner. It turns out that the computational cost of the

  18. 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.

  19. 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

  20. 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

  1. Cross-covariance based global dynamic sensitivity analysis

    Science.gov (United States)

    Shi, Yan; Lu, Zhenzhou; Li, Zhao; Wu, Mengmeng

    2018-02-01

    For identifying the cross-covariance source of dynamic output at each time instant for structural system involving both input random variables and stochastic processes, a global dynamic sensitivity (GDS) technique is proposed. The GDS considers the effect of time history inputs on the dynamic output. In the GDS, the cross-covariance decomposition is firstly developed to measure the contribution of the inputs to the output at different time instant, and an integration of the cross-covariance change over the specific time interval is employed to measure the whole contribution of the input to the cross-covariance of output. Then, the GDS main effect indices and the GDS total effect indices can be easily defined after the integration, and they are effective in identifying the important inputs and the non-influential inputs on the cross-covariance of output at each time instant, respectively. The established GDS analysis model has the same form with the classical ANOVA when it degenerates to the static case. After degeneration, the first order partial effect can reflect the individual effects of inputs to the output variance, and the second order partial effect can reflect the interaction effects to the output variance, which illustrates the consistency of the proposed GDS indices and the classical variance-based sensitivity indices. The MCS procedure and the Kriging surrogate method are developed to solve the proposed GDS indices. Several examples are introduced to illustrate the significance of the proposed GDS analysis technique and the effectiveness of the proposed solution.

  2. 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.

  3. 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

  4. Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study

    International Nuclear Information System (INIS)

    Zhai, Qingqing; Yang, Jun; Zhao, Yu

    2014-01-01

    Variance-based sensitivity analysis has been widely studied and asserted itself among practitioners. Monte Carlo simulation methods are well developed in the calculation of variance-based sensitivity indices but they do not make full use of each model run. Recently, several works mentioned a scatter-plot partitioning method to estimate the variance-based sensitivity indices from given data, where a single bunch of samples is sufficient to estimate all the sensitivity indices. This paper focuses on the space-partition method in the estimation of variance-based sensitivity indices, and its convergence and other performances are investigated. Since the method heavily depends on the partition scheme, the influence of the partition scheme is discussed and the optimal partition scheme is proposed based on the minimized estimator's variance. A decomposition and integration procedure is proposed to improve the estimation quality for higher order sensitivity indices. The proposed space-partition method is compared with the more traditional method and test cases show that it outperforms the traditional one

  5. 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.

  6. Multiple predictor smoothing methods for sensitivity analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Helton, Jon Craig; Storlie, Curtis B.

    2006-08-01

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

  7. Multiple predictor smoothing methods for sensitivity analysis

    International Nuclear Information System (INIS)

    Helton, Jon Craig; Storlie, Curtis B.

    2006-01-01

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

  8. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-03-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

  9. Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy

    Science.gov (United States)

    Shi, Yan; Lu, Zhenzhou; Zhou, Yicheng

    2018-06-01

    To analyse the component of fuzzy output entropy, a decomposition method of fuzzy output entropy is first presented. After the decomposition of fuzzy output entropy, the total fuzzy output entropy can be expressed as the sum of the component fuzzy entropy contributed by fuzzy inputs. Based on the decomposition of fuzzy output entropy, a new global sensitivity analysis model is established for measuring the effects of uncertainties of fuzzy inputs on the output. The global sensitivity analysis model can not only tell the importance of fuzzy inputs but also simultaneously reflect the structural composition of the response function to a certain degree. Several examples illustrate the validity of the proposed global sensitivity analysis, which is a significant reference in engineering design and optimization of structural systems.

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

    Energy Technology Data Exchange (ETDEWEB)

    Tong, C

    2007-10-15

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

  11. [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.

  12. 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

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

    Science.gov (United States)

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

  14. Object-sensitive Type Analysis of PHP

    NARCIS (Netherlands)

    Van der Hoek, Henk Erik; Hage, J

    2015-01-01

    In this paper we develop an object-sensitive type analysis for PHP, based on an extension of the notion of monotone frameworks to deal with the dynamic aspects of PHP, and following the framework of Smaragdakis et al. for object-sensitive analysis. We consider a number of instantiations of the

  15. 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) ...

  16. Robust Stability Clearance of Flight Control Law Based on Global Sensitivity Analysis

    Directory of Open Access Journals (Sweden)

    Liuli Ou

    2014-01-01

    Full Text Available To validate the robust stability of the flight control system of hypersonic flight vehicle, which suffers from a large number of parametrical uncertainties, a new clearance framework based on structural singular value (μ theory and global uncertainty sensitivity analysis (SA is proposed. In this framework, SA serves as the preprocess of uncertain model to be analysed to help engineers to determine which uncertainties affect the stability of the closed loop system more slightly. By ignoring these unimportant uncertainties, the calculation of μ can be simplified. Instead of analysing the effect of uncertainties on μ which involves solving optimal problems repeatedly, a simpler stability analysis function which represents the effect of uncertainties on closed loop poles is proposed. Based on this stability analysis function, Sobol’s method, the most widely used global SA method, is extended and applied to the new clearance framework due to its suitability for system with strong nonlinearity and input factors varying in large interval, as well as input factors subjecting to random distributions. In this method, the sensitive indices can be estimated via Monte Carlo simulation conveniently. An example is given to illustrate the efficiency of the proposed method.

  17. Development of a finite-element-based design sensitivity analysis for buckling and postbuckling of composite plates

    Directory of Open Access Journals (Sweden)

    Guo Ruijiang

    1995-01-01

    Full Text Available A finite element based sensitivity analysis procedure is developed for buckling and postbuckling of composite plates. This procedure is based on the direct differentiation approach combined with the reference volume concept. Linear elastic material model and nonlinear geometric relations are used. The sensitivity analysis technique results in a set of linear algebraic equations which are easy to solve. The procedure developed provides the sensitivity derivatives directly from the current load and responses by solving the set of linear equations. Numerical results are presented and are compared with those obtained using finite difference technique. The results show good agreement except at points near critical buckling load where discontinuities occur. The procedure is very efficient computationally.

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

    Science.gov (United States)

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

    2001-12-01

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

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

    Science.gov (United States)

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

    2008-08-15

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

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

    International Nuclear Information System (INIS)

    Mara, Thierry A.; Tarantola, Stefano

    2012-01-01

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

  1. 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.

  2. Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - I: Theory

    International Nuclear Information System (INIS)

    Cacuci, D. G.; Cacuci, D. G.; Ionescu-Bujor, M.

    2008-01-01

    The development of the adjoint sensitivity analysis procedure (ASAP) for generic dynamic reliability models based on Markov chains is presented, together with applications of this procedure to the analysis of several systems of increasing complexity. The general theory is presented in Part I of this work and is accompanied by a paradigm application to the dynamic reliability analysis of a simple binary component, namely a pump functioning on an 'up/down' cycle until it fails irreparably. This paradigm example admits a closed form analytical solution, which permits a clear illustration of the main characteristics of the ASAP for Markov chains. In particular, it is shown that the ASAP for Markov chains presents outstanding computational advantages over other procedures currently in use for sensitivity and uncertainty analysis of the dynamic reliability of large-scale systems. This conclusion is further underscored by the large-scale applications presented in Part II. (authors)

  3. Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - I: Theory

    Energy Technology Data Exchange (ETDEWEB)

    Cacuci, D. G. [Commiss Energy Atom, Direct Energy Nucl, Saclay, (France); Cacuci, D. G. [Univ Karlsruhe, Inst Nucl Technol and Reactor Safety, D-76021 Karlsruhe, (Germany); Ionescu-Bujor, M. [Forschungszentrum Karlsruhe, Fus Program, D-76021 Karlsruhe, (Germany)

    2008-07-01

    The development of the adjoint sensitivity analysis procedure (ASAP) for generic dynamic reliability models based on Markov chains is presented, together with applications of this procedure to the analysis of several systems of increasing complexity. The general theory is presented in Part I of this work and is accompanied by a paradigm application to the dynamic reliability analysis of a simple binary component, namely a pump functioning on an 'up/down' cycle until it fails irreparably. This paradigm example admits a closed form analytical solution, which permits a clear illustration of the main characteristics of the ASAP for Markov chains. In particular, it is shown that the ASAP for Markov chains presents outstanding computational advantages over other procedures currently in use for sensitivity and uncertainty analysis of the dynamic reliability of large-scale systems. This conclusion is further underscored by the large-scale applications presented in Part II. (authors)

  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. 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

  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. 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

  9. 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.

  10. Derivation of Continuum Models from An Agent-based Cancer Model: Optimization and Sensitivity Analysis.

    Science.gov (United States)

    Voulgarelis, Dimitrios; Velayudhan, Ajoy; Smith, Frank

    2017-01-01

    Agent-based models provide a formidable tool for exploring complex and emergent behaviour of biological systems as well as accurate results but with the drawback of needing a lot of computational power and time for subsequent analysis. On the other hand, equation-based models can more easily be used for complex analysis in a much shorter timescale. This paper formulates an ordinary differential equations and stochastic differential equations model to capture the behaviour of an existing agent-based model of tumour cell reprogramming and applies it to optimization of possible treatment as well as dosage sensitivity analysis. For certain values of the parameter space a close match between the equation-based and agent-based models is achieved. The need for division of labour between the two approaches is explored. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  11. LBLOCA sensitivity analysis using meta models

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  12. Robust Stability Clearance of Flight Control Law Based on Global Sensitivity Analysis

    OpenAIRE

    Ou, Liuli; Liu, Lei; Dong, Shuai; Wang, Yongji

    2014-01-01

    To validate the robust stability of the flight control system of hypersonic flight vehicle, which suffers from a large number of parametrical uncertainties, a new clearance framework based on structural singular value ( $\\mu $ ) theory and global uncertainty sensitivity analysis (SA) is proposed. In this framework, SA serves as the preprocess of uncertain model to be analysed to help engineers to determine which uncertainties affect the stability of the closed loop system more slightly. By ig...

  13. Weighting-Based Sensitivity Analysis in Causal Mediation Studies

    Science.gov (United States)

    Hong, Guanglei; Qin, Xu; Yang, Fan

    2018-01-01

    Through a sensitivity analysis, the analyst attempts to determine whether a conclusion of causal inference could be easily reversed by a plausible violation of an identification assumption. Analytic conclusions that are harder to alter by such a violation are expected to add a higher value to scientific knowledge about causality. This article…

  14. 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

  15. 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.

  16. Sensitivity Enhancement of FBG-Based Strain Sensor.

    Science.gov (United States)

    Li, Ruiya; Chen, Yiyang; Tan, Yuegang; Zhou, Zude; Li, Tianliang; Mao, Jian

    2018-05-17

    A novel fiber Bragg grating (FBG)-based strain sensor with a high-sensitivity is presented in this paper. The proposed FBG-based strain sensor enhances sensitivity by pasting the FBG on a substrate with a lever structure. This typical mechanical configuration mechanically amplifies the strain of the FBG to enhance overall sensitivity. As this mechanical configuration has a high stiffness, the proposed sensor can achieve a high resonant frequency and a wide dynamic working range. The sensing principle is presented, and the corresponding theoretical model is derived and validated. Experimental results demonstrate that the developed FBG-based strain sensor achieves an enhanced strain sensitivity of 6.2 pm/με, which is consistent with the theoretical analysis result. The strain sensitivity of the developed sensor is 5.2 times of the strain sensitivity of a bare fiber Bragg grating strain sensor. The dynamic characteristics of this sensor are investigated through the finite element method (FEM) and experimental tests. The developed sensor exhibits an excellent strain-sensitivity-enhancing property in a wide frequency range. The proposed high-sensitivity FBG-based strain sensor can be used for small-amplitude micro-strain measurement in harsh industrial environments.

  17. System-Level Sensitivity Analysis of SiNW-bioFET-Based Biosensing Using Lockin Amplification

    DEFF Research Database (Denmark)

    Patou, François; Dimaki, Maria; Kjærgaard, Claus

    2017-01-01

    carry out for the first time the system-level sensitivity analysis of a generic SiNW-bioFET model coupled to a custom-design instrument based on the lock-in amplifier. By investigating a large parametric space spanning over both sensor and instrumentation specifications, we demonstrate that systemwide...

  18. Multiple predictor smoothing methods for sensitivity analysis: Example results

    International Nuclear Information System (INIS)

    Storlie, Curtis B.; Helton, Jon C.

    2008-01-01

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

  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. Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis: A Tutorial.

    Science.gov (United States)

    Leurent, Baptiste; Gomes, Manuel; Faria, Rita; Morris, Stephen; Grieve, Richard; Carpenter, James R

    2018-04-20

    Cost-effectiveness analyses (CEA) of randomised controlled trials are a key source of information for health care decision makers. Missing data are, however, a common issue that can seriously undermine their validity. A major concern is that the chance of data being missing may be directly linked to the unobserved value itself [missing not at random (MNAR)]. For example, patients with poorer health may be less likely to complete quality-of-life questionnaires. However, the extent to which this occurs cannot be ascertained from the data at hand. Guidelines recommend conducting sensitivity analyses to assess the robustness of conclusions to plausible MNAR assumptions, but this is rarely done in practice, possibly because of a lack of practical guidance. This tutorial aims to address this by presenting an accessible framework and practical guidance for conducting sensitivity analysis for MNAR data in trial-based CEA. We review some of the methods for conducting sensitivity analysis, but focus on one particularly accessible approach, where the data are multiply-imputed and then modified to reflect plausible MNAR scenarios. We illustrate the implementation of this approach on a weight-loss trial, providing the software code. We then explore further issues around its use in practice.

  1. 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

  2. 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.

  3. Ethical sensitivity in professional practice: concept analysis.

    Science.gov (United States)

    Weaver, Kathryn; Morse, Janice; Mitcham, Carl

    2008-06-01

    This paper is a report of a concept analysis of ethical sensitivity. Ethical sensitivity enables nurses and other professionals to respond morally to the suffering and vulnerability of those receiving professional care and services. Because of its significance to nursing and other professional practices, ethical sensitivity deserves more focused analysis. A criteria-based method oriented toward pragmatic utility guided the analysis of 200 papers and books from the fields of nursing, medicine, psychology, dentistry, clinical ethics, theology, education, law, accounting or business, journalism, philosophy, political and social sciences and women's studies. This literature spanned 1970 to 2006 and was sorted by discipline and concept dimensions and examined for concept structure and use across various contexts. The analysis was completed in September 2007. Ethical sensitivity in professional practice develops in contexts of uncertainty, client suffering and vulnerability, and through relationships characterized by receptivity, responsiveness and courage on the part of professionals. Essential attributes of ethical sensitivity are identified as moral perception, affectivity and dividing loyalties. Outcomes include integrity preserving decision-making, comfort and well-being, learning and professional transcendence. Our findings promote ethical sensitivity as a type of practical wisdom that pursues client comfort and professional satisfaction with care delivery. The analysis and resulting model offers an inclusive view of ethical sensitivity that addresses some of the limitations with prior conceptualizations.

  4. Analysis of DNA methylation in Arabidopsis thaliana based on methylation-sensitive AFLP markers.

    Science.gov (United States)

    Cervera, M T; Ruiz-García, L; Martínez-Zapater, J M

    2002-12-01

    AFLP analysis using restriction enzyme isoschizomers that differ in their sensitivity to methylation of their recognition sites has been used to analyse the methylation state of anonymous CCGG sequences in Arabidopsis thaliana. The technique was modified to improve the quality of fingerprints and to visualise larger numbers of scorable fragments. Sequencing of amplified fragments indicated that detection was generally associated with non-methylation of the cytosine to which the isoschizomer is sensitive. Comparison of EcoRI/ HpaII and EcoRI/ MspI patterns in different ecotypes revealed that 35-43% of CCGG sites were differentially digested by the isoschizomers. Interestingly, the pattern of digestion among different plants belonging to the same ecotype is highly conserved, with the rate of intra-ecotype methylation-sensitive polymorphisms being less than 1%. However, pairwise comparisons of methylation patterns between samples belonging to different ecotypes revealed differences in up to 34% of the methylation-sensitive polymorphisms. The lack of correlation between inter-ecotype similarity matrices based on methylation-insensitive or methylation-sensitive polymorphisms suggests that whatever the mechanisms regulating methylation may be, they are not related to nucleotide sequence variation.

  5. Risk and sensitivity analysis in relation to external events

    International Nuclear Information System (INIS)

    Alzbutas, R.; Urbonas, R.; Augutis, J.

    2001-01-01

    This paper presents risk and sensitivity analysis of external events impacts on the safe operation in general and in particular the Ignalina Nuclear Power Plant safety systems. Analysis is based on the deterministic and probabilistic assumptions and assessment of the external hazards. The real statistic data are used as well as initial external event simulation. The preliminary screening criteria are applied. The analysis of external event impact on the NPP safe operation, assessment of the event occurrence, sensitivity analysis, and recommendations for safety improvements are performed for investigated external hazards. Such events as aircraft crash, extreme rains and winds, forest fire and flying parts of the turbine are analysed. The models are developed and probabilities are calculated. As an example for sensitivity analysis the model of aircraft impact is presented. The sensitivity analysis takes into account the uncertainty features raised by external event and its model. Even in case when the external events analysis show rather limited danger, the sensitivity analysis can determine the highest influence causes. These possible variations in future can be significant for safety level and risk based decisions. Calculations show that external events cannot significantly influence the safety level of the Ignalina NPP operation, however the events occurrence and propagation can be sufficiently uncertain.(author)

  6. 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.

  7. Multiple predictor smoothing methods for sensitivity analysis: Description of techniques

    International Nuclear Information System (INIS)

    Storlie, Curtis B.; Helton, Jon C.

    2008-01-01

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

  8. Global sensitivity analysis of computer models with functional inputs

    International Nuclear Information System (INIS)

    Iooss, Bertrand; Ribatet, Mathieu

    2009-01-01

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

  9. Frontier Assignment for Sensitivity Analysis of Data Envelopment Analysis

    Science.gov (United States)

    Naito, Akio; Aoki, Shingo; Tsuji, Hiroshi

    To extend the sensitivity analysis capability for DEA (Data Envelopment Analysis), this paper proposes frontier assignment based DEA (FA-DEA). The basic idea of FA-DEA is to allow a decision maker to decide frontier intentionally while the traditional DEA and Super-DEA decide frontier computationally. The features of FA-DEA are as follows: (1) provides chances to exclude extra-influential DMU (Decision Making Unit) and finds extra-ordinal DMU, and (2) includes the function of the traditional DEA and Super-DEA so that it is able to deal with sensitivity analysis more flexibly. Simple numerical study has shown the effectiveness of the proposed FA-DEA and the difference from the traditional DEA.

  10. High order depletion sensitivity analysis

    International Nuclear Information System (INIS)

    Naguib, K.; Adib, M.; Morcos, H.N.

    2002-01-01

    A high order depletion sensitivity method was applied to calculate the sensitivities of build-up of actinides in the irradiated fuel due to cross-section uncertainties. An iteration method based on Taylor series expansion was applied to construct stationary principle, from which all orders of perturbations were calculated. The irradiated EK-10 and MTR-20 fuels at their maximum burn-up of 25% and 65% respectively were considered for sensitivity analysis. The results of calculation show that, in case of EK-10 fuel (low burn-up), the first order sensitivity was found to be enough to perform an accuracy of 1%. While in case of MTR-20 (high burn-up) the fifth order was found to provide 3% accuracy. A computer code SENS was developed to provide the required calculations

  11. Risk Assessment Method for Offshore Structure Based on Global Sensitivity Analysis

    Directory of Open Access Journals (Sweden)

    Zou Tao

    2012-01-01

    Full Text Available Based on global sensitivity analysis (GSA, this paper proposes a new risk assessment method for an offshore structure design. This method quantifies all the significances among random variables and their parameters at first. And by comparing the degree of importance, all minor factors would be negligible. Then, the global uncertainty analysis work would be simplified. Global uncertainty analysis (GUA is an effective way to study the complexity and randomness of natural events. Since field measured data and statistical results often have inevitable errors and uncertainties which lead to inaccurate prediction and analysis, the risk in the design stage of offshore structures caused by uncertainties in environmental loads, sea level, and marine corrosion must be taken into account. In this paper, the multivariate compound extreme value distribution model (MCEVD is applied to predict the extreme sea state of wave, current, and wind. The maximum structural stress and deformation of a Jacket platform are analyzed and compared with different design standards. The calculation result sufficiently demonstrates the new risk assessment method’s rationality and security.

  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. A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

    2014-01-01

    GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. Emergency Load Shedding Strategy Based on Sensitivity Analysis of Relay Operation Margin against Cascading Events

    DEFF Research Database (Denmark)

    Liu, Zhou; Chen, Zhe; Sun, Haishun Sun

    2012-01-01

    the runtime emergent states of related system component. Based on sensitivity analysis between the relay operation margin and power system state variables, an optimal load shedding strategy is applied to adjust the emergent states timely before the unwanted relay operation. Load dynamics is also taken...... into account to compensate load shedding amount calculation. And the multi-agent technology is applied for the whole strategy implementation. A test system is built in real time digital simulator (RTDS) and has demonstrated the effectiveness of the proposed strategy.......In order to prevent long term voltage instability and induced cascading events, a load shedding strategy based on the sensitivity of relay operation margin to load powers is discussed and proposed in this paper. The operation margin of critical impedance backup relay is defined to identify...

  1. 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

  2. A new measure of uncertainty importance based on distributional sensitivity analysis for PSA

    International Nuclear Information System (INIS)

    Han, Seok Jung; Tak, Nam Il; Chun, Moon Hyun

    1996-01-01

    The main objective of the present study is to propose a new measure of uncertainty importance based on distributional sensitivity analysis. The new measure is developed to utilize a metric distance obtained from cumulative distribution functions (cdfs). The measure is evaluated for two cases: one is a cdf given by a known analytical distribution and the other given by an empirical distribution generated by a crude Monte Carlo simulation. To study its applicability, the present measure has been applied to two different cases. The results are compared with those of existing three methods. The present approach is a useful measure of uncertainty importance which is based on cdfs. This method is simple and easy to calculate uncertainty importance without any complex process. On the basis of the results obtained in the present work, the present method is recommended to be used as a tool for the analysis of uncertainty importance

  3. 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

  4. Development of a Sampling-Based Global Sensitivity Analysis Workflow for Multiscale Computational Cancer Models

    Science.gov (United States)

    Wang, Zhihui; Deisboeck, Thomas S.; Cristini, Vittorio

    2014-01-01

    There are two challenges that researchers face when performing global sensitivity analysis (GSA) on multiscale in silico cancer models. The first is increased computational intensity, since a multiscale cancer model generally takes longer to run than does a scale-specific model. The second problem is the lack of a best GSA method that fits all types of models, which implies that multiple methods and their sequence need to be taken into account. In this article, we therefore propose a sampling-based GSA workflow consisting of three phases – pre-analysis, analysis, and post-analysis – by integrating Monte Carlo and resampling methods with the repeated use of analysis of variance (ANOVA); we then exemplify this workflow using a two-dimensional multiscale lung cancer model. By accounting for all parameter rankings produced by multiple GSA methods, a summarized ranking is created at the end of the workflow based on the weighted mean of the rankings for each input parameter. For the cancer model investigated here, this analysis reveals that ERK, a downstream molecule of the EGFR signaling pathway, has the most important impact on regulating both the tumor volume and expansion rate in the algorithm used. PMID:25257020

  5. [Tourism function zoning of Jinyintan Grassland Scenic Area in Qinghai Province based on ecological sensitivity analysis].

    Science.gov (United States)

    Zhong, Lin-sheng; Tang, Cheng-cai; Guo, Hua

    2010-07-01

    Based on the statistical data of natural ecology and social economy in Jinyintan Grassland Scenic Area in Qinghai Province in 2008, an evaluation index system for the ecological sensitivity of this area was established from the aspects of protected area rank, vegetation type, slope, and land use type. The ecological sensitivity of the sub-areas with higher tourism value and ecological function in the area was evaluated, and the tourism function zoning of these sub-areas was made by the technology of GIS and according to the analysis of eco-environmental characteristics and ecological sensitivity of each sensitive sub-area. It was suggested that the Jinyintan Grassland Scenic Area could be divided into three ecological sensitivity sub-areas (high, moderate, and low), three tourism functional sub-areas (restricted development ecotourism, moderate development ecotourism, and mass tourism), and six tourism functional sub-areas (wetland protection, primitive ecological sightseeing, agriculture and pasture tourism, grassland tourism, town tourism, and rural tourism).

  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. Design Optimization Method for Composite Components Based on Moment Reliability-Sensitivity Criteria

    Science.gov (United States)

    Sun, Zhigang; Wang, Changxi; Niu, Xuming; Song, Yingdong

    2017-08-01

    In this paper, a Reliability-Sensitivity Based Design Optimization (RSBDO) methodology for the design of the ceramic matrix composites (CMCs) components has been proposed. A practical and efficient method for reliability analysis and sensitivity analysis of complex components with arbitrary distribution parameters are investigated by using the perturbation method, the respond surface method, the Edgeworth series and the sensitivity analysis approach. The RSBDO methodology is then established by incorporating sensitivity calculation model into RBDO methodology. Finally, the proposed RSBDO methodology is applied to the design of the CMCs components. By comparing with Monte Carlo simulation, the numerical results demonstrate that the proposed methodology provides an accurate, convergent and computationally efficient method for reliability-analysis based finite element modeling engineering practice.

  8. An uncertainty and sensitivity analysis approach for GIS-based multicriteria landslide susceptibility mapping

    Science.gov (United States)

    Feizizadeh, Bakhtiar; Blaschke, Thomas

    2014-01-01

    GIS-based multicriteria decision analysis (MCDA) methods are increasingly being used in landslide susceptibility mapping. However, the uncertainties that are associated with MCDA techniques may significantly impact the results. This may sometimes lead to inaccurate outcomes and undesirable consequences. This article introduces a new GIS-based MCDA approach. We illustrate the consequences of applying different MCDA methods within a decision-making process through uncertainty analysis. Three GIS-MCDA methods in conjunction with Monte Carlo simulation (MCS) and Dempster–Shafer theory are analyzed for landslide susceptibility mapping (LSM) in the Urmia lake basin in Iran, which is highly susceptible to landslide hazards. The methodology comprises three stages. First, the LSM criteria are ranked and a sensitivity analysis is implemented to simulate error propagation based on the MCS. The resulting weights are expressed through probability density functions. Accordingly, within the second stage, three MCDA methods, namely analytical hierarchy process (AHP), weighted linear combination (WLC) and ordered weighted average (OWA), are used to produce the landslide susceptibility maps. In the third stage, accuracy assessments are carried out and the uncertainties of the different results are measured. We compare the accuracies of the three MCDA methods based on (1) the Dempster–Shafer theory and (2) a validation of the results using an inventory of known landslides and their respective coverage based on object-based image analysis of IRS-ID satellite images. The results of this study reveal that through the integration of GIS and MCDA models, it is possible to identify strategies for choosing an appropriate method for LSM. Furthermore, our findings indicate that the integration of MCDA and MCS can significantly improve the accuracy of the results. In LSM, the AHP method performed best, while the OWA reveals better performance in the reliability assessment. The WLC

  9. Derivative based sensitivity analysis of gamma index

    Directory of Open Access Journals (Sweden)

    Biplab Sarkar

    2015-01-01

    Full Text Available Originally developed as a tool for patient-specific quality assurance in advanced treatment delivery methods to compare between measured and calculated dose distributions, the gamma index (γ concept was later extended to compare between any two dose distributions. It takes into effect both the dose difference (DD and distance-to-agreement (DTA measurements in the comparison. Its strength lies in its capability to give a quantitative value for the analysis, unlike other methods. For every point on the reference curve, if there is at least one point in the evaluated curve that satisfies the pass criteria (e.g., δDD = 1%, δDTA = 1 mm, the point is included in the quantitative score as "pass." Gamma analysis does not account for the gradient of the evaluated curve - it looks at only the minimum gamma value, and if it is <1, then the point passes, no matter what the gradient of evaluated curve is. In this work, an attempt has been made to present a derivative-based method for the identification of dose gradient. A mathematically derived reference profile (RP representing the penumbral region of 6 MV 10 cm × 10 cm field was generated from an error function. A general test profile (GTP was created from this RP by introducing 1 mm distance error and 1% dose error at each point. This was considered as the first of the two evaluated curves. By its nature, this curve is a smooth curve and would satisfy the pass criteria for all points in it. The second evaluated profile was generated as a sawtooth test profile (STTP which again would satisfy the pass criteria for every point on the RP. However, being a sawtooth curve, it is not a smooth one and would be obviously poor when compared with the smooth profile. Considering the smooth GTP as an acceptable profile when it passed the gamma pass criteria (1% DD and 1 mm DTA against the RP, the first and second order derivatives of the DDs (δD', δD" between these two curves were derived and used as the

  10. Beyond sensitivity analysis

    DEFF Research Database (Denmark)

    Lund, Henrik; Sorknæs, Peter; Mathiesen, Brian Vad

    2018-01-01

    of electricity, which have been introduced in recent decades. These uncertainties pose a challenge to the design and assessment of future energy strategies and investments, especially in the economic assessment of renewable energy versus business-as-usual scenarios based on fossil fuels. From a methodological...... point of view, the typical way of handling this challenge has been to predict future prices as accurately as possible and then conduct a sensitivity analysis. This paper includes a historical analysis of such predictions, leading to the conclusion that they are almost always wrong. Not only...... are they wrong in their prediction of price levels, but also in the sense that they always seem to predict a smooth growth or decrease. This paper introduces a new method and reports the results of applying it on the case of energy scenarios for Denmark. The method implies the expectation of fluctuating fuel...

  11. Probabilistic and sensitivity analysis of Botlek Bridge structures

    Directory of Open Access Journals (Sweden)

    Králik Juraj

    2017-01-01

    Full Text Available This paper deals with the probabilistic and sensitivity analysis of the largest movable lift bridge of the world. The bridge system consists of six reinforced concrete pylons and two steel decks 4000 tons weight each connected through ropes with counterweights. The paper focuses the probabilistic and sensitivity analysis as the base of dynamic study in design process of the bridge. The results had a high importance for practical application and design of the bridge. The model and resistance uncertainties were taken into account in LHS simulation method.

  12. Application of Stochastic Sensitivity Analysis to Integrated Force Method

    Directory of Open Access Journals (Sweden)

    X. F. Wei

    2012-01-01

    Full Text Available As a new formulation in structural analysis, Integrated Force Method has been successfully applied to many structures for civil, mechanical, and aerospace engineering due to the accurate estimate of forces in computation. Right now, it is being further extended to the probabilistic domain. For the assessment of uncertainty effect in system optimization and identification, the probabilistic sensitivity analysis of IFM was further investigated in this study. A set of stochastic sensitivity analysis formulation of Integrated Force Method was developed using the perturbation method. Numerical examples are presented to illustrate its application. Its efficiency and accuracy were also substantiated with direct Monte Carlo simulations and the reliability-based sensitivity method. The numerical algorithm was shown to be readily adaptable to the existing program since the models of stochastic finite element and stochastic design sensitivity are almost identical.

  13. 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...

  14. Sensor selection of helicopter transmission systems based on physical model and sensitivity analysis

    Directory of Open Access Journals (Sweden)

    Lyu Kehong

    2014-06-01

    Full Text Available In the helicopter transmission systems, it is important to monitor and track the tooth damage evolution using lots of sensors and detection methods. This paper develops a novel approach for sensor selection based on physical model and sensitivity analysis. Firstly, a physical model of tooth damage and mesh stiffness is built. Secondly, some effective condition indicators (CIs are presented, and the optimal CIs set is selected by comparing their test statistics according to Mann–Kendall test. Afterwards, the selected CIs are used to generate a health indicator (HI through sen slop estimator. Then, the sensors are selected according to the monotonic relevance and sensitivity to the damage levels. Finally, the proposed method is verified by the simulation and experimental data. The results show that the approach can provide a guide for health monitoring of helicopter transmission systems, and it is effective to reduce the test cost and improve the system’s reliability.

  15. 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.

  16. Genetic diversity analysis of Jatropha curcas L. (Euphorbiaceae) based on methylation-sensitive amplification polymorphism.

    Science.gov (United States)

    Kanchanaketu, T; Sangduen, N; Toojinda, T; Hongtrakul, V

    2012-04-13

    Genetic analysis of 56 samples of Jatropha curcas L. collected from Thailand and other countries was performed using the methylation-sensitive amplification polymorphism (MSAP) technique. Nine primer combinations were used to generate MSAP fingerprints. When the data were interpreted as amplified fragment length polymorphism (AFLP) markers, 471 markers were scored. All 56 samples were classified into three major groups: γ-irradiated, non-toxic and toxic accessions. Genetic similarity among the samples was extremely high, ranging from 0.95 to 1.00, which indicated very low genetic diversity in this species. The MSAP fingerprint was further analyzed for DNA methylation polymorphisms. The results revealed differences in the DNA methylation level among the samples. However, the samples collected from saline areas and some species hybrids showed specific DNA methylation patterns. AFLP data were used, together with methylation-sensitive AFLP (MS-AFLP) data, to construct a phylogenetic tree, resulting in higher efficiency to distinguish the samples. This combined analysis separated samples previously grouped in the AFLP analysis. This analysis also distinguished some hybrids. Principal component analysis was also performed; the results confirmed the separation in the phylogenetic tree. Some polymorphic bands, involving both nucleotide and DNA methylation polymorphism, that differed between toxic and non-toxic samples were identified, cloned and sequenced. BLAST analysis of these fragments revealed differences in DNA methylation in some known genes and nucleotide polymorphism in chloroplast DNA. We conclude that MSAP is a powerful technique for the study of genetic diversity for organisms that have a narrow genetic base.

  17. Systemization of burnup sensitivity analysis code

    International Nuclear Information System (INIS)

    Tatsumi, Masahiro; Hyoudou, Hideaki

    2004-02-01

    To practical use of fact reactors, it is a very important subject to improve prediction accuracy for neutronic properties in LMFBR cores from the viewpoints of improvements on plant efficiency with rationally high performance cores and that on reliability and safety margins. A distinct improvement on accuracy in nuclear core design has been accomplished by development of adjusted nuclear library using the cross-section adjustment method, in which the results of critical experiments of JUPITER and so on are reflected. In the design of large LMFBR cores, however, it is important to accurately estimate not only neutronic characteristics, for example, reaction rate distribution and control rod worth but also burnup characteristics, for example, burnup reactivity loss, breeding ratio and so on. For this purpose, it is desired to improve prediction accuracy of burnup characteristics using the data widely obtained in actual core such as the experimental fast reactor core 'JOYO'. The analysis of burnup characteristics is needed to effectively use burnup characteristics data in the actual cores based on the cross-section adjustment method. So far, development of a analysis code for burnup sensitivity, SAGEP-BURN, has been done and confirmed its effectiveness. However, there is a problem that analysis sequence become inefficient because of a big burden to user due to complexity of the theory of burnup sensitivity and limitation of the system. It is also desired to rearrange the system for future revision since it is becoming difficult to implement new functionalities in the existing large system. It is not sufficient to unify each computational component for some reasons; computational sequence may be changed for each item being analyzed or for purpose such as interpretation of physical meaning. Therefore it is needed to systemize the current code for burnup sensitivity analysis with component blocks of functionality that can be divided or constructed on occasion. For this

  18. 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.

  19. 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...

  20. Uncertainty and sensitivity analysis of electro-mechanical impedance based SHM system

    International Nuclear Information System (INIS)

    Rosiek, M; Martowicz, A; Uhl, T

    2010-01-01

    The paper deals with the application of uncertainty and sensitivity analysis performed for FE simulations for electro-mechanical impedance based SHM system. The measurement of electro-mechanical impedance allows to follow changes of mechanical properties of monitored construction. Therefore it can be effectively applied to conclude about presence of damage. Coupled FE simulations have been carried out for simultaneous consideration of both structural dynamics and piezoelectric properties of a simple beam with bonded transducer. Several indexes have been used to assess the damage growth. In the paper the results obtained with both deterministic and stochastic simulations are shown and discussed. First, the relationship between size of introduced damage and its indexes has been studied. Second, ranges of variation of selected model properties have been assumed to find relationships between them and damage indexes. The most influential parameters have been found. Finally, the overall propagation of considered uncertainty has been assessed and related histograms plotted to discuss effectiveness and robustness of tested damage indexes based on the measurement of electro-mechanical impedance.

  1. Variance decomposition-based sensitivity analysis via neural networks

    International Nuclear Information System (INIS)

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

    2003-01-01

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

  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. 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.

  4. 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)

  5. 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

  6. Sensitivity analysis and calibration of a dynamic physically based slope stability model

    Science.gov (United States)

    Zieher, Thomas; Rutzinger, Martin; Schneider-Muntau, Barbara; Perzl, Frank; Leidinger, David; Formayer, Herbert; Geitner, Clemens

    2017-06-01

    Physically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of parameter values, (ii) shortcomings of the selected model, (iii) uncertainties of laboratory tests and field measurements or (iv) parameters that cannot be derived experimentally or measured in the field (e.g. calibration constants). While systematic parameter calibration is a common task in hydrological modelling, this is rarely done using physically based slope stability models. In the present study a dynamic, physically based, coupled hydrological-geomechanical slope stability model is calibrated based on a limited number of laboratory tests and a detailed multitemporal shallow landslide inventory covering two landslide-triggering rainfall events in the Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified based on a local one-at-a-time sensitivity analysis. These parameters (hydraulic conductivity, specific storage, angle of internal friction for effective stress, cohesion for effective stress) are systematically sampled and calibrated for a landslide-triggering rainfall event in August 2005. The identified model ensemble, including 25 behavioural model runs with the highest portion of correctly predicted landslides and non-landslides, is then validated with another landslide-triggering rainfall event in May 1999. The identified model ensemble correctly predicts the location and the supposed triggering timing of 73.0 % of the observed landslides triggered in August 2005 and 91.5 % of the observed landslides triggered in May 1999. Results of the model ensemble driven with raised precipitation input reveal a slight increase in areas potentially affected by slope failure. At the same time, the peak run-off increases more markedly, suggesting that

  7. 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

  8. 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

  9. 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.

  10. Design of Diaphragm Based MEMS Pressure Sensor with Sensitivity Analysis for Environmental Applications

    Directory of Open Access Journals (Sweden)

    A. Nallathambi

    2015-05-01

    Full Text Available In this paper Micro-electromechanical System (MEMS diaphragm based pressure sensor for environmental applications is discussed. The main focus of this paper is to design, simulate and analyze the sensitivity of MEMS based diaphragm using different structures to measure the low and high pressure values. The simulation is done through the finite element tool and specifications related the maximum convinced stress; deflection and sensitivity of the diaphragms have been analyzed using the software INTELLISUITE 8.7v. The change in pressure is to bending of the diaphragm that modifies the measured displacement between the substrate and the diaphragm. This change in displacement gives the measure of the pressure in that environment. The design of these studies can be used to improve the sensitivity of these devices. Here the diaphragm based pressure sensor produced better displacement, sensitivity and stress output responses are obtained from the square diaphragm. The pressure range from 0.6 MPa to 25 MPa and its maximum displacement is accordingly 59 mm over a pressure range of 0 to 2 MPa. Its sensitivity is therefore 2.35 [10E-12/Pa].

  11. 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...

  12. Sensitivity Analysis of the Critical Speed in Railway Vehicle Dynamics

    DEFF Research Database (Denmark)

    Bigoni, Daniele; True, Hans; Engsig-Karup, Allan Peter

    2014-01-01

    We present an approach to global sensitivity analysis aiming at the reduction of its computational cost without compromising the results. The method is based on sampling methods, cubature rules, High-Dimensional Model Representation and Total Sensitivity Indices. The approach has a general applic...

  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. 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.

  15. Systemization of burnup sensitivity analysis code. 2

    International Nuclear Information System (INIS)

    Tatsumi, Masahiro; Hyoudou, Hideaki

    2005-02-01

    Towards the practical use of fast reactors, it is a very important subject to improve prediction accuracy for neutronic properties in LMFBR cores from the viewpoint of improvements on plant efficiency with rationally high performance cores and that on reliability and safety margins. A distinct improvement on accuracy in nuclear core design has been accomplished by the development of adjusted nuclear library using the cross-section adjustment method, in which the results of criticality experiments of JUPITER and so on are reflected. In the design of large LMFBR cores, however, it is important to accurately estimate not only neutronic characteristics, for example, reaction rate distribution and control rod worth but also burnup characteristics, for example, burnup reactivity loss, breeding ratio and so on. For this purpose, it is desired to improve prediction accuracy of burnup characteristics using the data widely obtained in actual core such as the experimental fast reactor 'JOYO'. The analysis of burnup characteristics is needed to effectively use burnup characteristics data in the actual cores based on the cross-section adjustment method. So far, a burnup sensitivity analysis code, SAGEP-BURN, has been developed and confirmed its effectiveness. However, there is a problem that analysis sequence become inefficient because of a big burden to users due to complexity of the theory of burnup sensitivity and limitation of the system. It is also desired to rearrange the system for future revision since it is becoming difficult to implement new functions in the existing large system. It is not sufficient to unify each computational component for the following reasons; the computational sequence may be changed for each item being analyzed or for purpose such as interpretation of physical meaning. Therefore, it is needed to systemize the current code for burnup sensitivity analysis with component blocks of functionality that can be divided or constructed on occasion. For

  16. 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

  17. 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.

  18. 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.

  19. Sensitivity Analysis Based SVM Application on Automatic Incident Detection of Rural Road in China

    Directory of Open Access Journals (Sweden)

    Xingliang Liu

    2018-01-01

    Full Text Available Traditional automatic incident detection methods such as artificial neural networks, backpropagation neural network, and Markov chains are not suitable for addressing the incident detection problem of rural roads in China which have a relatively high accident rate and a low reaction speed caused by the character of small traffic volume. This study applies the support vector machine (SVM and parameter sensitivity analysis methods to build an accident detection algorithm in a rural road condition, based on real-time data collected in a field experiment. The sensitivity of four parameters (speed, front distance, vehicle group time interval, and free driving ratio is analyzed, and the data sets of two parameters with a significant sensitivity are chosen to form the traffic state feature vector. The SVM and k-fold cross validation (K-CV methods are used to build the accident detection algorithm, which shows an excellent performance in detection accuracy (98.15% of the training data set and 87.5% of the testing data set. Therefore, the problem of low incident reaction speed of rural roads in China could be solved to some extent.

  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. 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

  2. The Volatility of Data Space: Topology Oriented Sensitivity Analysis

    Science.gov (United States)

    Du, Jing; Ligmann-Zielinska, Arika

    2015-01-01

    Despite the difference among specific methods, existing Sensitivity Analysis (SA) technologies are all value-based, that is, the uncertainties in the model input and output are quantified as changes of values. This paradigm provides only limited insight into the nature of models and the modeled systems. In addition to the value of data, a potentially richer information about the model lies in the topological difference between pre-model data space and post-model data space. This paper introduces an innovative SA method called Topology Oriented Sensitivity Analysis, which defines sensitivity as the volatility of data space. It extends SA into a deeper level that lies in the topology of data. PMID:26368929

  3. Rethinking Sensitivity Analysis of Nuclear Simulations with Topology

    Energy Technology Data Exchange (ETDEWEB)

    Dan Maljovec; Bei Wang; Paul Rosen; Andrea Alfonsi; Giovanni Pastore; Cristian Rabiti; Valerio Pascucci

    2016-01-01

    In nuclear engineering, understanding the safety margins of the nuclear reactor via simulations is arguably of paramount importance in predicting and preventing nuclear accidents. It is therefore crucial to perform sensitivity analysis to understand how changes in the model inputs affect the outputs. Modern nuclear simulation tools rely on numerical representations of the sensitivity information -- inherently lacking in visual encodings -- offering limited effectiveness in communicating and exploring the generated data. In this paper, we design a framework for sensitivity analysis and visualization of multidimensional nuclear simulation data using partition-based, topology-inspired regression models and report on its efficacy. We rely on the established Morse-Smale regression technique, which allows us to partition the domain into monotonic regions where easily interpretable linear models can be used to assess the influence of inputs on the output variability. The underlying computation is augmented with an intuitive and interactive visual design to effectively communicate sensitivity information to the nuclear scientists. Our framework is being deployed into the multi-purpose probabilistic risk assessment and uncertainty quantification framework RAVEN (Reactor Analysis and Virtual Control Environment). We evaluate our framework using an simulation dataset studying nuclear fuel performance.

  4. 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.

  5. 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.

  6. 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.

  7. Sensitivity theory for reactor burnup analysis based on depletion perturbation theory

    International Nuclear Information System (INIS)

    Yang, Wonsik.

    1989-01-01

    The large computational effort involved in the design and analysis of advanced reactor configurations motivated the development of Depletion Perturbation Theory (DPT) for general fuel cycle analysis. The work here focused on two important advances in the current methods. First, the adjoint equations were developed for using the efficient linear flux approximation to decouple the neutron/nuclide field equations. And second, DPT was extended to the constrained equilibrium cycle which is important for the consistent comparison and evaluation of alternative reactor designs. Practical strategies were formulated for solving the resulting adjoint equations and a computer code was developed for practical applications. In all cases analyzed, the sensitivity coefficients generated by DPT were in excellent agreement with the results of exact calculations. The work here indicates that for a given core response, the sensitivity coefficients to all input parameters can be computed by DPT with a computational effort similar to a single forward depletion calculation

  8. Continuous integration congestion cost allocation based on sensitivity

    International Nuclear Information System (INIS)

    Wu, Z.Q.; Wang, Y.N.

    2004-01-01

    Congestion cost allocation is a very important topic in congestion management. Allocation methods based on the Aumann-Shapley value use the discrete numerical integration method, which needs to solve the incremented OPF solution many times, and as such it is not suitable for practical application to large-scale systems. The optimal solution and its sensitivity change tendency during congestion removal using a DC optimal power flow (OPF) process is analysed. A simple continuous integration method based on the sensitivity is proposed for the congestion cost allocation. The proposed sensitivity analysis method needs a smaller computation time than the method based on using the quadratic method and inner point iteration. The proposed congestion cost allocation method uses a continuous integration method rather than discrete numerical integration. The method does not need to solve the incremented OPF solutions; which allows it use in large-scale systems. The method can also be used for AC OPF congestion management. (author)

  9. Status of XSUSA for sampling based nuclear data uncertainty and sensitivity analysis

    International Nuclear Information System (INIS)

    Zwermann, W.; Gallner, L.; Klein, M.; Krzydacz-Hausmann; Pasichnyk, I.; Pautz, A.; Velkov, K.

    2013-01-01

    In the present contribution, an overview of the sampling based XSUSA method for sensitivity and uncertainty analysis with respect to nuclear data is given. The focus is on recent developments and applications of XSUSA. These applications include calculations for critical assemblies, fuel assembly depletion calculations, and steady state as well as transient reactor core calculations. The analyses are partially performed in the framework of international benchmark working groups (UACSA - Uncertainty Analyses for Criticality Safety Assessment, UAM - Uncertainty Analysis in Modelling). It is demonstrated that particularly for full-scale reactor calculations the influence of the nuclear data uncertainties on the results can be substantial. For instance, for the radial fission rate distributions of mixed UO 2 /MOX light water reactor cores, the 2σ uncertainties in the core centre and periphery can reach values exceeding 10%. For a fast transient, the resulting time behaviour of the reactor power was covered by a wide uncertainty band. Overall, the results confirm the necessity of adding systematic uncertainty analyses to best-estimate reactor calculations. (authors)

  10. Palladium configuration dependence of hydrogen detection sensitivity based on graphene FET for breath analysis

    Science.gov (United States)

    Sakamoto, Yuri; Uemura, Kohei; Ikuta, Takashi; Maehashi, Kenzo

    2018-04-01

    We have succeeded in fabricating a hydrogen gas sensor based on palladium-modified graphene field-effect transistors (FETs). The negative-voltage shift in the transfer characteristics was observed with exposure to hydrogen gas, which was explained by the change in work function. The hydrogen concentration dependence of the voltage shift was investigated using graphene FETs with palladium deposited by three different evaporation processes. The results indicate that the hydrogen detection sensitivity of the palladium-modified graphene FETs is strongly dependent on the palladium configuration. Therefore, the palladium-modified graphene FET is a candidate for breath analysis.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. Sensitivity analysis for improving nanomechanical photonic transducers biosensors

    International Nuclear Information System (INIS)

    Fariña, D; Álvarez, M; Márquez, S; Lechuga, L M; Dominguez, C

    2015-01-01

    The achievement of high sensitivity and highly integrated transducers is one of the main challenges in the development of high-throughput biosensors. The aim of this study is to improve the final sensitivity of an opto-mechanical device to be used as a reliable biosensor. We report the analysis of the mechanical and optical properties of optical waveguide microcantilever transducers, and their dependency on device design and dimensions. The selected layout (geometry) based on two butt-coupled misaligned waveguides displays better sensitivities than an aligned one. With this configuration, we find that an optimal microcantilever thickness range between 150 nm and 400 nm would increase both microcantilever bending during the biorecognition process and increase optical sensitivity to 4.8   ×   10 −2  nm −1 , an order of magnitude higher than other similar opto-mechanical devices. Moreover, the analysis shows that a single mode behaviour of the propagating radiation is required to avoid modal interference that could misinterpret the readout signal. (paper)

  16. Global sensitivity analysis of Alkali-Surfactant-Polymer enhanced oil recovery processes

    Energy Technology Data Exchange (ETDEWEB)

    Carrero, Enrique; Queipo, Nestor V.; Pintos, Salvador; Zerpa, Luis E. [Applied Computing Institute, Faculty of Engineering, University of Zulia, Zulia (Venezuela)

    2007-08-15

    After conventional waterflooding processes the residual oil in the reservoir remains as a discontinuous phase in the form of oil drops trapped by capillary forces and is likely to be around 70% of the original oil in place (OOIP). The EOR method so-called Alkaline-Surfactant-Polymer (ASP) flooding has been proved to be effective in reducing the oil residual saturation in laboratory experiments and field projects through reduction of interfacial tension and mobility ratio between oil and water phases. A critical step for the optimal design and control of ASP recovery processes is to find the relative contributions of design variables such as, slug size and chemical concentrations, in the variability of given performance measures (e.g., net present value, cumulative oil recovery), considering a heterogeneous and multiphase petroleum reservoir (sensitivity analysis). Previously reported works using reservoir numerical simulation have been limited to local sensitivity analyses because a global sensitivity analysis may require hundreds or even thousands of computationally expensive evaluations (field scale numerical simulations). To overcome this issue, a surrogate-based approach is suggested. Surrogate-based analysis/optimization makes reference to the idea of constructing an alternative fast model (surrogate) from numerical simulation data and using it for analysis/optimization purposes. This paper presents an efficient global sensitivity approach based on Sobol's method and multiple surrogates (i.e., Polynomial Regression, Kriging, Radial Base Functions and a Weighed Adaptive Model), with the multiple surrogates used to address the uncertainty in the analysis derived from plausible alternative surrogate-modeling schemes. The proposed approach was evaluated in the context of the global sensitivity analysis of a field scale Alkali-Surfactant-Polymer flooding process. The design variables and the performance measure in the ASP process were selected as slug size

  17. Sensitivity analysis of the nuclear data for MYRRHA reactor modelling

    International Nuclear Information System (INIS)

    Stankovskiy, Alexey; Van den Eynde, Gert; Cabellos, Oscar; Diez, Carlos J.; Schillebeeckx, Peter; Heyse, Jan

    2014-01-01

    A global sensitivity analysis of effective neutron multiplication factor k eff to the change of nuclear data library revealed that JEFF-3.2T2 neutron-induced evaluated data library produces closer results to ENDF/B-VII.1 than does JEFF-3.1.2. The analysis of contributions of individual evaluations into k eff sensitivity allowed establishing the priority list of nuclides for which uncertainties on nuclear data must be improved. Detailed sensitivity analysis has been performed for two nuclides from this list, 56 Fe and 238 Pu. The analysis was based on a detailed survey of the evaluations and experimental data. To track the origin of the differences in the evaluations and their impact on k eff , the reaction cross-sections and multiplicities in one evaluation have been substituted by the corresponding data from other evaluations. (authors)

  18. 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.

  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. 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.

  1. 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.

  2. Global sensitivity analysis using polynomial chaos expansions

    International Nuclear Information System (INIS)

    Sudret, Bruno

    2008-01-01

    Global sensitivity analysis (SA) aims at quantifying the respective effects of input random variables (or combinations thereof) onto the variance of the response of a physical or mathematical model. Among the abundant literature on sensitivity measures, the Sobol' indices have received much attention since they provide accurate information for most models. The paper introduces generalized polynomial chaos expansions (PCE) to build surrogate models that allow one to compute the Sobol' indices analytically as a post-processing of the PCE coefficients. Thus the computational cost of the sensitivity indices practically reduces to that of estimating the PCE coefficients. An original non intrusive regression-based approach is proposed, together with an experimental design of minimal size. Various application examples illustrate the approach, both from the field of global SA (i.e. well-known benchmark problems) and from the field of stochastic mechanics. The proposed method gives accurate results for various examples that involve up to eight input random variables, at a computational cost which is 2-3 orders of magnitude smaller than the traditional Monte Carlo-based evaluation of the Sobol' indices

  3. Global sensitivity analysis using polynomial chaos expansions

    Energy Technology Data Exchange (ETDEWEB)

    Sudret, Bruno [Electricite de France, R and D Division, Site des Renardieres, F 77818 Moret-sur-Loing Cedex (France)], E-mail: bruno.sudret@edf.fr

    2008-07-15

    Global sensitivity analysis (SA) aims at quantifying the respective effects of input random variables (or combinations thereof) onto the variance of the response of a physical or mathematical model. Among the abundant literature on sensitivity measures, the Sobol' indices have received much attention since they provide accurate information for most models. The paper introduces generalized polynomial chaos expansions (PCE) to build surrogate models that allow one to compute the Sobol' indices analytically as a post-processing of the PCE coefficients. Thus the computational cost of the sensitivity indices practically reduces to that of estimating the PCE coefficients. An original non intrusive regression-based approach is proposed, together with an experimental design of minimal size. Various application examples illustrate the approach, both from the field of global SA (i.e. well-known benchmark problems) and from the field of stochastic mechanics. The proposed method gives accurate results for various examples that involve up to eight input random variables, at a computational cost which is 2-3 orders of magnitude smaller than the traditional Monte Carlo-based evaluation of the Sobol' indices.

  4. 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

  5. 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.

  6. Automatic differentiation for design sensitivity analysis of structural systems using multiple processors

    Science.gov (United States)

    Nguyen, Duc T.; Storaasli, Olaf O.; Qin, Jiangning; Qamar, Ramzi

    1994-01-01

    An automatic differentiation tool (ADIFOR) is incorporated into a finite element based structural analysis program for shape and non-shape design sensitivity analysis of structural systems. The entire analysis and sensitivity procedures are parallelized and vectorized for high performance computation. Small scale examples to verify the accuracy of the proposed program and a medium scale example to demonstrate the parallel vector performance on multiple CRAY C90 processors are included.

  7. The identification of model effective dimensions using global sensitivity analysis

    International Nuclear Information System (INIS)

    Kucherenko, Sergei; Feil, Balazs; Shah, Nilay; Mauntz, Wolfgang

    2011-01-01

    It is shown that the effective dimensions can be estimated at reasonable computational costs using variance based global sensitivity analysis. Namely, the effective dimension in the truncation sense can be found by using the Sobol' sensitivity indices for subsets of variables. The effective dimension in the superposition sense can be estimated by using the first order effects and the total Sobol' sensitivity indices. The classification of some important classes of integrable functions based on their effective dimension is proposed. It is shown that it can be used for the prediction of the QMC efficiency. Results of numerical tests verify the prediction of the developed techniques.

  8. The identification of model effective dimensions using global sensitivity analysis

    Energy Technology Data Exchange (ETDEWEB)

    Kucherenko, Sergei, E-mail: s.kucherenko@ic.ac.u [CPSE, Imperial College London, South Kensington Campus, London SW7 2AZ (United Kingdom); Feil, Balazs [Department of Process Engineering, University of Pannonia, Veszprem (Hungary); Shah, Nilay [CPSE, Imperial College London, South Kensington Campus, London SW7 2AZ (United Kingdom); Mauntz, Wolfgang [Lehrstuhl fuer Anlagensteuerungstechnik, Fachbereich Chemietechnik, Universitaet Dortmund (Germany)

    2011-04-15

    It is shown that the effective dimensions can be estimated at reasonable computational costs using variance based global sensitivity analysis. Namely, the effective dimension in the truncation sense can be found by using the Sobol' sensitivity indices for subsets of variables. The effective dimension in the superposition sense can be estimated by using the first order effects and the total Sobol' sensitivity indices. The classification of some important classes of integrable functions based on their effective dimension is proposed. It is shown that it can be used for the prediction of the QMC efficiency. Results of numerical tests verify the prediction of the developed techniques.

  9. 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...

  10. 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

  11. Improved Extreme Learning Machine based on the Sensitivity Analysis

    Science.gov (United States)

    Cui, Licheng; Zhai, Huawei; Wang, Benchao; Qu, Zengtang

    2018-03-01

    Extreme learning machine and its improved ones is weak in some points, such as computing complex, learning error and so on. After deeply analyzing, referencing the importance of hidden nodes in SVM, an novel analyzing method of the sensitivity is proposed which meets people’s cognitive habits. Based on these, an improved ELM is proposed, it could remove hidden nodes before meeting the learning error, and it can efficiently manage the number of hidden nodes, so as to improve the its performance. After comparing tests, it is better in learning time, accuracy and so on.

  12. 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.

  13. Sensitivity Analysis of Weather Variables on Offsite Consequence Analysis Tools in South Korea and the United States

    Directory of Open Access Journals (Sweden)

    Min-Uk Kim

    2018-05-01

    Full Text Available We studied sensitive weather variables for consequence analysis, in the case of chemical leaks on the user side of offsite consequence analysis (OCA tools. We used OCA tools Korea Offsite Risk Assessment (KORA and Areal Location of Hazardous Atmospheres (ALOHA in South Korea and the United States, respectively. The chemicals used for this analysis were 28% ammonia (NH3, 35% hydrogen chloride (HCl, 50% hydrofluoric acid (HF, and 69% nitric acid (HNO3. The accident scenarios were based on leakage accidents in storage tanks. The weather variables were air temperature, wind speed, humidity, and atmospheric stability. Sensitivity analysis was performed using the Statistical Package for the Social Sciences (SPSS program for dummy regression analysis. Sensitivity analysis showed that impact distance was not sensitive to humidity. Impact distance was most sensitive to atmospheric stability, and was also more sensitive to air temperature than wind speed, according to both the KORA and ALOHA tools. Moreover, the weather variables were more sensitive in rural conditions than in urban conditions, with the ALOHA tool being more influenced by weather variables than the KORA tool. Therefore, if using the ALOHA tool instead of the KORA tool in rural conditions, users should be careful not to cause any differences in impact distance due to input errors of weather variables, with the most sensitive one being atmospheric stability.

  14. Sensitivity Analysis of Weather Variables on Offsite Consequence Analysis Tools in South Korea and the United States.

    Science.gov (United States)

    Kim, Min-Uk; Moon, Kyong Whan; Sohn, Jong-Ryeul; Byeon, Sang-Hoon

    2018-05-18

    We studied sensitive weather variables for consequence analysis, in the case of chemical leaks on the user side of offsite consequence analysis (OCA) tools. We used OCA tools Korea Offsite Risk Assessment (KORA) and Areal Location of Hazardous Atmospheres (ALOHA) in South Korea and the United States, respectively. The chemicals used for this analysis were 28% ammonia (NH₃), 35% hydrogen chloride (HCl), 50% hydrofluoric acid (HF), and 69% nitric acid (HNO₃). The accident scenarios were based on leakage accidents in storage tanks. The weather variables were air temperature, wind speed, humidity, and atmospheric stability. Sensitivity analysis was performed using the Statistical Package for the Social Sciences (SPSS) program for dummy regression analysis. Sensitivity analysis showed that impact distance was not sensitive to humidity. Impact distance was most sensitive to atmospheric stability, and was also more sensitive to air temperature than wind speed, according to both the KORA and ALOHA tools. Moreover, the weather variables were more sensitive in rural conditions than in urban conditions, with the ALOHA tool being more influenced by weather variables than the KORA tool. Therefore, if using the ALOHA tool instead of the KORA tool in rural conditions, users should be careful not to cause any differences in impact distance due to input errors of weather variables, with the most sensitive one being atmospheric stability.

  15. Global sensitivity analysis for models with spatially dependent outputs

    International Nuclear Information System (INIS)

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

    2011-01-01

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

  16. USE OF SENSITIVITY ANALYSIS ON A PHYSIOLOGICALLY-BASED PHARMACOKINETIC (PBPK) MODEL FOR CHLOROFORM IN RATS TO DETERMINE AGE-RELATED TOXICITY

    Science.gov (United States)

    USE OF SENSITIVITY ANALYSIS ON A PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODEL FOR CHLOROFORM IN RATS TO DETERMINE AGE-RELATED TOXICITY.CR Eklund, MV Evans, and JE Simmons. US EPA, ORD, NHEERL, ETD,PKB, Research Triangle Park, NC. Chloroform (CHCl3) is a disinfec...

  17. 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.

  18. Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity at high sensitivity levels (Conference Presentation)

    Science.gov (United States)

    Zhao, Jianhua; Zeng, Haishan; Kalia, Sunil; Lui, Harvey

    2017-02-01

    Background: Raman spectroscopy is a non-invasive optical technique which can measure molecular vibrational modes within tissue. A large-scale clinical study (n = 518) has demonstrated that real-time Raman spectroscopy could distinguish malignant from benign skin lesions with good diagnostic accuracy; this was validated by a follow-up independent study (n = 127). Objective: Most of the previous diagnostic algorithms have typically been based on analyzing the full band of the Raman spectra, either in the fingerprint or high wavenumber regions. Our objective in this presentation is to explore wavenumber selection based analysis in Raman spectroscopy for skin cancer diagnosis. Methods: A wavenumber selection algorithm was implemented using variably-sized wavenumber windows, which were determined by the correlation coefficient between wavenumbers. Wavenumber windows were chosen based on accumulated frequency from leave-one-out cross-validated stepwise regression or least and shrinkage selection operator (LASSO). The diagnostic algorithms were then generated from the selected wavenumber windows using multivariate statistical analyses, including principal component and general discriminant analysis (PC-GDA) and partial least squares (PLS). A total cohort of 645 confirmed lesions from 573 patients encompassing skin cancers, precancers and benign skin lesions were included. Lesion measurements were divided into training cohort (n = 518) and testing cohort (n = 127) according to the measurement time. Result: The area under the receiver operating characteristic curve (ROC) improved from 0.861-0.891 to 0.891-0.911 and the diagnostic specificity for sensitivity levels of 0.99-0.90 increased respectively from 0.17-0.65 to 0.20-0.75 by selecting specific wavenumber windows for analysis. Conclusion: Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity at high sensitivity levels.

  19. Restructuring of burnup sensitivity analysis code system by using an object-oriented design approach

    International Nuclear Information System (INIS)

    Kenji, Yokoyama; Makoto, Ishikawa; Masahiro, Tatsumi; Hideaki, Hyoudou

    2005-01-01

    A new burnup sensitivity analysis code system was developed with help from the object-oriented technique and written in Python language. It was confirmed that they are powerful to support complex numerical calculation procedure such as reactor burnup sensitivity analysis. The new burnup sensitivity analysis code system PSAGEP was restructured from a complicated old code system and reborn as a user-friendly code system which can calculate the sensitivity coefficients of the nuclear characteristics considering multicycle burnup effect based on the generalized perturbation theory (GPT). A new encapsulation framework for conventional codes written in Fortran was developed. This framework supported to restructure the software architecture of the old code system by hiding implementation details and allowed users of the new code system to easily calculate the burnup sensitivity coefficients. The framework can be applied to the other development projects since it is carefully designed to be independent from PSAGEP. Numerical results of the burnup sensitivity coefficient of a typical fast breeder reactor were given with components based on GPT and the multicycle burnup effects on the sensitivity coefficient were discussed. (authors)

  20. Density-based global sensitivity analysis of sheet-flow travel time: Kinematic wave-based formulations

    Science.gov (United States)

    Hosseini, Seiyed Mossa; Ataie-Ashtiani, Behzad; Simmons, Craig T.

    2018-04-01

    Despite advancements in developing physics-based formulations to estimate the sheet-flow travel time (tSHF), the quantification of the relative impacts of influential parameters on tSHF has not previously been considered. In this study, a brief review of the physics-based formulations to estimate tSHF including kinematic wave (K-W) theory in combination with Manning's roughness (K-M) and with Darcy-Weisbach friction formula (K-D) over single and multiple planes is provided. Then, the relative significance of input parameters to the developed approaches is quantified by a density-based global sensitivity analysis (GSA). The performance of K-M considering zero-upstream and uniform flow depth (so-called K-M1 and K-M2), and K-D formulae to estimate the tSHF over single plane surface were assessed using several sets of experimental data collected from the previous studies. The compatibility of the developed models to estimate tSHF over multiple planes considering temporal rainfall distributions of Natural Resources Conservation Service, NRCS (I, Ia, II, and III) are scrutinized by several real-world examples. The results obtained demonstrated that the main controlling parameters of tSHF through K-D and K-M formulae are the length of surface plane (mean sensitivity index T̂i = 0.72) and flow resistance (mean T̂i = 0.52), respectively. Conversely, the flow temperature and initial abstraction ratio of rainfall have the lowest influence on tSHF (mean T̂i is 0.11 and 0.12, respectively). The significant role of the flow regime on the estimation of tSHF over a single and a cascade of planes are also demonstrated. Results reveal that the K-D formulation provides more precise tSHF over the single plane surface with an average percentage of error, APE equal to 9.23% (the APE for K-M1 and K-M2 formulae were 13.8%, and 36.33%, respectively). The superiority of Manning-jointed formulae in estimation of tSHF is due to the incorporation of effects from different flow regimes as

  1. Sensitivity Analysis to Control the Far-Wake Unsteadiness Behind Turbines

    Directory of Open Access Journals (Sweden)

    Esteban Ferrer

    2017-10-01

    Full Text Available We explore the stability of wakes arising from 2D flow actuators based on linear momentum actuator disc theory. We use stability and sensitivity analysis (using adjoints to show that the wake stability is controlled by the Reynolds number and the thrust force (or flow resistance applied through the turbine. First, we report that decreasing the thrust force has a comparable stabilising effect to a decrease in Reynolds numbers (based on the turbine diameter. Second, a discrete sensitivity analysis identifies two regions for suitable placement of flow control forcing, one close to the turbines and one far downstream. Third, we show that adding a localised control force, in the regions identified by the sensitivity analysis, stabilises the wake. Particularly, locating the control forcing close to the turbines results in an enhanced stabilisation such that the wake remains steady for significantly higher Reynolds numbers or turbine thrusts. The analysis of the controlled flow fields confirms that modifying the velocity gradient close to the turbine is more efficient to stabilise the wake than controlling the wake far downstream. The analysis is performed for the first flow bifurcation (at low Reynolds numbers which serves as a foundation of the stabilization technique but the control strategy is tested at higher Reynolds numbers in the final section of the paper, showing enhanced stability for a turbulent flow case.

  2. Semianalytic Design Sensitivity Analysis of Nonlinear Structures With a Commercial Finite Element Package

    International Nuclear Information System (INIS)

    Lee, Tae Hee; Yoo, Jung Hun; Choi, Hyeong Cheol

    2002-01-01

    A finite element package is often used as a daily design tool for engineering designers in order to analyze and improve the design. The finite element analysis can provide the responses of a system for given design variables. Although finite element analysis can quite well provide the structural behaviors for given design variables, it cannot provide enough information to improve the design such as design sensitivity coefficients. Design sensitivity analysis is an essential step to predict the change in responses due to a change in design variables and to optimize a system with the aid of the gradient-based optimization techniques. To develop a numerical method of design sensitivity analysis, analytical derivatives that are based on analytical differentiation of the continuous or discrete finite element equations are effective but analytical derivatives are difficult because of the lack of internal information of the commercial finite element package such as shape functions. Therefore, design sensitivity analysis outside of the finite element package is necessary for practical application in an industrial setting. In this paper, the semi-analytic method for design sensitivity analysis is used for the development of the design sensitivity module outside of a commercial finite element package of ANSYS. The direct differentiation method is employed to compute the design derivatives of the response and the pseudo-load for design sensitivity analysis is effectively evaluated by using the design variation of the related internal nodal forces. Especially, we suggest an effective method for stress and nonlinear design sensitivity analyses that is independent of the commercial finite element package is also discussed. Numerical examples are illustrated to show the accuracy and efficiency of the developed method and to provide insights for implementation of the suggested method into other commercial finite element packages

  3. 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

  4. 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.

  5. TEMAC, Top Event Sensitivity Analysis

    International Nuclear Information System (INIS)

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

    1988-01-01

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

  6. Ecosystem-based management of a Mediterranean urban wastewater system: a sensitivity analysis of the operational degrees of freedom.

    Science.gov (United States)

    Corominas, Lluís; Neumann, Marc B

    2014-10-01

    Urban wastewater systems discharge organic matter, nutrients and other pollutants (including toxic substances) to receiving waters, even after removing more than 90% of incoming pollutants from human activities. Understanding their interactions with the receiving water bodies is essential for the implementation of ecosystem-based management strategies. Using mathematical modeling and sensitivity analysis we quantified how 19 operational variables of an urban wastewater system affect river water quality. The mathematical model of the Congost system (in the Besòs catchment, Spain) characterizes the dynamic interactions between sewers, storage tanks, wastewater treatment plants and the river. The sensitivity analysis shows that the use of storage tanks for peak shaving and the use of a connection between two neighboring wastewater treatment plants are the most important factors influencing river water quality. We study how the sensitivity of the water quality variables towards changes in the operational variables varies along the river due to discharge locations and river self-purification processes. We demonstrate how to use the approach to identify interactions and how to discard non-influential operational variables. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. ASKI: A modular toolbox for scattering-integral-based seismic full waveform inversion and sensitivity analysis utilizing external forward codes

    Directory of Open Access Journals (Sweden)

    Florian Schumacher

    2016-01-01

    Full Text Available Due to increasing computational resources, the development of new numerically demanding methods and software for imaging Earth’s interior remains of high interest in Earth sciences. Here, we give a description from a user’s and programmer’s perspective of the highly modular, flexible and extendable software package ASKI–Analysis of Sensitivity and Kernel Inversion–recently developed for iterative scattering-integral-based seismic full waveform inversion. In ASKI, the three fundamental steps of solving the seismic forward problem, computing waveform sensitivity kernels and deriving a model update are solved by independent software programs that interact via file output/input only. Furthermore, the spatial discretizations of the model space used for solving the seismic forward problem and for deriving model updates, respectively, are kept completely independent. For this reason, ASKI does not contain a specific forward solver but instead provides a general interface to established community wave propagation codes. Moreover, the third fundamental step of deriving a model update can be repeated at relatively low costs applying different kinds of model regularization or re-selecting/weighting the inverted dataset without need to re-solve the forward problem or re-compute the kernels. Additionally, ASKI offers the user sensitivity and resolution analysis tools based on the full sensitivity matrix and allows to compose customized workflows in a consistent computational environment. ASKI is written in modern Fortran and Python, it is well documented and freely available under terms of the GNU General Public License (http://www.rub.de/aski.

  8. 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

  9. 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.

  10. Analysis of Global Sensitivity of Landing Variables on Landing Loads and Extreme Values of the Loads in Carrier-Based Aircrafts

    Directory of Open Access Journals (Sweden)

    Jin Zhou

    2018-01-01

    Full Text Available When a carrier-based aircraft is in arrested landing on deck, the impact loads on landing gears and airframe are closely related to landing states. The distribution and extreme values of the landing loads obtained during life-cycle analysis provide an important basis for buffering parameter design and fatigue design. In this paper, the effect of the multivariate distribution was studied based on military standards and guides. By establishment of a virtual prototype, the extended Fourier amplitude sensitivity test (EFAST method is applied on sensitivity analysis of landing variables. The results show that sinking speed and rolling angle are the main influencing factors on the landing gear’s course load and vertical load; sinking speed, rolling angle, and yawing angle are the main influencing factors on the landing gear’s lateral load; and sinking speed is the main influencing factor on the barycenter overload. The extreme values of loads show that the typical condition design in the structural strength analysis is safe. The maximum difference value of the vertical load of the main landing gear is 12.0%. This research may provide some reference for structure design of landing gears and compilation of load spectrum for carrier-based aircrafts.

  11. Multitarget global sensitivity analysis of n-butanol combustion.

    Science.gov (United States)

    Zhou, Dingyu D Y; Davis, Michael J; Skodje, Rex T

    2013-05-02

    A model for the combustion of butanol is studied using a recently developed theoretical method for the systematic improvement of the kinetic mechanism. The butanol mechanism includes 1446 reactions, and we demonstrate that it is straightforward and computationally feasible to implement a full global sensitivity analysis incorporating all the reactions. In addition, we extend our previous analysis of ignition-delay targets to include species targets. The combination of species and ignition targets leads to multitarget global sensitivity analysis, which allows for a more complete mechanism validation procedure than we previously implemented. The inclusion of species sensitivity analysis allows for a direct comparison between reaction pathway analysis and global sensitivity analysis.

  12. 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.

  13. '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.

  14. Non-invasive baroreflex sensitivity assessment using wavelet transfer function-based time–frequency analysis

    International Nuclear Information System (INIS)

    Keissar, K; Gilad, O; Maestri, R; Pinna, G D; La Rovere, M T

    2010-01-01

    A novel approach for the estimation of baroreflex sensitivity (BRS) is introduced based on time–frequency analysis of the transfer function (TF). The TF method (TF-BRS) is a well-established non-invasive technique which assumes stationarity. This condition is difficult to meet, especially in cardiac patients. In this study, the classical TF was replaced with a wavelet transfer function (WTF) and the classical coherence was replaced with wavelet transform coherence (WTC), adding the time domain as an additional degree of freedom with dynamic error estimation. Error analysis and comparison between WTF-BRS and TF-BRS were performed using simulated signals with known transfer function and added noise. Similar comparisons were performed for ECG and blood pressure signals, in the supine position, of 19 normal subjects, 44 patients with a history of previous myocardial infarction (MI) and 45 patients with chronic heart failure. This yielded an excellent linear association (R > 0.94, p < 0.001) for time-averaged WTF-BRS, validating the new method as consistent with a known method. The additional advantage of dynamic analysis of coherence and TF estimates was illustrated in two physiological examples of supine rest and change of posture showing the evolution of BRS synchronized with its error estimations and sympathovagal balance

  15. 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

  16. 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

  17. 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.

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

    African Journals Online (AJOL)

    user

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

  19. 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

  20. 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)

  1. Variance estimation for sensitivity analysis of poverty and inequality measures

    Directory of Open Access Journals (Sweden)

    Christian Dudel

    2017-04-01

    Full Text Available Estimates of poverty and inequality are often based on application of a single equivalence scale, despite the fact that a large number of different equivalence scales can be found in the literature. This paper describes a framework for sensitivity analysis which can be used to account for the variability of equivalence scales and allows to derive variance estimates of results of sensitivity analysis. Simulations show that this method yields reliable estimates. An empirical application reveals that accounting for both variability of equivalence scales and sampling variance leads to confidence intervals which are wide.

  2. 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)

  3. Moment-based metrics for global sensitivity analysis of hydrological systems

    Directory of Open Access Journals (Sweden)

    A. Dell'Oca

    2017-12-01

    Full Text Available We propose new metrics to assist global sensitivity analysis, GSA, of hydrological and Earth systems. Our approach allows assessing the impact of uncertain parameters on main features of the probability density function, pdf, of a target model output, y. These include the expected value of y, the spread around the mean and the degree of symmetry and tailedness of the pdf of y. Since reliable assessment of higher-order statistical moments can be computationally demanding, we couple our GSA approach with a surrogate model, approximating the full model response at a reduced computational cost. Here, we consider the generalized polynomial chaos expansion (gPCE, other model reduction techniques being fully compatible with our theoretical framework. We demonstrate our approach through three test cases, including an analytical benchmark, a simplified scenario mimicking pumping in a coastal aquifer and a laboratory-scale conservative transport experiment. Our results allow ascertaining which parameters can impact some moments of the model output pdf while being uninfluential to others. We also investigate the error associated with the evaluation of our sensitivity metrics by replacing the original system model through a gPCE. Our results indicate that the construction of a surrogate model with increasing level of accuracy might be required depending on the statistical moment considered in the GSA. The approach is fully compatible with (and can assist the development of analysis techniques employed in the context of reduction of model complexity, model calibration, design of experiment, uncertainty quantification and risk assessment.

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

    African Journals Online (AJOL)

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

  5. 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.

  6. 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.

  7. Methodology for sensitivity analysis, approximate analysis, and design optimization in CFD for multidisciplinary applications. [computational fluid dynamics

    Science.gov (United States)

    Taylor, Arthur C., III; Hou, Gene W.

    1992-01-01

    Fundamental equations of aerodynamic sensitivity analysis and approximate analysis for the two dimensional thin layer Navier-Stokes equations are reviewed, and special boundary condition considerations necessary to apply these equations to isolated lifting airfoils on 'C' and 'O' meshes are discussed in detail. An efficient strategy which is based on the finite element method and an elastic membrane representation of the computational domain is successfully tested, which circumvents the costly 'brute force' method of obtaining grid sensitivity derivatives, and is also useful in mesh regeneration. The issue of turbulence modeling is addressed in a preliminary study. Aerodynamic shape sensitivity derivatives are efficiently calculated, and their accuracy is validated on two viscous test problems, including: (1) internal flow through a double throat nozzle, and (2) external flow over a NACA 4-digit airfoil. An automated aerodynamic design optimization strategy is outlined which includes the use of a design optimization program, an aerodynamic flow analysis code, an aerodynamic sensitivity and approximate analysis code, and a mesh regeneration and grid sensitivity analysis code. Application of the optimization methodology to the two test problems in each case resulted in a new design having a significantly improved performance in the aerodynamic response of interest.

  8. 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

  9. Sensitivity analysis in multiple imputation in effectiveness studies of psychotherapy.

    Science.gov (United States)

    Crameri, Aureliano; von Wyl, Agnes; Koemeda, Margit; Schulthess, Peter; Tschuschke, Volker

    2015-01-01

    The importance of preventing and treating incomplete data in effectiveness studies is nowadays emphasized. However, most of the publications focus on randomized clinical trials (RCT). One flexible technique for statistical inference with missing data is multiple imputation (MI). Since methods such as MI rely on the assumption of missing data being at random (MAR), a sensitivity analysis for testing the robustness against departures from this assumption is required. In this paper we present a sensitivity analysis technique based on posterior predictive checking, which takes into consideration the concept of clinical significance used in the evaluation of intra-individual changes. We demonstrate the possibilities this technique can offer with the example of irregular longitudinal data collected with the Outcome Questionnaire-45 (OQ-45) and the Helping Alliance Questionnaire (HAQ) in a sample of 260 outpatients. The sensitivity analysis can be used to (1) quantify the degree of bias introduced by missing not at random data (MNAR) in a worst reasonable case scenario, (2) compare the performance of different analysis methods for dealing with missing data, or (3) detect the influence of possible violations to the model assumptions (e.g., lack of normality). Moreover, our analysis showed that ratings from the patient's and therapist's version of the HAQ could significantly improve the predictive value of the routine outcome monitoring based on the OQ-45. Since analysis dropouts always occur, repeated measurements with the OQ-45 and the HAQ analyzed with MI are useful to improve the accuracy of outcome estimates in quality assurance assessments and non-randomized effectiveness studies in the field of outpatient psychotherapy.

  10. Systemization of burnup sensitivity analysis code (2) (Contract research)

    International Nuclear Information System (INIS)

    Tatsumi, Masahiro; Hyoudou, Hideaki

    2008-08-01

    Towards the practical use of fast reactors, it is a very important subject to improve prediction accuracy for neutronic properties in LMFBR cores from the viewpoint of improvements on plant economic efficiency with rationally high performance cores and that on reliability and safety margins. A distinct improvement on accuracy in nuclear core design has been accomplished by the development of adjusted nuclear library using the cross-section adjustment method, in which the results of critical experiments of JUPITER and so on are reflected. In the design of large LMFBR cores, however, it is important to accurately estimate not only neutronic characteristics, for example, reaction rate distribution and control rod worth but also burnup characteristics, for example, burnup reactivity loss, breeding ratio and so on. For this purpose, it is desired to improve prediction accuracy of burnup characteristics using the data widely obtained in actual core such as the experimental fast reactor 'JOYO'. The analysis of burnup characteristic is needed to effectively use burnup characteristics data in the actual cores based on the cross-section adjustment method. So far, a burnup sensitivity analysis code, SAGEP-BURN, has been developed and confirmed its effectiveness. However, there is a problem that analysis sequence become inefficient because of a big burden to users due to complexity of the theory of burnup sensitivity and limitation of the system. It is also desired to rearrange the system for future revision since it is becoming difficult to implement new functions in the existing large system. It is not sufficient to unify each computational component for the following reasons: the computational sequence may be changed for each item being analyzed or for purpose such as interpretation of physical meaning. Therefore, it is needed to systemize the current code for burnup sensitivity analysis with component blocks of functionality that can be divided or constructed on occasion

  11. 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

  12. Automated differentiation of computer models for sensitivity analysis

    International Nuclear Information System (INIS)

    Worley, B.A.

    1990-01-01

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

  13. Automated differentiation of computer models for sensitivity analysis

    International Nuclear Information System (INIS)

    Worley, B.A.

    1991-01-01

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

  14. Water-Based Pressure-Sensitive Paints

    Science.gov (United States)

    Jordan, Jeffrey D.; Watkins, A. Neal; Oglesby, Donald M.; Ingram, JoAnne L.

    2006-01-01

    Water-based pressure-sensitive paints (PSPs) have been invented as alternatives to conventional organic-solvent-based pressure-sensitive paints, which are used primarily for indicating distributions of air pressure on wind-tunnel models. Typically, PSPs are sprayed onto aerodynamic models after they have been mounted in wind tunnels. When conventional organic-solvent-based PSPs are used, this practice creates a problem of removing toxic fumes from inside the wind tunnels. The use of water-based PSPs eliminates this problem. The waterbased PSPs offer high performance as pressure indicators, plus all the advantages of common water-based paints (low toxicity, low concentrations of volatile organic compounds, and easy cleanup by use of water).

  15. Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - II: Application to IFMIF reliability assessment

    Energy Technology Data Exchange (ETDEWEB)

    Cacuci, D. G. [Commiss Energy Atom, Direct Energy Nucl, Saclay, (France); Cacuci, D. G.; Balan, I. [Univ Karlsruhe, Inst Nucl Technol and Reactor Safetly, Karlsruhe, (Germany); Ionescu-Bujor, M. [Forschungszentrum Karlsruhe, Fus Program, D-76021 Karlsruhe, (Germany)

    2008-07-01

    In Part II of this work, the adjoint sensitivity analysis procedure developed in Part I is applied to perform sensitivity analysis of several dynamic reliability models of systems of increasing complexity, culminating with the consideration of the International Fusion Materials Irradiation Facility (IFMIF) accelerator system. Section II presents the main steps of a procedure for the automated generation of Markov chains for reliability analysis, including the abstraction of the physical system, construction of the Markov chain, and the generation and solution of the ensuing set of differential equations; all of these steps have been implemented in a stand-alone computer code system called QUEFT/MARKOMAG-S/MCADJSEN. This code system has been applied to sensitivity analysis of dynamic reliability measures for a paradigm '2-out-of-3' system comprising five components and also to a comprehensive dynamic reliability analysis of the IFMIF accelerator system facilities for the average availability and, respectively, the system's availability at the final mission time. The QUEFT/MARKOMAG-S/MCADJSEN has been used to efficiently compute sensitivities to 186 failure and repair rates characterizing components and subsystems of the first-level fault tree of the IFMIF accelerator system. (authors)

  16. Adjoint sensitivity analysis of dynamic reliability models based on Markov chains - II: Application to IFMIF reliability assessment

    International Nuclear Information System (INIS)

    Cacuci, D. G.; Cacuci, D. G.; Balan, I.; Ionescu-Bujor, M.

    2008-01-01

    In Part II of this work, the adjoint sensitivity analysis procedure developed in Part I is applied to perform sensitivity analysis of several dynamic reliability models of systems of increasing complexity, culminating with the consideration of the International Fusion Materials Irradiation Facility (IFMIF) accelerator system. Section II presents the main steps of a procedure for the automated generation of Markov chains for reliability analysis, including the abstraction of the physical system, construction of the Markov chain, and the generation and solution of the ensuing set of differential equations; all of these steps have been implemented in a stand-alone computer code system called QUEFT/MARKOMAG-S/MCADJSEN. This code system has been applied to sensitivity analysis of dynamic reliability measures for a paradigm '2-out-of-3' system comprising five components and also to a comprehensive dynamic reliability analysis of the IFMIF accelerator system facilities for the average availability and, respectively, the system's availability at the final mission time. The QUEFT/MARKOMAG-S/MCADJSEN has been used to efficiently compute sensitivities to 186 failure and repair rates characterizing components and subsystems of the first-level fault tree of the IFMIF accelerator system. (authors)

  17. 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)

  18. Sensitivity and uncertainty analysis of NET/ITER shielding blankets

    International Nuclear Information System (INIS)

    Hogenbirk, A.; Gruppelaar, H.; Verschuur, K.A.

    1990-09-01

    Results are presented of sensitivity and uncertainty calculations based upon the European fusion file (EFF-1). The effect of uncertainties in Fe, Cr and Ni cross sections on the nuclear heating in the coils of a NET/ITER shielding blanket has been studied. The analysis has been performed for the total cross section as well as partial cross sections. The correct expression for the sensitivity profile was used, including the gain term. The resulting uncertainty in the nuclear heating lies between 10 and 20 per cent. (author). 18 refs.; 2 figs.; 2 tabs

  19. 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).

  20. 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

  1. 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

  2. Automatic CT-based finite element model generation for temperature-based death time estimation: feasibility study and sensitivity analysis.

    Science.gov (United States)

    Schenkl, Sebastian; Muggenthaler, Holger; Hubig, Michael; Erdmann, Bodo; Weiser, Martin; Zachow, Stefan; Heinrich, Andreas; Güttler, Felix Victor; Teichgräber, Ulf; Mall, Gita

    2017-05-01

    Temperature-based death time estimation is based either on simple phenomenological models of corpse cooling or on detailed physical heat transfer models. The latter are much more complex but allow a higher accuracy of death time estimation, as in principle, all relevant cooling mechanisms can be taken into account.Here, a complete workflow for finite element-based cooling simulation is presented. The following steps are demonstrated on a CT phantom: Computer tomography (CT) scan Segmentation of the CT images for thermodynamically relevant features of individual geometries and compilation in a geometric computer-aided design (CAD) model Conversion of the segmentation result into a finite element (FE) simulation model Computation of the model cooling curve (MOD) Calculation of the cooling time (CTE) For the first time in FE-based cooling time estimation, the steps from the CT image over segmentation to FE model generation are performed semi-automatically. The cooling time calculation results are compared to cooling measurements performed on the phantoms under controlled conditions. In this context, the method is validated using a CT phantom. Some of the phantoms' thermodynamic material parameters had to be determined via independent experiments.Moreover, the impact of geometry and material parameter uncertainties on the estimated cooling time is investigated by a sensitivity analysis.

  3. Sensitivity Analysis of a Horizontal Earth Electrode under Impulse ...

    African Journals Online (AJOL)

    This paper presents the sensitivity analysis of an earthing conductor under the influence of impulse current arising from a lightning stroke. The approach is based on the 2nd order finite difference time domain (FDTD). The earthing conductor is regarded as a lossy transmission line where it is divided into series connected ...

  4. Stochastic sensitivity analysis of periodic attractors in non-autonomous nonlinear dynamical systems based on stroboscopic map

    Energy Technology Data Exchange (ETDEWEB)

    Guo, Kong-Ming, E-mail: kmguo@xidian.edu.cn [School of Electromechanical Engineering, Xidian University, P.O. Box 187, Xi' an 710071 (China); Jiang, Jun, E-mail: jun.jiang@mail.xjtu.edu.cn [State Key Laboratory for Strength and Vibration, Xi' an Jiaotong University, Xi' an 710049 (China)

    2014-07-04

    To apply stochastic sensitivity function method, which can estimate the probabilistic distribution of stochastic attractors, to non-autonomous dynamical systems, a 1/N-period stroboscopic map for a periodic motion is constructed in order to discretize the continuous cycle into a discrete one. In this way, the sensitivity analysis of a cycle for discrete map can be utilized and a numerical algorithm for the stochastic sensitivity analysis of periodic solutions of non-autonomous nonlinear dynamical systems under stochastic disturbances is devised. An external excited Duffing oscillator and a parametric excited laser system are studied as examples to show the validity of the proposed method. - Highlights: • A method to analyze sensitivity of stochastic periodic attractors in non-autonomous dynamical systems is proposed. • Probabilistic distribution around periodic attractors in an external excited Φ{sup 6} Duffing system is obtained. • Probabilistic distribution around a periodic attractor in a parametric excited laser system is determined.

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

    Science.gov (United States)

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

    2016-01-01

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

  6. Probabilistic sensitivity analysis incorporating the bootstrap: an example comparing treatments for the eradication of Helicobacter pylori.

    Science.gov (United States)

    Pasta, D J; Taylor, J L; Henning, J M

    1999-01-01

    Decision-analytic models are frequently used to evaluate the relative costs and benefits of alternative therapeutic strategies for health care. Various types of sensitivity analysis are used to evaluate the uncertainty inherent in the models. Although probabilistic sensitivity analysis is more difficult theoretically and computationally, the results can be much more powerful and useful than deterministic sensitivity analysis. The authors show how a Monte Carlo simulation can be implemented using standard software to perform a probabilistic sensitivity analysis incorporating the bootstrap. The method is applied to a decision-analytic model evaluating the cost-effectiveness of Helicobacter pylori eradication. The necessary steps are straightforward and are described in detail. The use of the bootstrap avoids certain difficulties encountered with theoretical distributions. The probabilistic sensitivity analysis provided insights into the decision-analytic model beyond the traditional base-case and deterministic sensitivity analyses and should become the standard method for assessing sensitivity.

  7. Structural development and web service based sensitivity analysis of the Biome-BGC MuSo model

    Science.gov (United States)

    Hidy, Dóra; Balogh, János; Churkina, Galina; Haszpra, László; Horváth, Ferenc; Ittzés, Péter; Ittzés, Dóra; Ma, Shaoxiu; Nagy, Zoltán; Pintér, Krisztina; Barcza, Zoltán

    2014-05-01

    -BGC with multi-soil layer). Within the frame of the BioVeL project (http://www.biovel.eu) an open source and domain independent scientific workflow management system (http://www.taverna.org.uk) are used to support 'in silico' experimentation and easy applicability of different models including Biome-BGC MuSo. Workflows can be built upon functionally linked sets of web services like retrieval of meteorological dataset and other parameters; preparation of single run or spatial run model simulation; desk top grid technology based Monte Carlo experiment with parallel processing; model sensitivity analysis, etc. The newly developed, Monte Carlo experiment based sensitivity analysis is described in this study and results are presented about differences in the sensitivity of the original and the developed Biome-BGC model.

  8. 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.

  9. Reliability Coupled Sensitivity Based Design Approach for Gravity Retaining Walls

    Science.gov (United States)

    Guha Ray, A.; Baidya, D. K.

    2012-09-01

    Sensitivity analysis involving different random variables and different potential failure modes of a gravity retaining wall focuses on the fact that high sensitivity of a particular variable on a particular mode of failure does not necessarily imply a remarkable contribution to the overall failure probability. The present paper aims at identifying a probabilistic risk factor ( R f ) for each random variable based on the combined effects of failure probability ( P f ) of each mode of failure of a gravity retaining wall and sensitivity of each of the random variables on these failure modes. P f is calculated by Monte Carlo simulation and sensitivity analysis of each random variable is carried out by F-test analysis. The structure, redesigned by modifying the original random variables with the risk factors, is safe against all the variations of random variables. It is observed that R f for friction angle of backfill soil ( φ 1 ) increases and cohesion of foundation soil ( c 2 ) decreases with an increase of variation of φ 1 , while R f for unit weights ( γ 1 and γ 2 ) for both soil and friction angle of foundation soil ( φ 2 ) remains almost constant for variation of soil properties. The results compared well with some of the existing deterministic and probabilistic methods and found to be cost-effective. It is seen that if variation of φ 1 remains within 5 %, significant reduction in cross-sectional area can be achieved. But if the variation is more than 7-8 %, the structure needs to be modified. Finally design guidelines for different wall dimensions, based on the present approach, are proposed.

  10. 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.

  11. 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.

  12. Least Squares Shadowing Sensitivity Analysis of Chaotic Flow Around a Two-Dimensional Airfoil

    Science.gov (United States)

    Blonigan, Patrick J.; Wang, Qiqi; Nielsen, Eric J.; Diskin, Boris

    2016-01-01

    Gradient-based sensitivity analysis has proven to be an enabling technology for many applications, including design of aerospace vehicles. However, conventional sensitivity analysis methods break down when applied to long-time averages of chaotic systems. This breakdown is a serious limitation because many aerospace applications involve physical phenomena that exhibit chaotic dynamics, most notably high-resolution large-eddy and direct numerical simulations of turbulent aerodynamic flows. A recently proposed methodology, Least Squares Shadowing (LSS), avoids this breakdown and advances the state of the art in sensitivity analysis for chaotic flows. The first application of LSS to a chaotic flow simulated with a large-scale computational fluid dynamics solver is presented. The LSS sensitivity computed for this chaotic flow is verified and shown to be accurate, but the computational cost of the current LSS implementation is high.

  13. 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

  14. 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

  15. Sensitivity analysis for matched pair analysis of binary data: From worst case to average case analysis.

    Science.gov (United States)

    Hasegawa, Raiden; Small, Dylan

    2017-12-01

    In matched observational studies where treatment assignment is not randomized, sensitivity analysis helps investigators determine how sensitive their estimated treatment effect is to some unmeasured confounder. The standard approach calibrates the sensitivity analysis according to the worst case bias in a pair. This approach will result in a conservative sensitivity analysis if the worst case bias does not hold in every pair. In this paper, we show that for binary data, the standard approach can be calibrated in terms of the average bias in a pair rather than worst case bias. When the worst case bias and average bias differ, the average bias interpretation results in a less conservative sensitivity analysis and more power. In many studies, the average case calibration may also carry a more natural interpretation than the worst case calibration and may also allow researchers to incorporate additional data to establish an empirical basis with which to calibrate a sensitivity analysis. We illustrate this with a study of the effects of cellphone use on the incidence of automobile accidents. Finally, we extend the average case calibration to the sensitivity analysis of confidence intervals for attributable effects. © 2017, The International Biometric Society.

  16. 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...

  17. Computing derivative-based global sensitivity measures using polynomial chaos expansions

    International Nuclear Information System (INIS)

    Sudret, B.; Mai, C.V.

    2015-01-01

    In the field of computer experiments sensitivity analysis aims at quantifying the relative importance of each input parameter (or combinations thereof) of a computational model with respect to the model output uncertainty. Variance decomposition methods leading to the well-known Sobol' indices are recognized as accurate techniques, at a rather high computational cost though. The use of polynomial chaos expansions (PCE) to compute Sobol' indices has allowed to alleviate the computational burden though. However, when dealing with large dimensional input vectors, it is good practice to first use screening methods in order to discard unimportant variables. The derivative-based global sensitivity measures (DGSMs) have been developed recently in this respect. In this paper we show how polynomial chaos expansions may be used to compute analytically DGSMs as a mere post-processing. This requires the analytical derivation of derivatives of the orthonormal polynomials which enter PC expansions. Closed-form expressions for Hermite, Legendre and Laguerre polynomial expansions are given. The efficiency of the approach is illustrated on two well-known benchmark problems in sensitivity analysis. - Highlights: • Derivative-based global sensitivity measures (DGSM) have been developed for screening purpose. • Polynomial chaos expansions (PC) are used as a surrogate model of the original computational model. • From a PC expansion the DGSM can be computed analytically. • The paper provides the derivatives of Hermite, Legendre and Laguerre polynomials for this purpose

  18. Sensitivity analysis for plane orientation in three-dimensional cephalometric analysis based on superimposition of serial cone beam computed tomography images

    Science.gov (United States)

    Lagravère, M O; Major, P W; Carey, J

    2010-01-01

    Objectives The purpose of this study was to evaluate the potential errors associated with superimposition of serial cone beam CT (CBCT) images utilizing reference planes based on cranial base landmarks using a sensitivity analysis. Methods CBCT images from 62 patients participating in a maxillary expansion clinical trial were analysed. The left and right auditory external meatus (AEM), dorsum foramen magnum (DFM) and the midpoint between the left and right foramen spinosum (ELSA) were used to define a three-dimensional (3D) anatomical reference co-ordinate system. Intraclass correlation coefficients for all four landmarks were obtained. Transformation of the reference system was carried out using the four landmarks and mathematical comparison of values. Results Excellent intrareliability values for each dimension were obtained for each landmark. Evaluation of the method to transform the co-ordinate system was first done by comparing interlandmark distances before and after transformations, giving errors in lengths in the order of 10–14% (software rounding error). A sensitivity evaluation was performed by adding 0.25 mm, 0.5 mm and 1 mm error in one axis of the ELSA. A positioning error of 0.25 mm in the ELSA can produce up to 1.0 mm error in other cranial base landmark co-ordinates. These errors could be magnified to distant landmarks where in some cases menton and infraorbital landmarks were displaced 4–6 mm. Conclusions Minor variations in location of the ELSA, both the AEM and the DFM landmarks produce large and potentially clinically significant uncertainty in co-ordinate system alignment. PMID:20841457

  19. 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.

  20. Automating sensitivity analysis of computer models using computer calculus

    International Nuclear Information System (INIS)

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

    1986-01-01

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

  1. Meta-analysis of the relative sensitivity of semi-natural vegetation species to ozone

    International Nuclear Information System (INIS)

    Hayes, F.; Jones, M.L.M.; Mills, G.; Ashmore, M.

    2007-01-01

    This study identified 83 species from existing publications suitable for inclusion in a database of sensitivity of species to ozone (OZOVEG database). An index, the relative sensitivity to ozone, was calculated for each species based on changes in biomass in order to test for species traits associated with ozone sensitivity. Meta-analysis of the ozone sensitivity data showed a wide inter-specific range in response to ozone. Some relationships in comparison to plant physiological and ecological characteristics were identified. Plants of the therophyte lifeform were particularly sensitive to ozone. Species with higher mature leaf N concentration were more sensitive to ozone than those with lower leaf N concentration. Some relationships between relative sensitivity to ozone and Ellenberg habitat requirements were also identified. In contrast, no relationships between relative sensitivity to ozone and mature leaf P concentration, Grime's CSR strategy, leaf longevity, flowering season, stomatal density and maximum altitude were found. The relative sensitivity of species and relationships with plant characteristics identified in this study could be used to predict sensitivity to ozone of untested species and communities. - Meta-analysis of the relative sensitivity of semi-natural vegetation species to ozone showed some relationships with physiological and ecological characteristics

  2. Sensitivity analysis for missing dichotomous outcome data in multi-visit randomized clinical trial with randomization-based covariance adjustment.

    Science.gov (United States)

    Li, Siying; Koch, Gary G; Preisser, John S; Lam, Diana; Sanchez-Kam, Matilde

    2017-01-01

    Dichotomous endpoints in clinical trials have only two possible outcomes, either directly or via categorization of an ordinal or continuous observation. It is common to have missing data for one or more visits during a multi-visit study. This paper presents a closed form method for sensitivity analysis of a randomized multi-visit clinical trial that possibly has missing not at random (MNAR) dichotomous data. Counts of missing data are redistributed to the favorable and unfavorable outcomes mathematically to address possibly informative missing data. Adjusted proportion estimates and their closed form covariance matrix estimates are provided. Treatment comparisons over time are addressed with Mantel-Haenszel adjustment for a stratification factor and/or randomization-based adjustment for baseline covariables. The application of such sensitivity analyses is illustrated with an example. An appendix outlines an extension of the methodology to ordinal endpoints.

  3. Sensitivity analysis in optimization and reliability problems

    International Nuclear Information System (INIS)

    Castillo, Enrique; Minguez, Roberto; Castillo, Carmen

    2008-01-01

    The paper starts giving the main results that allow a sensitivity analysis to be performed in a general optimization problem, including sensitivities of the objective function, the primal and the dual variables with respect to data. In particular, general results are given for non-linear programming, and closed formulas for linear programming problems are supplied. Next, the methods are applied to a collection of civil engineering reliability problems, which includes a bridge crane, a retaining wall and a composite breakwater. Finally, the sensitivity analysis formulas are extended to calculus of variations problems and a slope stability problem is used to illustrate the methods

  4. Sensitivity analysis in optimization and reliability problems

    Energy Technology Data Exchange (ETDEWEB)

    Castillo, Enrique [Department of Applied Mathematics and Computational Sciences, University of Cantabria, Avda. Castros s/n., 39005 Santander (Spain)], E-mail: castie@unican.es; Minguez, Roberto [Department of Applied Mathematics, University of Castilla-La Mancha, 13071 Ciudad Real (Spain)], E-mail: roberto.minguez@uclm.es; Castillo, Carmen [Department of Civil Engineering, University of Castilla-La Mancha, 13071 Ciudad Real (Spain)], E-mail: mariacarmen.castillo@uclm.es

    2008-12-15

    The paper starts giving the main results that allow a sensitivity analysis to be performed in a general optimization problem, including sensitivities of the objective function, the primal and the dual variables with respect to data. In particular, general results are given for non-linear programming, and closed formulas for linear programming problems are supplied. Next, the methods are applied to a collection of civil engineering reliability problems, which includes a bridge crane, a retaining wall and a composite breakwater. Finally, the sensitivity analysis formulas are extended to calculus of variations problems and a slope stability problem is used to illustrate the methods.

  5. 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.

  6. Sensitivity analysis for large-scale problems

    Science.gov (United States)

    Noor, Ahmed K.; Whitworth, Sandra L.

    1987-01-01

    The development of efficient techniques for calculating sensitivity derivatives is studied. The objective is to present a computational procedure for calculating sensitivity derivatives as part of performing structural reanalysis for large-scale problems. The scope is limited to framed type structures. Both linear static analysis and free-vibration eigenvalue problems are considered.

  7. Fines Classification Based on Sensitivity to Pore-Fluid Chemistry

    KAUST Repository

    Jang, Junbong

    2015-12-28

    The 75-μm particle size is used to discriminate between fine and coarse grains. Further analysis of fine grains is typically based on the plasticity chart. Whereas pore-fluid-chemistry-dependent soil response is a salient and distinguishing characteristic of fine grains, pore-fluid chemistry is not addressed in current classification systems. Liquid limits obtained with electrically contrasting pore fluids (deionized water, 2-M NaCl brine, and kerosene) are combined to define the soil "electrical sensitivity." Liquid limit and electrical sensitivity can be effectively used to classify fine grains according to their fluid-soil response into no-, low-, intermediate-, or high-plasticity fine grains of low, intermediate, or high electrical sensitivity. The proposed methodology benefits from the accumulated experience with liquid limit in the field and addresses the needs of a broader range of geotechnical engineering problems. © ASCE.

  8. Fines classification based on sensitivity to pore-fluid chemistry

    Science.gov (United States)

    Jang, Junbong; Santamarina, J. Carlos

    2016-01-01

    The 75-μm particle size is used to discriminate between fine and coarse grains. Further analysis of fine grains is typically based on the plasticity chart. Whereas pore-fluid-chemistry-dependent soil response is a salient and distinguishing characteristic of fine grains, pore-fluid chemistry is not addressed in current classification systems. Liquid limits obtained with electrically contrasting pore fluids (deionized water, 2-M NaCl brine, and kerosene) are combined to define the soil “electrical sensitivity.” Liquid limit and electrical sensitivity can be effectively used to classify fine grains according to their fluid-soil response into no-, low-, intermediate-, or high-plasticity fine grains of low, intermediate, or high electrical sensitivity. The proposed methodology benefits from the accumulated experience with liquid limit in the field and addresses the needs of a broader range of geotechnical engineering problems.

  9. Prediction of sensitivity to gefitinib/erlotinib for EGFR mutations in NSCLC based on structural interaction fingerprints and multilinear principal component analysis.

    Science.gov (United States)

    Zou, Bin; Lee, Victor H F; Yan, Hong

    2018-03-07

    Non-small cell lung cancer (NSCLC) with activating EGFR mutations, especially exon 19 deletions and the L858R point mutation, is particularly responsive to gefitinib and erlotinib. However, the sensitivity varies for less common and rare EGFR mutations. There are various explanations for the low sensitivity of EGFR exon 20 insertions and the exon 20 T790 M point mutation to gefitinib/erlotinib. However, few studies discuss, from a structural perspective, why less common mutations, like G719X and L861Q, have moderate sensitivity to gefitinib/erlotinib. To decode the drug sensitivity/selectivity of EGFR mutants, it is important to analyze the interaction between EGFR mutants and EGFR inhibitors. In this paper, the 30 most common EGFR mutants were selected and the technique of protein-ligand interaction fingerprint (IFP) was applied to analyze and compare the binding modes of EGFR mutant-gefitinib/erlotinib complexes. Molecular dynamics simulations were employed to obtain the dynamic trajectory and a matrix of IFPs for each EGFR mutant-inhibitor complex. Multilinear Principal Component Analysis (MPCA) was applied for dimensionality reduction and feature selection. The selected features were further analyzed for use as a drug sensitivity predictor. The results showed that the accuracy of prediction of drug sensitivity was very high for both gefitinib and erlotinib. Targeted Projection Pursuit (TPP) was used to show that the data points can be easily separated based on their sensitivities to gefetinib/erlotinib. We can conclude that the IFP features of EGFR mutant-TKI complexes and the MPCA-based tensor object feature extraction are useful to predict the drug sensitivity of EGFR mutants. The findings provide new insights for studying and predicting drug resistance/sensitivity of EGFR mutations in NSCLC and can be beneficial to the design of future targeted therapies and innovative drug discovery.

  10. Regional and parametric sensitivity analysis of Sobol' indices

    International Nuclear Information System (INIS)

    Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

    2015-01-01

    Nowadays, utilizing the Monte Carlo estimators for variance-based sensitivity analysis has gained sufficient popularity in many research fields. These estimators are usually based on n+2 sample matrices well designed for computing both the main and total effect indices, where n is the input dimension. The aim of this paper is to use such n+2 sample matrices to investigate how the main and total effect indices change when the uncertainty of the model inputs are reduced. For this purpose, the regional main and total effect functions are defined for measuring the changes on the main and total effect indices when the distribution range of one input is reduced, and the parametric main and total effect functions are introduced to quantify the residual main and total effect indices due to the reduced variance of one input. Monte Carlo estimators are derived for all the developed sensitivity concepts based on the n+2 samples matrices originally used for computing the main and total effect indices, thus no extra computational cost is introduced. The Ishigami function, a nonlinear model and a planar ten-bar structure are utilized for illustrating the developed sensitivity concepts, and for demonstrating the efficiency and accuracy of the derived Monte Carlo estimators. - Highlights: • The regional main and total effect functions are developed. • The parametric main and total effect functions are introduced. • The proposed sensitivity functions are all generalizations of Sobol' indices. • The Monte Carlo estimators are derived for the four sensitivity functions. • The computational cost of the estimators is the same as that of Sobol' indices

  11. Sensitivity analysis of the Two Geometry Method

    International Nuclear Information System (INIS)

    Wichers, V.A.

    1993-09-01

    The Two Geometry Method (TGM) was designed specifically for the verification of the uranium enrichment of low enriched UF 6 gas in the presence of uranium deposits on the pipe walls. Complications can arise if the TGM is applied under extreme conditions, such as deposits larger than several times the gas activity, small pipe diameters less than 40 mm and low pressures less than 150 Pa. This report presents a comprehensive sensitivity analysis of the TGM. The impact of the various sources of uncertainty on the performance of the method is discussed. The application to a practical case is based on worst case conditions with regards to the measurement conditions, and on realistic conditions with respect to the false alarm probability and the non detection probability. Monte Carlo calculations were used to evaluate the sensitivity for sources of uncertainty which are experimentally inaccessible. (orig.)

  12. First order sensitivity analysis of flexible multibody systems using absolute nodal coordinate formulation

    International Nuclear Information System (INIS)

    Pi Ting; Zhang Yunqing; Chen Liping

    2012-01-01

    Design sensitivity analysis of flexible multibody systems is important in optimizing the performance of mechanical systems. The choice of coordinates to describe the motion of multibody systems has a great influence on the efficiency and accuracy of both the dynamic and sensitivity analysis. In the flexible multibody system dynamics, both the floating frame of reference formulation (FFRF) and absolute nodal coordinate formulation (ANCF) are frequently utilized to describe flexibility, however, only the former has been used in design sensitivity analysis. In this article, ANCF, which has been recently developed and focuses on modeling of beams and plates in large deformation problems, is extended into design sensitivity analysis of flexible multibody systems. The Motion equations of a constrained flexible multibody system are expressed as a set of index-3 differential algebraic equations (DAEs), in which the element elastic forces are defined using nonlinear strain-displacement relations. Both the direct differentiation method and adjoint variable method are performed to do sensitivity analysis and the related dynamic and sensitivity equations are integrated with HHT-I3 algorithm. In this paper, a new method to deduce system sensitivity equations is proposed. With this approach, the system sensitivity equations are constructed by assembling the element sensitivity equations with the help of invariant matrices, which results in the advantage that the complex symbolic differentiation of the dynamic equations is avoided when the flexible multibody system model is changed. Besides that, the dynamic and sensitivity equations formed with the proposed method can be efficiently integrated using HHT-I3 method, which makes the efficiency of the direct differentiation method comparable to that of the adjoint variable method when the number of design variables is not extremely large. All these improvements greatly enhance the application value of the direct differentiation

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

    Science.gov (United States)

    Prestes García, Antonio; Rodríguez-Patón, Alfonso

    2016-12-01

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

  14. 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

  15. 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

  16. Uncertainty, sensitivity analysis and the role of data based mechanistic modeling in hydrology

    Science.gov (United States)

    Ratto, M.; Young, P. C.; Romanowicz, R.; Pappenberger, F.; Saltelli, A.; Pagano, A.

    2007-05-01

    In this paper, we discuss a joint approach to calibration and uncertainty estimation for hydrologic systems that combines a top-down, data-based mechanistic (DBM) modelling methodology; and a bottom-up, reductionist modelling methodology. The combined approach is applied to the modelling of the River Hodder catchment in North-West England. The top-down DBM model provides a well identified, statistically sound yet physically meaningful description of the rainfall-flow data, revealing important characteristics of the catchment-scale response, such as the nature of the effective rainfall nonlinearity and the partitioning of the effective rainfall into different flow pathways. These characteristics are defined inductively from the data without prior assumptions about the model structure, other than it is within the generic class of nonlinear differential-delay equations. The bottom-up modelling is developed using the TOPMODEL, whose structure is assumed a priori and is evaluated by global sensitivity analysis (GSA) in order to specify the most sensitive and important parameters. The subsequent exercises in calibration and validation, performed with Generalized Likelihood Uncertainty Estimation (GLUE), are carried out in the light of the GSA and DBM analyses. This allows for the pre-calibration of the the priors used for GLUE, in order to eliminate dynamical features of the TOPMODEL that have little effect on the model output and would be rejected at the structure identification phase of the DBM modelling analysis. In this way, the elements of meaningful subjectivity in the GLUE approach, which allow the modeler to interact in the modelling process by constraining the model to have a specific form prior to calibration, are combined with other more objective, data-based benchmarks for the final uncertainty estimation. GSA plays a major role in building a bridge between the hypothetico-deductive (bottom-up) and inductive (top-down) approaches and helps to improve the

  17. 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

  18. 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...

  19. 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...

  20. Sensitivity analysis of hybrid power systems using Power Pinch Analysis considering Feed-in Tariff

    International Nuclear Information System (INIS)

    Mohammad Rozali, Nor Erniza; Wan Alwi, Sharifah Rafidah; Manan, Zainuddin Abdul; Klemeš, Jiří Jaromír

    2016-01-01

    Feed-in Tariff (FiT) has been one of the most effective policies in accelerating the development of renewable energy (RE) projects. The amount of RE electricity in the FiT purchase agreement is an important decision that has to be made by the RE project developers. They have to consider various crucial factors associated with RE system operation as well as its stochastic nature. The presented work aims to assess the sensitivity and profitability of a hybrid power system (HPS) in cases of RE system failure or shutdown. The amount of RE electricity for the FiT purchase agreement in various scenarios was determined using a novel tool called On-Grid Problem Table based on the Power Pinch Analysis (PoPA). A sensitivity table has also been introduced to assist planners to evaluate the effects of the RE system's failure on the profitability of the HPS. This table offers insights on the variance of the RE electricity. The sensitivity analysis of various possible scenarios shows that the RE projects can still provide financial benefits via the FiT, despite the losses incurred from the penalty levied. - Highlights: • A Power Pinch Analysis (PoPA) tool to assess the economics of an HPS with FiT. • The new On-Grid Problem Table for targeting the available RE electricity for FiT sale. • A sensitivity table showing the effect of RE electricity changes on the HPS profitability.

  1. 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.)

  2. Dual-energy CT based vascular iodine analysis improves sensitivity for peripheral pulmonary artery thrombus detection: An experimental study in canines

    Energy Technology Data Exchange (ETDEWEB)

    Tang, Chun Xiang [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing, Jiangsu 210002 (China); Zhang, Long Jiang, E-mail: kevinzhlj@163.com [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing, Jiangsu 210002 (China); Han, Zong Hong; Zhou, Chang Sheng [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing, Jiangsu 210002 (China); Krazinski, Aleksander W.; Silverman, Justin R. [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC (United States); Schoepf, U. Joseph [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing, Jiangsu 210002 (China); Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC (United States); Lu, Guang Ming, E-mail: cjr.luguangming@vip.163.com [Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, Nanjing, Jiangsu 210002 (China)

    2013-12-01

    Purpose: To evaluate the performance of dual-energy CT (DECT) based vascular iodine analysis for the detection of acute peripheral pulmonary thrombus (PE) in a canine model with histopathological findings as the reference standard. Materials and methods: The study protocol was approved by our institutional animal committee. Thrombi (n = 12) or saline (n = 4) were intravenously injected via right femoral vein in sixteen dogs, respectively. CT pulmonary angiography (CTPA) in DECT mode was performed and conventional CTPA images and DECT based vascular iodine studies using Lung Vessels application were reconstructed. Two radiologists visually evaluated the number and location of PEs using conventional CTPA and DECT series on a per-animal and a per-clot basis. Detailed histopathological examination of lung specimens and catheter angiography served as reference standard. Sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) of DECT and CTPA were calculated on a segmental and subsegmental or more distal pulmonary artery basis. Weighted κ values were computed to evaluate inter-modality and inter-reader agreement. Results: Thirteen dogs were enrolled for final image analysis (experimental group = 9, control group = 4). Histopathological results revealed 237 emboli in 45 lung lobes in 9 experimental dogs, 11 emboli in segmental pulmonary arteries, 49 in subsegmental pulmonary arteries, 177 in fifth-order or more distal pulmonary arteries. Overall sensitivity, specificity, accuracy, PPV, and NPV for CTPA plus DECT were 93.1%, 76.9%, 87.8%, 89.4%, and 84.2% for the detection of pulmonary emboli. With CTPA versus DECT, sensitivities, specificities, accuracies, PPVs, and NPVs are all 100% for the detection of pulmonary emboli on a segmental pulmonary artery basis, 88.9%, 100%, 96.0%, 100%, and 94.1% for CTPA and 90.4%, 93.0%, 92.0%, 88.7%, and 94.1% for DECT on a subsegmental pulmonary artery basis; 23.8%, 96.4%, 50.4%, 93

  3. 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.

  4. TOLERANCE SENSITIVITY ANALYSIS: THIRTY YEARS LATER

    Directory of Open Access Journals (Sweden)

    Richard E. Wendell

    2010-12-01

    Full Text Available Tolerance sensitivity analysis was conceived in 1980 as a pragmatic approach to effectively characterize a parametric region over which objective function coefficients and right-hand-side terms in linear programming could vary simultaneously and independently while maintaining the same optimal basis. As originally proposed, the tolerance region corresponds to the maximum percentage by which coefficients or terms could vary from their estimated values. Over the last thirty years the original results have been extended in a number of ways and applied in a variety of applications. This paper is a critical review of tolerance sensitivity analysis, including extensions and applications.

  5. Sensitivity analysis for missing data in regulatory submissions.

    Science.gov (United States)

    Permutt, Thomas

    2016-07-30

    The National Research Council Panel on Handling Missing Data in Clinical Trials recommended that sensitivity analyses have to be part of the primary reporting of findings from clinical trials. Their specific recommendations, however, seem not to have been taken up rapidly by sponsors of regulatory submissions. The NRC report's detailed suggestions are along rather different lines than what has been called sensitivity analysis in the regulatory setting up to now. Furthermore, the role of sensitivity analysis in regulatory decision-making, although discussed briefly in the NRC report, remains unclear. This paper will examine previous ideas of sensitivity analysis with a view to explaining how the NRC panel's recommendations are different and possibly better suited to coping with present problems of missing data in the regulatory setting. It will also discuss, in more detail than the NRC report, the relevance of sensitivity analysis to decision-making, both for applicants and for regulators. Published 2015. This article is a U.S. Government work and is in the public domain in the USA. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

  6. Automating sensitivity analysis of computer models using computer calculus

    International Nuclear Information System (INIS)

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

    1985-01-01

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

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  8. Sensitivity analysis and related analysis : A survey of statistical techniques

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    1995-01-01

    This paper reviews the state of the art in five related types of analysis, namely (i) sensitivity or what-if analysis, (ii) uncertainty or risk analysis, (iii) screening, (iv) validation, and (v) optimization. The main question is: when should which type of analysis be applied; which statistical

  9. Sensitivity analysis of land unit suitability for conservation using a knowledge-based system.

    Science.gov (United States)

    Humphries, Hope C; Bourgeron, Patrick S; Reynolds, Keith M

    2010-08-01

    The availability of spatially continuous data layers can have a strong impact on selection of land units for conservation purposes. The suitability of ecological conditions for sustaining the targets of conservation is an important consideration in evaluating candidate conservation sites. We constructed two fuzzy logic-based knowledge bases to determine the conservation suitability of land units in the interior Columbia River basin using NetWeaver software in the Ecosystem Management Decision Support application framework. Our objective was to assess the sensitivity of suitability ratings, derived from evaluating the knowledge bases, to fuzzy logic function parameters and to the removal of data layers (land use condition, road density, disturbance regime change index, vegetation change index, land unit size, cover type size, and cover type change index). The amount and geographic distribution of suitable land polygons was most strongly altered by the removal of land use condition, road density, and land polygon size. Removal of land use condition changed suitability primarily on private or intensively-used public land. Removal of either road density or land polygon size most strongly affected suitability on higher-elevation US Forest Service land containing small-area biophysical environments. Data layers with the greatest influence differed in rank between the two knowledge bases. Our results reinforce the importance of including both biophysical and socio-economic attributes to determine the suitability of land units for conservation. The sensitivity tests provided information about knowledge base structuring and parameterization as well as prioritization for future data needs.

  10. Mixed kernel function support vector regression for global sensitivity analysis

    Science.gov (United States)

    Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

    2017-11-01

    Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

  11. 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

  12. 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

  13. 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.

  14. Sensitivity Analysis of Criticality for Different Nuclear Fuel Shapes

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Hyun Sik; Jang, Misuk; Kim, Seoung Rae [NESS, Daejeon (Korea, Republic of)

    2016-10-15

    Rod-type nuclear fuel was mainly developed in the past, but recent study has been extended to plate-type nuclear fuel. Therefore, this paper reviews the sensitivity of criticality according to different shapes of nuclear fuel types. Criticality analysis was performed using MCNP5. MCNP5 is well-known Monte Carlo codes for criticality analysis and a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron or coupled neutron / photon / electron transport, including the capability to calculate eigenvalues for critical systems. We performed the sensitivity analysis of criticality for different fuel shapes. In sensitivity analysis for simple fuel shapes, the criticality is proportional to the surface area. But for fuel Assembly types, it is not proportional to the surface area. In sensitivity analysis for intervals between plates, the criticality is greater as the interval increases, but if the interval is greater than 8mm, it showed an opposite trend that the criticality decrease by a larger interval. As a result, it has failed to obtain the logical content to be described in common for all cases. The sensitivity analysis of Criticality would be always required whenever subject to be analyzed is changed.

  15. Sensitivity Analysis of Criticality for Different Nuclear Fuel Shapes

    International Nuclear Information System (INIS)

    Kang, Hyun Sik; Jang, Misuk; Kim, Seoung Rae

    2016-01-01

    Rod-type nuclear fuel was mainly developed in the past, but recent study has been extended to plate-type nuclear fuel. Therefore, this paper reviews the sensitivity of criticality according to different shapes of nuclear fuel types. Criticality analysis was performed using MCNP5. MCNP5 is well-known Monte Carlo codes for criticality analysis and a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron or coupled neutron / photon / electron transport, including the capability to calculate eigenvalues for critical systems. We performed the sensitivity analysis of criticality for different fuel shapes. In sensitivity analysis for simple fuel shapes, the criticality is proportional to the surface area. But for fuel Assembly types, it is not proportional to the surface area. In sensitivity analysis for intervals between plates, the criticality is greater as the interval increases, but if the interval is greater than 8mm, it showed an opposite trend that the criticality decrease by a larger interval. As a result, it has failed to obtain the logical content to be described in common for all cases. The sensitivity analysis of Criticality would be always required whenever subject to be analyzed is changed

  16. The role of sensitivity analysis in probabilistic safety assessment

    International Nuclear Information System (INIS)

    Hirschberg, S.; Knochenhauer, M.

    1987-01-01

    The paper describes several items suitable for close examination by means of application of sensitivity analysis, when performing a level 1 PSA. Sensitivity analyses are performed with respect to; (1) boundary conditions, (2) operator actions, and (3) treatment of common cause failures (CCFs). The items of main interest are identified continuously in the course of performing a PSA, as well as by scrutinising the final results. The practical aspects of sensitivity analysis are illustrated by several applications from a recent PSA study (ASEA-ATOM BWR 75). It is concluded that sensitivity analysis leads to insights important for analysts, reviewers and decision makers. (orig./HP)

  17. 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.

  18. Sensitivity Analysis in Two-Stage DEA

    Directory of Open Access Journals (Sweden)

    Athena Forghani

    2015-07-01

    Full Text Available Data envelopment analysis (DEA is a method for measuring the efficiency of peer decision making units (DMUs which uses a set of inputs to produce a set of outputs. In some cases, DMUs have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. One important issue in two-stage DEA is the sensitivity of the results of an analysis to perturbations in the data. The current paper looks into combined model for two-stage DEA and applies the sensitivity analysis to DMUs on the entire frontier. In fact, necessary and sufficient conditions for preserving a DMU's efficiency classiffication are developed when various data changes are applied to all DMUs.

  19. Sensitivity Analysis in Two-Stage DEA

    Directory of Open Access Journals (Sweden)

    Athena Forghani

    2015-12-01

    Full Text Available Data envelopment analysis (DEA is a method for measuring the efficiency of peer decision making units (DMUs which uses a set of inputs to produce a set of outputs. In some cases, DMUs have a two-stage structure, in which the first stage utilizes inputs to produce outputs used as the inputs of the second stage to produce final outputs. One important issue in two-stage DEA is the sensitivity of the results of an analysis to perturbations in the data. The current paper looks into combined model for two-stage DEA and applies the sensitivity analysis to DMUs on the entire frontier. In fact, necessary and sufficient conditions for preserving a DMU's efficiency classiffication are developed when various data changes are applied to all DMUs.

  20. 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.

  1. Sensitivity Analysis of Simulation Models

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2009-01-01

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

  2. 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

  3. 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

  4. 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.

  5. 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)

  6. Sensitivity analysis using probability bounding

    International Nuclear Information System (INIS)

    Ferson, Scott; Troy Tucker, W.

    2006-01-01

    Probability bounds analysis (PBA) provides analysts a convenient means to characterize the neighborhood of possible results that would be obtained from plausible alternative inputs in probabilistic calculations. We show the relationship between PBA and the methods of interval analysis and probabilistic uncertainty analysis from which it is jointly derived, and indicate how the method can be used to assess the quality of probabilistic models such as those developed in Monte Carlo simulations for risk analyses. We also illustrate how a sensitivity analysis can be conducted within a PBA by pinching inputs to precise distributions or real values

  7. A cell-based in vitro alternative to identify skin sensitizers by gene expression

    International Nuclear Information System (INIS)

    Hooyberghs, Jef; Schoeters, Elke; Lambrechts, Nathalie; Nelissen, Inge; Witters, Hilda; Schoeters, Greet; Heuvel, Rosette van den

    2008-01-01

    The ethical and economic burden associated with animal testing for assessment of skin sensitization has triggered intensive research effort towards development and validation of alternative methods. In addition, new legislation on the registration and use of cosmetics and chemicals promote the use of suitable alternatives for hazard assessment. Our previous studies demonstrated that human CD34 + progenitor-derived dendritic cells from cord blood express specific gene profiles upon exposure to low molecular weight sensitizing chemicals. This paper presents a classification model based on this cell type which is successful in discriminating sensitizing chemicals from non-sensitizing chemicals based on transcriptome analysis of 13 genes. Expression profiles of a set of 10 sensitizers and 11 non-sensitizers were analyzed by RT-PCR using 9 different exposure conditions and a total of 73 donor samples. Based on these data a predictive dichotomous classifier for skin sensitizers has been constructed, which is referred to as . In a first step the dimensionality of the input data was reduced by selectively rejecting a number of exposure conditions and genes. Next, the generalization of a linear classifier was evaluated by a cross-validation which resulted in a prediction performance with a concordance of 89%, a specificity of 97% and a sensitivity of 82%. These results show that the present model may be a useful human in vitro alternative for further use in a test strategy towards the reduction of animal use for skin sensitization

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Jianbin Guo

    2014-07-01

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

  10. OPTIMIZATION OF THE TEMPERATURE CONTROL SCHEME FOR ROLLER COMPACTED CONCRETE DAMS BASED ON FINITE ELEMENT AND SENSITIVITY ANALYSIS METHODS

    Directory of Open Access Journals (Sweden)

    Huawei Zhou

    2016-10-01

    Full Text Available Achieving an effective combination of various temperature control measures is critical for temperature control and crack prevention of concrete dams. This paper presents a procedure for optimizing the temperature control scheme of roller compacted concrete (RCC dams that couples the finite element method (FEM with a sensitivity analysis method. In this study, seven temperature control schemes are defined according to variations in three temperature control measures: concrete placement temperature, water-pipe cooling time, and thermal insulation layer thickness. FEM is employed to simulate the equivalent temperature field and temperature stress field obtained under each of the seven designed temperature control schemes for a typical overflow dam monolith based on the actual characteristics of a RCC dam located in southwestern China. A sensitivity analysis is subsequently conducted to investigate the degree of influence each of the three temperature control measures has on the temperature field and temperature tensile stress field of the dam. Results show that the placement temperature has a substantial influence on the maximum temperature and tensile stress of the dam, and that the placement temperature cannot exceed 15 °C. The water-pipe cooling time and thermal insulation layer thickness have little influence on the maximum temperature, but both demonstrate a substantial influence on the maximum tensile stress of the dam. The thermal insulation thickness is significant for reducing the probability of cracking as a result of high thermal stress, and the maximum tensile stress can be controlled under the specification limit with a thermal insulation layer thickness of 10 cm. Finally, an optimized temperature control scheme for crack prevention is obtained based on the analysis results.

  11. Sensitivity analysis for reactivity and power density investigations in nuclear reactors

    International Nuclear Information System (INIS)

    Naguib, K.; Morcos, H.N.; Sallam, O.H.; Abdelsamei, SH.

    1993-01-01

    Sensitivity analysis theory based on the variational functional approaches was applied to evaluate sensitivities of eigenvalues and power densities due to variation of the absorber concentration in the reactor core. The practical usefulness of this method is illustrated by considering test cases. The result indicates that this method is as accurate as those obtained from direct calculations, yet it provides an economical means in saving computational time since it requires fewer calculations. The SARC-1/2 code have been written in Fortran-77 to solve this problem.3 tab. 1 fig

  12. 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

  13. An adjoint method of sensitivity analysis for residual vibrations of structures subject to impacts

    Science.gov (United States)

    Yan, Kun; Cheng, Gengdong

    2018-03-01

    For structures subject to impact loads, the residual vibration reduction is more and more important as the machines become faster and lighter. An efficient sensitivity analysis of residual vibration with respect to structural or operational parameters is indispensable for using a gradient based optimization algorithm, which reduces the residual vibration in either active or passive way. In this paper, an integrated quadratic performance index is used as the measure of the residual vibration, since it globally measures the residual vibration response and its calculation can be simplified greatly with Lyapunov equation. Several sensitivity analysis approaches for performance index were developed based on the assumption that the initial excitations of residual vibration were given and independent of structural design. Since the resulting excitations by the impact load often depend on structural design, this paper aims to propose a new efficient sensitivity analysis method for residual vibration of structures subject to impacts to consider the dependence. The new method is developed by combining two existing methods and using adjoint variable approach. Three numerical examples are carried out and demonstrate the accuracy of the proposed method. The numerical results show that the dependence of initial excitations on structural design variables may strongly affects the accuracy of sensitivities.

  14. 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.

  15. Improved analysis of Monascus pigments based on their pH-sensitive UV-Vis absorption and reactivity properties.

    Science.gov (United States)

    Shi, Kan; Chen, Gong; Pistolozzi, Marco; Xia, Fenggeng; Wu, Zhenqiang

    2016-09-01

    Monascus pigments, a mixture of azaphilones mainly composed of red, orange and yellow pigments, are usually prepared in aqueous ethanol and analysed by ultraviolet-visible (UV-Vis) spectroscopy. The pH of aqueous ethanol used during sample preparation and analysis has never been considered a key parameter to control; however, this study shows that the UV-Vis spectra and colour characteristics of the six major pigments are strongly influenced by the pH of the solvent employed. In addition, the increase of solvent pH results in a remarkable increase of the amination reaction of orange pigments with amino compounds, and at higher pH (≥ 6.0) a significant amount of orange pigment derivatives rapidly form. The consequent impact of these pH-sensitive properties on pigment analysis is further discussed. Based on the presented results, we propose that the sample preparation and analysis of Monascus pigments should be uniformly performed at low pH (≤ 2.5) to avoid variations of UV-Vis spectra and the creation of artefacts due to the occurrence of amination reactions, and ensure an accurate analysis that truly reflects pigment characteristics in the samples.

  16. Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization

    Science.gov (United States)

    Adkins, Daniel E.; McClay, Joseph L.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Souza, Renan P.; Crowley, James J.; Sullivan, Patrick F.; van den Oord, Edwin J.C.G.; Beardsley, Patrick M.

    2014-01-01

    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In the present study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate < 0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent methamphetamine levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. PMID:24034544

  17. Stochastic sensitivity analysis and Langevin simulation for neural network learning

    International Nuclear Information System (INIS)

    Koda, Masato

    1997-01-01

    A comprehensive theoretical framework is proposed for the learning of a class of gradient-type neural networks with an additive Gaussian white noise process. The study is based on stochastic sensitivity analysis techniques, and formal expressions are obtained for stochastic learning laws in terms of functional derivative sensitivity coefficients. The present method, based on Langevin simulation techniques, uses only the internal states of the network and ubiquitous noise to compute the learning information inherent in the stochastic correlation between noise signals and the performance functional. In particular, the method does not require the solution of adjoint equations of the back-propagation type. Thus, the present algorithm has the potential for efficiently learning network weights with significantly fewer computations. Application to an unfolded multi-layered network is described, and the results are compared with those obtained by using a back-propagation method

  18. 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

  19. 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.

  20. 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...

  1. Global sensitivity analysis using low-rank tensor approximations

    International Nuclear Information System (INIS)

    Konakli, Katerina; Sudret, Bruno

    2016-01-01

    In the context of global sensitivity analysis, the Sobol' indices constitute a powerful tool for assessing the relative significance of the uncertain input parameters of a model. We herein introduce a novel approach for evaluating these indices at low computational cost, by post-processing the coefficients of polynomial meta-models belonging to the class of low-rank tensor approximations. Meta-models of this class can be particularly efficient in representing responses of high-dimensional models, because the number of unknowns in their general functional form grows only linearly with the input dimension. The proposed approach is validated in example applications, where the Sobol' indices derived from the meta-model coefficients are compared to reference indices, the latter obtained by exact analytical solutions or Monte-Carlo simulation with extremely large samples. Moreover, low-rank tensor approximations are confronted to the popular polynomial chaos expansion meta-models in case studies that involve analytical rank-one functions and finite-element models pertinent to structural mechanics and heat conduction. In the examined applications, indices based on the novel approach tend to converge faster to the reference solution with increasing size of the experimental design used to build the meta-model. - Highlights: • A new method is proposed for global sensitivity analysis of high-dimensional models. • Low-rank tensor approximations (LRA) are used as a meta-modeling technique. • Analytical formulas for the Sobol' indices in terms of LRA coefficients are derived. • The accuracy and efficiency of the approach is illustrated in application examples. • LRA-based indices are compared to indices based on polynomial chaos expansions.

  2. Development and Sensitivity Analysis of a Frost Risk model based primarily on freely distributed Earth Observation data

    Science.gov (United States)

    Louka, Panagiota; Petropoulos, George; Papanikolaou, Ioannis

    2015-04-01

    The ability to map the spatiotemporal distribution of extreme climatic conditions, such as frost, is a significant tool in successful agricultural management and decision making. Nowadays, with the development of Earth Observation (EO) technology, it is possible to obtain accurately, timely and in a cost-effective way information on the spatiotemporal distribution of frost conditions, particularly over large and otherwise inaccessible areas. The present study aimed at developing and evaluating a frost risk prediction model, exploiting primarily EO data from MODIS and ASTER sensors and ancillary ground observation data. For the evaluation of our model, a region in north-western Greece was selected as test site and a detailed sensitivity analysis was implemented. The agreement between the model predictions and the observed (remotely sensed) frost frequency obtained by MODIS sensor was evaluated thoroughly. Also, detailed comparisons of the model predictions were performed against reference frost ground observations acquired from the Greek Agricultural Insurance Organization (ELGA) over a period of 10-years (2000-2010). Overall, results evidenced the ability of the model to produce reasonably well the frost conditions, following largely explainable patterns in respect to the study site and local weather conditions characteristics. Implementation of our proposed frost risk model is based primarily on satellite imagery analysis provided nowadays globally at no cost. It is also straightforward and computationally inexpensive, requiring much less effort in comparison for example to field surveying. Finally, the method is adjustable to be potentially integrated with other high resolution data available from both commercial and non-commercial vendors. Keywords: Sensitivity analysis, frost risk mapping, GIS, remote sensing, MODIS, Greece

  3. 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.

  4. On the consistency of adjoint sensitivity analysis for structural optimization of linear dynamic problems

    DEFF Research Database (Denmark)

    Jensen, Jakob Søndergaard; Nakshatrala, Praveen B.; Tortorelli, Daniel A.

    2014-01-01

    Gradient-based topology optimization typically involves thousands or millions of design variables. This makes efficient sensitivity analysis essential and for this the adjoint variable method (AVM) is indispensable. For transient problems it has been observed that the traditional AVM, based on a ...

  5. Topological sensitivity based far-field detection of elastic inclusions

    Directory of Open Access Journals (Sweden)

    Tasawar Abbas

    2018-03-01

    Full Text Available The aim of this article is to present and rigorously analyze topological sensitivity based algorithms for detection of diametrically small inclusions in an isotropic homogeneous elastic formation using single and multiple measurements of the far-field scattering amplitudes. A L2-cost functional is considered and a location indicator is constructed from its topological derivative. The performance of the indicator is analyzed in terms of the topological sensitivity for location detection and stability with respect to measurement and medium noises. It is established that the location indicator does not guarantee inclusion detection and achieves only a low resolution when there is mode-conversion in an elastic formation. Accordingly, a weighted location indicator is designed to tackle the mode-conversion phenomenon. It is substantiated that the weighted function renders the location of an inclusion stably with resolution as per Rayleigh criterion. 2000 MSC: 35R30, 35L05, 74B05, 47A52, 65J20, Keywords: Inverse elastic scattering, Elasticity imaging, Topological derivative, Resolution analysis, Stability analysis

  6. Sensitivity analysis of VERA-CS and FRAPCON coupling in a multiphysics environment

    International Nuclear Information System (INIS)

    Blakely, Cole; Zhang, Hongbin; Ban, Heng

    2018-01-01

    Highlights: •VERA-CS and FRAPCON coupling. •Uncertainty quantification and sensitivity analysis for coupled VERA-CS and FRAPCON simulations in a multiphysics environment LOTUS. -- Abstract: A demonstration and description of the LOCA Toolkit for US light water reactors (LOTUS) is presented. Through LOTUS, the core simulator VERA-CS developed by CASL is coupled with the fuel performance code FRAPCON. The coupling is performed with consistent uncertainty propagation with all model inconsistencies being well-documented. Monte Carlo sampling is performed on a single 17 × 17 fuel assembly with a three cycle depletion case. Both uncertainty quantification (UQ) and sensitivity analysis (SA) are used at multiple states within the simulation to elucidate the behavior of minimum departure from nucleate boiling ratio (MDNBR), maximum fuel centerline temperature (MFCT), and gap conductance at peak power (GCPP). The SA metrics used are the Pearson correlation coefficient, Sobol sensitivity indices, and the density-based, delta moment independent measures. Results for MDNBR show consistency among all SA measures, as well for all states throughout the fuel lifecycle. MFCT results contain consistent rankings between SA measures, but show differences throughout the lifecycle. GCPP exhibits predominantly linear relations at low and high burnup, but highly nonlinear relations at intermediate burnup due to abrupt shifts between models. Such behavior is largely undetectable to traditional regression or variance-based methods and demonstrates the utility of density-based methods.

  7. Sensitivity field distributions for segmental bioelectrical impedance analysis based on real human anatomy

    International Nuclear Information System (INIS)

    Danilov, A A; Rudnev, S G; V Vassilevski, Yu; Kramarenko, V K; Nikolaev, D V; Smirnov, A V; Salamatova, V Yu

    2013-01-01

    In this work, an adaptive unstructured tetrahedral mesh generation technology is applied for simulation of segmental bioimpedance measurements using high-resolution whole-body model of the Visible Human Project man. Sensitivity field distributions for a conventional tetrapolar, as well as eight- and ten-electrode measurement configurations are obtained. Based on the ten-electrode configuration, we suggest an algorithm for monitoring changes in the upper lung area.

  8. Sensitivity field distributions for segmental bioelectrical impedance analysis based on real human anatomy

    Science.gov (United States)

    Danilov, A. A.; Kramarenko, V. K.; Nikolaev, D. V.; Rudnev, S. G.; Salamatova, V. Yu; Smirnov, A. V.; Vassilevski, Yu V.

    2013-04-01

    In this work, an adaptive unstructured tetrahedral mesh generation technology is applied for simulation of segmental bioimpedance measurements using high-resolution whole-body model of the Visible Human Project man. Sensitivity field distributions for a conventional tetrapolar, as well as eight- and ten-electrode measurement configurations are obtained. Based on the ten-electrode configuration, we suggest an algorithm for monitoring changes in the upper lung area.

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

    Science.gov (United States)

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

    2010-01-01

    regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.

  10. 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.

  11. Stand-alone core sensitivity and uncertainty analysis of ALFRED from Monte Carlo simulations

    International Nuclear Information System (INIS)

    Pérez-Valseca, A.-D.; Espinosa-Paredes, G.; François, J.L.; Vázquez Rodríguez, A.; Martín-del-Campo, C.

    2017-01-01

    Highlights: • Methodology based on Monte Carlo simulation. • Sensitivity analysis of Lead Fast Reactor (LFR). • Uncertainty and regression analysis of LFR. • 10% change in the core inlet flow, the response in thermal power change is 0.58%. • 2.5% change in the inlet lead temperature the response is 1.87% in power. - Abstract: The aim of this paper is the sensitivity and uncertainty analysis of a Lead-Cooled Fast Reactor (LFR) based on Monte Carlo simulation of sizes up to 2000. The methodology developed in this work considers the uncertainty of sensitivities and uncertainty of output variables due to a single-input-variable variation. The Advanced Lead fast Reactor European Demonstrator (ALFRED) is analyzed to determine the behavior of the essential parameters due to effects of mass flow and temperature of liquid lead. The ALFRED core mathematical model developed in this work is fully transient, which takes into account the heat transfer in an annular fuel pellet design, the thermo-fluid in the core, and the neutronic processes, which are modeled with point kinetic with feedback fuel temperature and expansion effects. The sensitivity evaluated in terms of the relative standard deviation (RSD) showed that for 10% change in the core inlet flow, the response in thermal power change is 0.58%, and for 2.5% change in the inlet lead temperature is 1.87%. The regression analysis with mass flow rate as the predictor variable showed statistically valid cubic correlations for neutron flux and linear relationship neutron flux as a function of the lead temperature. No statistically valid correlation was observed for the reactivity as a function of the mass flow rate and for the lead temperature. These correlations are useful for the study, analysis, and design of any LFR.

  12. Risk Characterization uncertainties associated description, sensitivity analysis

    International Nuclear Information System (INIS)

    Carrillo, M.; Tovar, M.; Alvarez, J.; Arraez, M.; Hordziejewicz, I.; Loreto, I.

    2013-01-01

    The power point presentation is about risks to the estimated levels of exposure, uncertainty and variability in the analysis, sensitivity analysis, risks from exposure to multiple substances, formulation of guidelines for carcinogenic and genotoxic compounds and risk subpopulations

  13. Overview of methods for uncertainty analysis and sensitivity analysis in probabilistic risk assessment

    International Nuclear Information System (INIS)

    Iman, R.L.; Helton, J.C.

    1985-01-01

    Probabilistic Risk Assessment (PRA) is playing an increasingly important role in the nuclear reactor regulatory process. The assessment of uncertainties associated with PRA results is widely recognized as an important part of the analysis process. One of the major criticisms of the Reactor Safety Study was that its representation of uncertainty was inadequate. The desire for the capability to treat uncertainties with the MELCOR risk code being developed at Sandia National Laboratories is indicative of the current interest in this topic. However, as yet, uncertainty analysis and sensitivity analysis in the context of PRA is a relatively immature field. In this paper, available methods for uncertainty analysis and sensitivity analysis in a PRA are reviewed. This review first treats methods for use with individual components of a PRA and then considers how these methods could be combined in the performance of a complete PRA. In the context of this paper, the goal of uncertainty analysis is to measure the imprecision in PRA outcomes of interest, and the goal of sensitivity analysis is to identify the major contributors to this imprecision. There are a number of areas that must be considered in uncertainty analysis and sensitivity analysis for a PRA: (1) information, (2) systems analysis, (3) thermal-hydraulic phenomena/fission product behavior, (4) health and economic consequences, and (5) display of results. Each of these areas and the synthesis of them into a complete PRA are discussed

  14. Finite mixture models for sensitivity analysis of thermal hydraulic codes for passive safety systems analysis

    Energy Technology Data Exchange (ETDEWEB)

    Di Maio, Francesco, E-mail: francesco.dimaio@polimi.it [Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano (Italy); Nicola, Giancarlo [Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano (Italy); Zio, Enrico [Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano (Italy); Chair on System Science and Energetic Challenge Fondation EDF, Ecole Centrale Paris and Supelec, Paris (France); Yu, Yu [School of Nuclear Science and Engineering, North China Electric Power University, 102206 Beijing (China)

    2015-08-15

    Highlights: • Uncertainties of TH codes affect the system failure probability quantification. • We present Finite Mixture Models (FMMs) for sensitivity analysis of TH codes. • FMMs approximate the pdf of the output of a TH code with a limited number of simulations. • The approach is tested on a Passive Containment Cooling System of an AP1000 reactor. • The novel approach overcomes the results of a standard variance decomposition method. - Abstract: For safety analysis of Nuclear Power Plants (NPPs), Best Estimate (BE) Thermal Hydraulic (TH) codes are used to predict system response in normal and accidental conditions. The assessment of the uncertainties of TH codes is a critical issue for system failure probability quantification. In this paper, we consider passive safety systems of advanced NPPs and present a novel approach of Sensitivity Analysis (SA). The approach is based on Finite Mixture Models (FMMs) to approximate the probability density function (i.e., the uncertainty) of the output of the passive safety system TH code with a limited number of simulations. We propose a novel Sensitivity Analysis (SA) method for keeping the computational cost low: an Expectation Maximization (EM) algorithm is used to calculate the saliency of the TH code input variables for identifying those that most affect the system functional failure. The novel approach is compared with a standard variance decomposition method on a case study considering a Passive Containment Cooling System (PCCS) of an Advanced Pressurized reactor AP1000.

  15. Super-Efficiency and Sensitivity Analysis Based on Input-Oriented DEA-R

    Directory of Open Access Journals (Sweden)

    M. R. Mozaffari∗

    2012-03-01

    Full Text Available This paper suggests a method of finding super-efficiency scores and modification of input-oriented models for sensitivity analysis of decision making units. First, by using DEA-R (ratiobased DEA models in the input orientation, the models of superefficiency and also models of super-efficiency modification are suggested. Second, the worst-case scenarios are considered where the efficiency of the test DMU is deteriorating while the efficiencies of the other DMUs are improving. Then, by combining these two ideas, a model is suggested which increases the super-efficiency score and modifies the change ranges in order to preserve the performance class. In the end, the super-efficiency and change interval of efficient decision making units for 23 branches of Zone 1 of the Islamic Azad University are calculated

  16. SENSITIVITY ANALYSIS OF BUILDING STRUCTURES WITHIN THE SCOPE OF ENERGY, ENVIRONMENT AND INVESTMENT

    Directory of Open Access Journals (Sweden)

    František Kulhánek

    2015-10-01

    Full Text Available The primary objective of this paper is to prove the feasibility of sensitivity analysis with dominant weight method for structure parts of envelope of buildings inclusive of energy; ecological and financial assessments, and determination of different designs for same structural part via multi-criteria assessment with theoretical example designs ancillary. Multi-criteria assessment (MCA of different structural designs or in other word alternatives aims to find the best available alternative. The application of sensitivity analysis technique in this paper bases on dominant weighting method. In this research, to choose the best thermal insulation design in the case of that more than one projection, simultaneously, criteria of total thickness (T; heat transfer coefficient (U through the cross section; global warming potential (GWP; acid produce (AP; primary energy content (PEI non renewable and cost per m2 (C are investigated for all designs via sensitivity analysis. Three different designs for external wall (over soil which are convenient with regard to globally suggested energy features for passive house design are investigated through the mentioned six projections. By creating a given set of scenarios; depending upon the importance of each criterion, sensitivity analysis is distributed. As conclusion, uncertainty in the output of model is attributed to different sources in the model input. In this manner, determination of the best available design is achieved. The original outlook and the outlook afterwards the sensitivity analysis are visualized, that enables easily to choose the optimum design within the scope of verified components.

  17. Sensitivity Analysis for Design Optimization Integrated Software Tools, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of this proposed project is to provide a new set of sensitivity analysis theory and codes, the Sensitivity Analysis for Design Optimization Integrated...

  18. 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.

  19. 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.

  20. Sensitivity analysis of Smith's AMRV model

    International Nuclear Information System (INIS)

    Ho, Chih-Hsiang

    1995-01-01

    Multiple-expert hazard/risk assessments have considerable precedent, particularly in the Yucca Mountain site characterization studies. In this paper, we present a Bayesian approach to statistical modeling in volcanic hazard assessment for the Yucca Mountain site. Specifically, we show that the expert opinion on the site disruption parameter p is elicited on the prior distribution, π (p), based on geological information that is available. Moreover, π (p) can combine all available geological information motivated by conflicting but realistic arguments (e.g., simulation, cluster analysis, structural control, etc.). The incorporated uncertainties about the probability of repository disruption p, win eventually be averaged out by taking the expectation over π (p). We use the following priors in the analysis: priors chosen for mathematical convenience: Beta (r, s) for (r, s) = (2, 2), (3, 3), (5, 5), (2, 1), (2, 8), (8, 2), and (1, 1); and three priors motivated by expert knowledge. Sensitivity analysis is performed for each prior distribution. Estimated values of hazard based on the priors chosen for mathematical simplicity are uniformly higher than those obtained based on the priors motivated by expert knowledge. And, the model using the prior, Beta (8,2), yields the highest hazard (= 2.97 X 10 -2 ). The minimum hazard is produced by the open-quotes three-expert priorclose quotes (i.e., values of p are equally likely at 10 -3 10 -2 , and 10 -1 ). The estimate of the hazard is 1.39 x which is only about one order of magnitude smaller than the maximum value. The term, open-quotes hazardclose quotes, is defined as the probability of at least one disruption of a repository at the Yucca Mountain site by basaltic volcanism for the next 10,000 years

  1. The formation of continuous opinion dynamics based on a gambling mechanism and its sensitivity analysis

    Science.gov (United States)

    Zhu, Yueying; Alexandre Wang, Qiuping; Li, Wei; Cai, Xu

    2017-09-01

    The formation of continuous opinion dynamics is investigated based on a virtual gambling mechanism where agents fight for a limited resource. We propose a model with agents holding opinions between -1 and 1. Agents are segregated into two cliques according to the sign of their opinions. Local communication happens only when the opinion distance between corresponding agents is no larger than a pre-defined confidence threshold. Theoretical analysis regarding special cases provides a deep understanding of the roles of both the resource allocation parameter and confidence threshold in the formation of opinion dynamics. For a sparse network, the evolution of opinion dynamics is negligible in the region of low confidence threshold when the mindless agents are absent. Numerical results also imply that, in the presence of economic agents, high confidence threshold is required for apparent clustering of agents in opinion. Moreover, a consensus state is generated only when the following three conditions are satisfied simultaneously: mindless agents are absent, the resource is concentrated in one clique, and confidence threshold tends to a critical value(=1.25+2/ka ; k_a>8/3 , the average number of friends of individual agents). For fixed a confidence threshold and resource allocation parameter, the most chaotic steady state of the dynamics happens when the fraction of mindless agents is about 0.7. It is also demonstrated that economic agents are more likely to win at gambling, compared to mindless ones. Finally, the importance of three involved parameters in establishing the uncertainty of model response is quantified in terms of Latin hypercube sampling-based sensitivity analysis.

  2. Global sensitivity analysis of bogie dynamics with respect to suspension components

    Energy Technology Data Exchange (ETDEWEB)

    Mousavi Bideleh, Seyed Milad, E-mail: milad.mousavi@chalmers.se; Berbyuk, Viktor, E-mail: viktor.berbyuk@chalmers.se [Chalmers University of Technology, Department of Applied Mechanics (Sweden)

    2016-06-15

    The effects of bogie primary and secondary suspension stiffness and damping components on the dynamics behavior of a high speed train are scrutinized based on the multiplicative dimensional reduction method (M-DRM). A one-car railway vehicle model is chosen for the analysis at two levels of the bogie suspension system: symmetric and asymmetric configurations. Several operational scenarios including straight and circular curved tracks are considered, and measurement data are used as the track irregularities in different directions. Ride comfort, safety, and wear objective functions are specified to evaluate the vehicle’s dynamics performance on the prescribed operational scenarios. In order to have an appropriate cut center for the sensitivity analysis, the genetic algorithm optimization routine is employed to optimize the primary and secondary suspension components in terms of wear and comfort, respectively. The global sensitivity indices are introduced and the Gaussian quadrature integrals are employed to evaluate the simplified sensitivity indices correlated to the objective functions. In each scenario, the most influential suspension components on bogie dynamics are recognized and a thorough analysis of the results is given. The outcomes of the current research provide informative data that can be beneficial in design and optimization of passive and active suspension components for high speed train bogies.

  3. Global sensitivity analysis of bogie dynamics with respect to suspension components

    International Nuclear Information System (INIS)

    Mousavi Bideleh, Seyed Milad; Berbyuk, Viktor

    2016-01-01

    The effects of bogie primary and secondary suspension stiffness and damping components on the dynamics behavior of a high speed train are scrutinized based on the multiplicative dimensional reduction method (M-DRM). A one-car railway vehicle model is chosen for the analysis at two levels of the bogie suspension system: symmetric and asymmetric configurations. Several operational scenarios including straight and circular curved tracks are considered, and measurement data are used as the track irregularities in different directions. Ride comfort, safety, and wear objective functions are specified to evaluate the vehicle’s dynamics performance on the prescribed operational scenarios. In order to have an appropriate cut center for the sensitivity analysis, the genetic algorithm optimization routine is employed to optimize the primary and secondary suspension components in terms of wear and comfort, respectively. The global sensitivity indices are introduced and the Gaussian quadrature integrals are employed to evaluate the simplified sensitivity indices correlated to the objective functions. In each scenario, the most influential suspension components on bogie dynamics are recognized and a thorough analysis of the results is given. The outcomes of the current research provide informative data that can be beneficial in design and optimization of passive and active suspension components for high speed train bogies.

  4. High sensitivity neutron activation analysis of environmental and biological standard reference materials

    International Nuclear Information System (INIS)

    Greenberg, R.R.; Fleming, R.F.; Zeisler, R.

    1984-01-01

    Neutron activation analysis is a sensitive method with unique capabilities for the analysis of environmental and biological samples. Since it is based upon the nuclear properties of the elements, it does not suffer from many of the chemical effects that plague other methods of analysis. Analyses can be performed either with no chemical treatment of the sample (instrumentally), or with separations of the elements of interest after neutron irradiation (radiochemically). Typical examples of both types of analysis are discussed, and data obtained for a number of environmental and biological SRMs are presented. (author)

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

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  6. Pricing index-based catastrophe bonds: Part 2: Object-oriented design issues and sensitivity analysis

    Science.gov (United States)

    Unger, André J. A.

    2010-02-01

    This work is the second installment in a two-part series, and focuses on object-oriented programming methods to implement an augmented-state variable approach to aggregate the PCS index and introduce the Bermudan-style call feature into the proposed CAT bond model. The PCS index is aggregated quarterly using a discrete Asian running-sum formulation. The resulting aggregate PCS index augmented-state variable is used to specify the payoff (principle) on the CAT bond based on reinsurance layers. The purpose of the Bermudan-style call option is to allow the reinsurer to minimize their interest rate risk exposure on making fixed coupon payments under prevailing interest rates. A sensitivity analysis is performed to determine the impact of uncertainty in the frequency and magnitude of hurricanes on the price of the CAT bond. Results indicate that while the CAT bond is highly sensitive to the natural variability in the frequency of landfalling hurricanes between El Ninõ and non-El Ninõ years, it remains relatively insensitive to uncertainty in the magnitude of damages. In addition, results indicate that the maximum price of the CAT bond is insensitive to whether it is engineered to cover low frequency high magnitude events in a 'high' reinsurance layer relative to high frequency low magnitude events in a 'low' reinsurance layer. Also, while it is possible for the reinsurer to minimize their interest rate risk exposure on the fixed coupon payments, the impact of this risk on the price of the CAT bond appears small relative to the natural variability in the CAT bond price, and consequently catastrophic risk, due to uncertainty in the frequency and magnitude of landfalling hurricanes.

  7. 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.

  8. 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.

  9. Photoanode Thickness Optimization and Impedance Spectroscopic Analysis of Dye-Sensitized Solar Cells based on a Carbazole-Containing Ruthenium Dye

    Science.gov (United States)

    Choi, Jongwan; Kim, Felix Sunjoo

    2018-03-01

    We studied the influence of photoanode thickness on the photovoltaic characteristics and impedance responses of the dye-sensitized solar cells based on a ruthenium dye containing a hexyloxyl-substituted carbazole unit (Ru-HCz). As the thickness of photoanode increases from 4.2 μm to 14.8 μm, the dye-loading amount and the efficiency increase. The device with thicker photoanode shows a decrease in the efficiency due to the higher probability of recombination of electron-hole pairs before charge extraction. We also analyzed the electron-transfer and recombination characteristics as a function of photoanode thickness through detailed electrochemical impedance spectroscopy analysis.

  10. 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

  11. An efficient sampling approach for variance-based sensitivity analysis based on the law of total variance in the successive intervals without overlapping

    Science.gov (United States)

    Yun, Wanying; Lu, Zhenzhou; Jiang, Xian

    2018-06-01

    To efficiently execute the variance-based global sensitivity analysis, the law of total variance in the successive intervals without overlapping is proved at first, on which an efficient space-partition sampling-based approach is subsequently proposed in this paper. Through partitioning the sample points of output into different subsets according to different inputs, the proposed approach can efficiently evaluate all the main effects concurrently by one group of sample points. In addition, there is no need for optimizing the partition scheme in the proposed approach. The maximum length of subintervals is decreased by increasing the number of sample points of model input variables in the proposed approach, which guarantees the convergence condition of the space-partition approach well. Furthermore, a new interpretation on the thought of partition is illuminated from the perspective of the variance ratio function. Finally, three test examples and one engineering application are employed to demonstrate the accuracy, efficiency and robustness of the proposed approach.

  12. Allergen Sensitization Pattern by Sex: A Cluster Analysis in Korea.

    Science.gov (United States)

    Ohn, Jungyoon; Paik, Seung Hwan; Doh, Eun Jin; Park, Hyun-Sun; Yoon, Hyun-Sun; Cho, Soyun

    2017-12-01

    Allergens tend to sensitize simultaneously. Etiology of this phenomenon has been suggested to be allergen cross-reactivity or concurrent exposure. However, little is known about specific allergen sensitization patterns. To investigate the allergen sensitization characteristics according to gender. Multiple allergen simultaneous test (MAST) is widely used as a screening tool for detecting allergen sensitization in dermatologic clinics. We retrospectively reviewed the medical records of patients with MAST results between 2008 and 2014 in our Department of Dermatology. A cluster analysis was performed to elucidate the allergen-specific immunoglobulin (Ig)E cluster pattern. The results of MAST (39 allergen-specific IgEs) from 4,360 cases were analyzed. By cluster analysis, 39items were grouped into 8 clusters. Each cluster had characteristic features. When compared with female, the male group tended to be sensitized more frequently to all tested allergens, except for fungus allergens cluster. The cluster and comparative analysis results demonstrate that the allergen sensitization is clustered, manifesting allergen similarity or co-exposure. Only the fungus cluster allergens tend to sensitize female group more frequently than male group.

  13. Uncertainty and Sensitivity Analysis for an Ibuprofen Synthesis Model Based on Hoechst Path

    DEFF Research Database (Denmark)

    da Conceicao Do Carmo Montes, Frederico; Gernaey, Krist V.; Sin, Gürkan

    2017-01-01

    into consideration the effects of temperature, acidity, and the choice of the catalyst. Parameter estimation and uncertainty analysis were conducted on the kinetic model parameters using experimental data available in the literature. Finally, one factor at a time sensitivity analysis in the form of deviations......The pharmaceutical industry faces several challenges and barriers when implementing new or improving current pharmaceutical processes, such as competition from generic drug manufacturers and stricter regulations from the U.S. Food and Drug Administration and the European Medicine agency. The demand...... for efficient and reliable models to simulate and design/improve pharmaceutical processes is therefore increasing. For the case of ibuprofen, a well-known anti-inflammatory drug, the existing models do not include its complete synthesis path, usually referring only to one out of aset of different reactions...

  14. [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.

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

    Science.gov (United States)

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

    2014-04-01

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

  16. Acceleration and sensitivity analysis of lattice kinetic Monte Carlo simulations using parallel processing and rate constant rescaling.

    Science.gov (United States)

    Núñez, M; Robie, T; Vlachos, D G

    2017-10-28

    Kinetic Monte Carlo (KMC) simulation provides insights into catalytic reactions unobtainable with either experiments or mean-field microkinetic models. Sensitivity analysis of KMC models assesses the robustness of the predictions to parametric perturbations and identifies rate determining steps in a chemical reaction network. Stiffness in the chemical reaction network, a ubiquitous feature, demands lengthy run times for KMC models and renders efficient sensitivity analysis based on the likelihood ratio method unusable. We address the challenge of efficiently conducting KMC simulations and performing accurate sensitivity analysis in systems with unknown time scales by employing two acceleration techniques: rate constant rescaling and parallel processing. We develop statistical criteria that ensure sufficient sampling of non-equilibrium steady state conditions. Our approach provides the twofold benefit of accelerating the simulation itself and enabling likelihood ratio sensitivity analysis, which provides further speedup relative to finite difference sensitivity analysis. As a result, the likelihood ratio method can be applied to real chemistry. We apply our methodology to the water-gas shift reaction on Pt(111).

  17. An ESDIRK Method with Sensitivity Analysis Capabilities

    DEFF Research Database (Denmark)

    Kristensen, Morten Rode; Jørgensen, John Bagterp; Thomsen, Per Grove

    2004-01-01

    of the sensitivity equations. A key feature is the reuse of information already computed for the state integration, hereby minimizing the extra effort required for sensitivity integration. Through case studies the new algorithm is compared to an extrapolation method and to the more established BDF based approaches...

  18. Toward Estimating Wetland Water Level Changes Based on Hydrological Sensitivity Analysis of PALSAR Backscattering Coefficients over Different Vegetation Fields

    Directory of Open Access Journals (Sweden)

    Ting Yuan

    2015-03-01

    Full Text Available Synthetic Aperture Radar (SAR has been successfully used to map wetland’s inundation extents and types of vegetation based on the fact that the SAR backscatter signal from the wetland is mainly controlled by the wetland vegetation type and water level changes. This study describes the relation between L-band PALSAR  and seasonal water level changes obtained from Envisat altimetry over the island of Île Mbamou in the Congo Basin where two distinctly different vegetation types are found. We found positive correlations between and water level changes over the forested southern Île Mbamou whereas both positive and negative correlations were observed over the non-forested northern Île Mbamou depending on the amount of water level increase. Based on the analysis of sensitivity, we found that denser vegetation canopy leads to less sensitive  variation with respect to the water level changes regardless of forested or non-forested canopy. Furthermore, we attempted to estimate water level changes which were then compared with the Envisat altimetry and InSAR results. Our results demonstrated a potential to generate two-dimensional maps of water level changes over the wetlands, and thus may have substantial synergy with the planned Surface Water and Ocean Topography (SWOT mission.

  19. Powder stickiness in milk drying: uncertainty and sensitivity analysis for process understanding

    DEFF Research Database (Denmark)

    Ferrari, Adrián; Gutiérrez, Soledad; Sin, Gürkan

    2017-01-01

    A powder stickiness model based in the glass transition temperature (Gordon – Taylor equations) was built for a production scale milk drying process (including a spray chamber, and internal/external fluid beds). To help process understanding, the model was subjected to sensitivity analysis (SA...... for nonlinear error propagation was selected as the main UA approach. SA results show an important local sensitivity on the spray dryer, but at the end of the internal fluid bed (critical point for stickiness) minor local sensitivities were observed. Feed concentrate moisture was found as the input with major...... global sensitivity on the glass transition temperature at the critical point, so it could represent a key variable for helping on stickiness control. UA results show the major model predictions uncertainty on the spray dryer, but it does not represent a stickiness issue since the product...

  20. Sensitivity analysis: Interaction of DOE SNF and packaging materials

    International Nuclear Information System (INIS)

    Anderson, P.A.; Kirkham, R.J.; Shaber, E.L.

    1999-01-01

    A sensitivity analysis was conducted to evaluate the technical issues pertaining to possible destructive interactions between spent nuclear fuels (SNFs) and the stainless steel canisters. When issues are identified through such an analysis, they provide the technical basis for answering what if questions and, if needed, for conducting additional analyses, testing, or other efforts to resolve them in order to base the licensing on solid technical grounds. The analysis reported herein systematically assessed the chemical and physical properties and the potential interactions of the materials that comprise typical US Department of Energy (DOE) SNFs and the stainless steel canisters in which they will be stored, transported, and placed in a geologic repository for final disposition. The primary focus in each step of the analysis was to identify any possible phenomena that could potentially compromise the structural integrity of the canisters and to assess their thermodynamic feasibility

  1. 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.

  2. Dynamic Resonance Sensitivity Analysis in Wind Farms

    DEFF Research Database (Denmark)

    Ebrahimzadeh, Esmaeil; Blaabjerg, Frede; Wang, Xiongfei

    2017-01-01

    (PFs) are calculated by critical eigenvalue sensitivity analysis versus the entries of the MIMO matrix. The PF analysis locates the most exciting bus of the resonances, where can be the best location to install the passive or active filters to reduce the harmonic resonance problems. Time...

  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. Sensitivity analysis technique for application to deterministic models

    International Nuclear Information System (INIS)

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

    1987-01-01

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

  5. 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)

  6. Climatic and basin factors affecting the flood frequency curve: PART I – A simple sensitivity analysis based on the continuous simulation approach

    Directory of Open Access Journals (Sweden)

    A. M. Hashemi

    2000-01-01

    Full Text Available Regionalized and at-site flood frequency curves exhibit considerable variability in their shapes, but the factors controlling the variability (other than sampling effects are not well understood. An application of the Monte Carlo simulation-based derived distribution approach is presented in this two-part paper to explore the influence of climate, described by simulated rainfall and evapotranspiration time series, and basin factors on the flood frequency curve (ffc. The sensitivity analysis conducted in the paper should not be interpreted as reflecting possible climate changes, but the results can provide an indication of the changes to which the flood frequency curve might be sensitive. A single site Neyman Scott point process model of rainfall, with convective and stratiform cells (Cowpertwait, 1994; 1995, has been employed to generate synthetic rainfall inputs to a rainfall runoff model. The time series of the potential evapotranspiration (ETp demand has been represented through an AR(n model with seasonal component, while a simplified version of the ARNO rainfall-runoff model (Todini, 1996 has been employed to simulate the continuous discharge time series. All these models have been parameterised in a realistic manner using observed data and results from previous applications, to obtain ‘reference’ parameter sets for a synthetic case study. Subsequently, perturbations to the model parameters have been made one-at-a-time and the sensitivities of the generated annual maximum rainfall and flood frequency curves (unstandardised, and standardised by the mean have been assessed. Overall, the sensitivity analysis described in this paper suggests that the soil moisture regime, and, in particular, the probability distribution of soil moisture content at the storm arrival time, can be considered as a unifying link between the perturbations to the several parameters and their effects on the standardised and unstandardised ffcs, thus revealing the

  7. 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.

  8. A practical approach to the sensitivity analysis for kinetic Monte Carlo simulation of heterogeneous catalysis

    Science.gov (United States)

    Hoffmann, Max J.; Engelmann, Felix; Matera, Sebastian

    2017-01-01

    Lattice kinetic Monte Carlo simulations have become a vital tool for predictive quality atomistic understanding of complex surface chemical reaction kinetics over a wide range of reaction conditions. In order to expand their practical value in terms of giving guidelines for the atomic level design of catalytic systems, it is very desirable to readily evaluate a sensitivity analysis for a given model. The result of such a sensitivity analysis quantitatively expresses the dependency of the turnover frequency, being the main output variable, on the rate constants entering the model. In the past, the application of sensitivity analysis, such as degree of rate control, has been hampered by its exuberant computational effort required to accurately sample numerical derivatives of a property that is obtained from a stochastic simulation method. In this study, we present an efficient and robust three-stage approach that is capable of reliably evaluating the sensitivity measures for stiff microkinetic models as we demonstrate using the CO oxidation on RuO2(110) as a prototypical reaction. In the first step, we utilize the Fisher information matrix for filtering out elementary processes which only yield negligible sensitivity. Then we employ an estimator based on the linear response theory for calculating the sensitivity measure for non-critical conditions which covers the majority of cases. Finally, we adapt a method for sampling coupled finite differences for evaluating the sensitivity measure for lattice based models. This allows for an efficient evaluation even in critical regions near a second order phase transition that are hitherto difficult to control. The combined approach leads to significant computational savings over straightforward numerical derivatives and should aid in accelerating the nano-scale design of heterogeneous catalysts.

  9. Transport energy demand in Andorra. Assessing private car futures through sensitivity and scenario analysis

    International Nuclear Information System (INIS)

    Travesset-Baro, Oriol; Gallachóir, Brian P.Ó.; Jover, Eric; Rosas-Casals, Marti

    2016-01-01

    This paper presents a model which estimates current car fleet energy consumption in Andorra and forecasts such consumption as a reference scenario. The base-year model is built through a bottom-up methodology using vehicle registration and technical inspection data. The model forecasts energy consumption up to 2050, taking into account the fleet structure, the car survival profile, trends in activity of the various car categories, and the fuel price and income elasticities that affect car stock and total fleet activity. It provides an initial estimate of private car energy demand in Andorra and charts a baseline scenario that describes a hypothetical future based on historical trends. A local sensitivity analysis is conducted to determine the most sensitive input parameters and study the effect of its variability. In addition, the scenario analysis explores the most uncertain future aspects which can cause important variability in the results with respect to the Reference scenario and provides a broad estimate of potential energy savings related to different policy strategies. - Highlights: •A private car energy model is built using aggregated available data. •Andorra's current car fleet energy consumption is estimated and forecasted to 2050. •Potential energy savings have been estimated using sensitivity and scenario analysis.

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

    Science.gov (United States)

    Kurtulus, Bedri; Flipo, Nicolas

    2012-01-01

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

  11. 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.

  12. A Comprehensive Sensitivity Analysis of a Data Center Network with Server Virtualization for Business Continuity

    Directory of Open Access Journals (Sweden)

    Tuan Anh Nguyen

    2015-01-01

    Full Text Available Sensitivity assessment of availability for data center networks (DCNs is of paramount importance in design and management of cloud computing based businesses. Previous work has presented a performance modeling and analysis of a fat-tree based DCN using queuing theory. In this paper, we present a comprehensive availability modeling and sensitivity analysis of a DCell-based DCN with server virtualization for business continuity using stochastic reward nets (SRN. We use SRN in modeling to capture complex behaviors and dependencies of the system in detail. The models take into account (i two DCell configurations, respectively, composed of two and three physical hosts in a DCell0 unit, (ii failure modes and corresponding recovery behaviors of hosts, switches, and VMs, and VM live migration mechanism within and between DCell0s, and (iii dependencies between subsystems (e.g., between a host and VMs and between switches and VMs in the same DCell0. The constructed SRN models are analyzed in detail with regard to various metrics of interest to investigate system’s characteristics. A comprehensive sensitivity analysis of system availability is carried out in consideration of the major impacting parameters in order to observe the system’s complicated behaviors and find the bottlenecks of system availability. The analysis results show the availability improvement, capability of fault tolerance, and business continuity of the DCNs complying with DCell network topology. This study provides a basis of designing and management of DCNs for business continuity.

  13. 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

  14. Sensitivity analysis for contagion effects in social networks

    Science.gov (United States)

    VanderWeele, Tyler J.

    2014-01-01

    Analyses of social network data have suggested that obesity, smoking, happiness and loneliness all travel through social networks. Individuals exert “contagion effects” on one another through social ties and association. These analyses have come under critique because of the possibility that homophily from unmeasured factors may explain these statistical associations and because similar findings can be obtained when the same methodology is applied to height, acne and head-aches, for which the conclusion of contagion effects seems somewhat less plausible. We use sensitivity analysis techniques to assess the extent to which supposed contagion effects for obesity, smoking, happiness and loneliness might be explained away by homophily or confounding and the extent to which the critique using analysis of data on height, acne and head-aches is relevant. Sensitivity analyses suggest that contagion effects for obesity and smoking cessation are reasonably robust to possible latent homophily or environmental confounding; those for happiness and loneliness are somewhat less so. Supposed effects for height, acne and head-aches are all easily explained away by latent homophily and confounding. The methodology that has been employed in past studies for contagion effects in social networks, when used in conjunction with sensitivity analysis, may prove useful in establishing social influence for various behaviors and states. The sensitivity analysis approach can be used to address the critique of latent homophily as a possible explanation of associations interpreted as contagion effects. PMID:25580037

  15. Model-based global sensitivity analysis as applied to identification of anti-cancer drug targets and biomarkers of drug resistance in the ErbB2/3 network

    Science.gov (United States)

    Lebedeva, Galina; Sorokin, Anatoly; Faratian, Dana; Mullen, Peter; Goltsov, Alexey; Langdon, Simon P.; Harrison, David J.; Goryanin, Igor

    2012-01-01

    High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a

  16. 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.

  17. 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.

  18. Sensitivity analysis of Monju using ERANOS with JENDL-4.0

    International Nuclear Information System (INIS)

    Tamagno, P.; Van Rooijen, W. F. G.; Takeda, T.; Konomura, M.

    2012-01-01

    This paper deals with sensitivity analysis using JENDL-4.0 nuclear data applied to the Monju reactor. In 2010 the Japan Atomic Energy Agency - JAEA - released a new set of nuclear data: JENDL-4.0. This new evaluation is expected to contain improved data on actinides and covariance matrices. Covariance matrices are a key point in quantification of uncertainties due to basic nuclear data. For sensitivity analysis, the well-established ERANOS [1] code was chosen because of its integrated modules that allow users to perform a sensitivity analysis of complex reactor geometries. A JENDL-4.0 cross-section library is not available for ERANOS. Therefore a cross-section library had to be made from the original nuclear data set, available as ENDF formatted files. This is achieved by using the following codes: NJOY, CALENDF, MERGE and GECCO in order to create a library for the ECCO cell code (part of ERANOS). In order to make sure of the accuracy of the new ECCO library, two benchmark experiments have been analyzed: the MZA and MZB cores of the MOZART program measured at the ZEBRA facility in the UK. These were chosen due to their similarity to the Monju core. Using the JENDL-4.0 ECCO library we have analyzed the criticality of Monju during the restart in 2010. We have obtained good agreement with the measured criticality. Perturbation calculations have been performed between JENDL-3.3 and JENDL-4.0 based models. The isotopes 239 Pu, 238 U, 241 Am and 241 Pu account for a major part of observed differences. (authors)

  19. Experimental Design for Sensitivity Analysis of Simulation Models

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2001-01-01

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

  20. Parametric study and global sensitivity analysis for co-pyrolysis of rape straw and waste tire via variance-based decomposition.

    Science.gov (United States)

    Xu, Li; Jiang, Yong; Qiu, Rong

    2018-01-01

    In present study, co-pyrolysis behavior of rape straw, waste tire and their various blends were investigated. TG-FTIR indicated that co-pyrolysis was characterized by a four-step reaction, and H 2 O, CH, OH, CO 2 and CO groups were the main products evolved during the process. Additionally, using BBD-based experimental results, best-fit multiple regression models with high R 2 -pred values (94.10% for mass loss and 95.37% for reaction heat), which correlated explanatory variables with the responses, were presented. The derived models were analyzed by ANOVA at 95% confidence interval, F-test, lack-of-fit test and residues normal probability plots implied the models described well the experimental data. Finally, the model uncertainties as well as the interactive effect of these parameters were studied, the total-, first- and second-order sensitivity indices of operating factors were proposed using Sobol' variance decomposition. To the authors' knowledge, this is the first time global parameter sensitivity analysis has been performed in (co-)pyrolysis literature. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Jacques, J

    2005-12-15

    Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)

  3. Dye-sensitized solar cells based on purple corn sensitizers

    International Nuclear Information System (INIS)

    Phinjaturus, Kawin; Maiaugree, Wasan; Suriharn, Bhalang; Pimanpaeng, Samuk; Amornkitbamrung, Vittaya; Swatsitang, Ekaphan

    2016-01-01

    Graphical abstract: - Highlights: • Extract from husk, cob and silk of purple corn was used as a photosensitizer in DSSC. • Effect of solvents i.e. acetone, ethanol and DI water on DSSC efficiency was studied. • The highest efficiency of 1.06% was obtained in DSSC based on acetone extraction. - Abstract: Natural dye extracted from husk, cob and silk of purple corn, were used for the first time as photosensitizers in dye sensitized solar cells (DSSCs). The dye sensitized solar cells fabrication process has been optimized in terms of solvent extraction. The resulting maximal efficiency of 1.06% was obtained from purple corn husk extracted by acetone. The ultraviolet–visible (UV–vis) spectroscopy, Fourier transform infrared spectroscopy (FTIR), electrochemical impedance spectroscopy (EIS) and incident photon-to-current efficiency (IPCE) were employed to characterize the natural dye and the DSSCs.

  4. Dye-sensitized solar cells based on purple corn sensitizers

    Energy Technology Data Exchange (ETDEWEB)

    Phinjaturus, Kawin [Materials Science and Nanotechnology Program, Faculty of Science, Khon Kaen University, Khon Kaen 40002 (Thailand); Maiaugree, Wasan [Department of Physics, Faculty of Science, Khon Kaen University, Khon Kaen 40002 (Thailand); Suriharn, Bhalang [Department of Plant Science and Agricultural Resources, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002 (Thailand); Pimanpaeng, Samuk; Amornkitbamrung, Vittaya [Department of Physics, Faculty of Science, Khon Kaen University, Khon Kaen 40002 (Thailand); Integrated Nanotechnology Research Center (INRC), Department of Physics, Faculty of Science, Khon Kaen University, Khon Kaen 40002 (Thailand); Swatsitang, Ekaphan, E-mail: ekaphan@kku.ac.th [Department of Physics, Faculty of Science, Khon Kaen University, Khon Kaen 40002 (Thailand); Integrated Nanotechnology Research Center (INRC), Department of Physics, Faculty of Science, Khon Kaen University, Khon Kaen 40002 (Thailand); Nanotec-KKU Center of Excellence on Advanced Nanomaterials for Energy Production and Storage, Khon Kaen 40002 (Thailand)

    2016-09-01

    Graphical abstract: - Highlights: • Extract from husk, cob and silk of purple corn was used as a photosensitizer in DSSC. • Effect of solvents i.e. acetone, ethanol and DI water on DSSC efficiency was studied. • The highest efficiency of 1.06% was obtained in DSSC based on acetone extraction. - Abstract: Natural dye extracted from husk, cob and silk of purple corn, were used for the first time as photosensitizers in dye sensitized solar cells (DSSCs). The dye sensitized solar cells fabrication process has been optimized in terms of solvent extraction. The resulting maximal efficiency of 1.06% was obtained from purple corn husk extracted by acetone. The ultraviolet–visible (UV–vis) spectroscopy, Fourier transform infrared spectroscopy (FTIR), electrochemical impedance spectroscopy (EIS) and incident photon-to-current efficiency (IPCE) were employed to characterize the natural dye and the DSSCs.

  5. 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.

  6. Bead-based competitive fluorescence immunoassay for sensitive and rapid diagnosis of cyanotoxin risk in drinking water.

    Science.gov (United States)

    Yu, Hye-Weon; Jang, Am; Kim, Lan Hee; Kim, Sung-Jo; Kim, In S

    2011-09-15

    Due to the increased occurrence of cyanobacterial blooms and their toxins in drinking water sources, effective management based on a sensitive and rapid analytical method is in high demand for security of safe water sources and environmental human health. Here, a competitive fluorescence immunoassay of microcystin-LR (MCYST-LR) is developed in an attempt to improve the sensitivity, analysis time, and ease-of-manipulation of analysis. To serve this aim, a bead-based suspension assay was introduced based on two major sensing elements: an antibody-conjugated quantum dot (QD) detection probe and an antigen-immobilized magnetic bead (MB) competitor. The assay was composed of three steps: the competitive immunological reaction of QD detection probes against analytes and MB competitors, magnetic separation and washing, and the optical signal generation of QDs. The fluorescence intensity was found to be inversely proportional to the MCYST-LR concentration. Under optimized conditions, the proposed assay performed well for the identification and quantitative analysis of MCYST-LR (within 30 min in the range of 0.42-25 μg/L, with a limit of detection of 0.03 μg/L). It is thus expected that this enhanced assay can contribute both to the sensitive and rapid diagnosis of cyanotoxin risk in drinking water and effective management procedures.

  7. Life cycle assessment of Italian citrus-based products. Sensitivity analysis and improvement scenarios.

    Science.gov (United States)

    Beccali, Marco; Cellura, Maurizio; Iudicello, Maria; Mistretta, Marina

    2010-07-01

    Though many studies concern the agro-food sector in the EU and Italy, and its environmental impacts, literature is quite lacking in works regarding LCA application on citrus products. This paper represents one of the first studies on the environmental impacts of citrus products in order to suggest feasible strategies and actions to improve their environmental performance. In particular, it is part of a research aimed to estimate environmental burdens associated with the production of the following citrus-based products: essential oil, natural juice and concentrated juice from oranges and lemons. The life cycle assessment of these products, published in a previous paper, had highlighted significant environmental issues in terms of energy consumption, associated CO(2) emissions, and water consumption. Starting from such results the authors carry out an improvement analysis of the assessed production system, whereby sustainable scenarios for saving water and energy are proposed to reduce environmental burdens of the examined production system. In addition, a sensitivity analysis to estimate the effects of the chosen methods will be performed, giving data on the outcome of the study. Uncertainty related to allocation methods, secondary data sources, and initial assumptions on cultivation, transport modes, and waste management is analysed. The results of the performed analyses allow stating that every assessed eco-profile is differently influenced by the uncertainty study. Different assumptions on initial data and methods showed very sensible variations in the energy and environmental performances of the final products. Besides, the results show energy and environmental benefits that clearly state the improvement of the products eco-profile, by reusing purified water use for irrigation, using the railway mode for the delivery of final products, when possible, and adopting efficient technologies, as the mechanical vapour recompression, in the pasteurisation and

  8. An adaptive Mantel-Haenszel test for sensitivity analysis in observational studies.

    Science.gov (United States)

    Rosenbaum, Paul R; Small, Dylan S

    2017-06-01

    In a sensitivity analysis in an observational study with a binary outcome, is it better to use all of the data or to focus on subgroups that are expected to experience the largest treatment effects? The answer depends on features of the data that may be difficult to anticipate, a trade-off between unknown effect-sizes and known sample sizes. We propose a sensitivity analysis for an adaptive test similar to the Mantel-Haenszel test. The adaptive test performs two highly correlated analyses, one focused analysis using a subgroup, one combined analysis using all of the data, correcting for multiple testing using the joint distribution of the two test statistics. Because the two component tests are highly correlated, this correction for multiple testing is small compared with, for instance, the Bonferroni inequality. The test has the maximum design sensitivity of two component tests. A simulation evaluates the power of a sensitivity analysis using the adaptive test. Two examples are presented. An R package, sensitivity2x2xk, implements the procedure. © 2016, The International Biometric Society.

  9. 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.

  10. 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

  11. Sensitivity analysis of the energy demand of existing buildings based on the Danish Building and Dwelling Register

    DEFF Research Database (Denmark)

    Nielsen, Anker; Wittchen, Kim Bjarne; Bertelsen, Niels Haldor

    2014-01-01

    performance certificate. The Danish Building Research Institute has described a method that can be applied for estimating the energy demand of dwellings. This is based on the information in the Danish Building and Dwelling Register and requirements in the Danish Building Regulations from the year......The EU Directive on the Energy Performance of Buildings requires that energy certification of buildings should be implemented in Denmark so that houses that are sold or let should have an energy performance certificate. The result is that only a small part of existing houses has an energy...... of construction of the house. The result is an estimate of the energy demand of each building with a variation. This makes it possible to make an automatic classification of all buildings. The paper discusses the uncertainties and makes a sensitivity analysis to find the important parameters. The variations...

  12. A generalized matching law analysis of cocaine vs. food choice in rhesus monkeys: effects of candidate 'agonist-based' medications on sensitivity to reinforcement.

    Science.gov (United States)

    Hutsell, Blake A; Negus, S Stevens; Banks, Matthew L

    2015-01-01

    We have previously demonstrated reductions in cocaine choice produced by either continuous 14-day phendimetrazine and d-amphetamine treatment or removing cocaine availability under a cocaine vs. food choice procedure in rhesus monkeys. The aim of the present investigation was to apply the concatenated generalized matching law (GML) to cocaine vs. food choice dose-effect functions incorporating sensitivity to both the relative magnitude and price of each reinforcer. Our goal was to determine potential behavioral mechanisms underlying pharmacological treatment efficacy to decrease cocaine choice. A multi-model comparison approach was used to characterize dose- and time-course effects of both pharmacological and environmental manipulations on sensitivity to reinforcement. GML models provided an excellent fit of the cocaine choice dose-effect functions in individual monkeys. Reductions in cocaine choice by both pharmacological and environmental manipulations were principally produced by systematic decreases in sensitivity to reinforcer price and non-systematic changes in sensitivity to reinforcer magnitude. The modeling approach used provides a theoretical link between the experimental analysis of choice and pharmacological treatments being evaluated as candidate 'agonist-based' medications for cocaine addiction. The analysis suggests that monoamine releaser treatment efficacy to decrease cocaine choice was mediated by selectively increasing the relative price of cocaine. Overall, the net behavioral effect of these pharmacological treatments was to increase substitutability of food pellets, a nondrug reinforcer, for cocaine. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  13. A double-loop adaptive sampling approach for sensitivity-free dynamic reliability analysis

    International Nuclear Information System (INIS)

    Wang, Zequn; Wang, Pingfeng

    2015-01-01

    Dynamic reliability measures reliability of an engineered system considering time-variant operation condition and component deterioration. Due to high computational costs, conducting dynamic reliability analysis at an early system design stage remains challenging. This paper presents a confidence-based meta-modeling approach, referred to as double-loop adaptive sampling (DLAS), for efficient sensitivity-free dynamic reliability analysis. The DLAS builds a Gaussian process (GP) model sequentially to approximate extreme system responses over time, so that Monte Carlo simulation (MCS) can be employed directly to estimate dynamic reliability. A generic confidence measure is developed to evaluate the accuracy of dynamic reliability estimation while using the MCS approach based on developed GP models. A double-loop adaptive sampling scheme is developed to efficiently update the GP model in a sequential manner, by considering system input variables and time concurrently in two sampling loops. The model updating process using the developed sampling scheme can be terminated once the user defined confidence target is satisfied. The developed DLAS approach eliminates computationally expensive sensitivity analysis process, thus substantially improves the efficiency of dynamic reliability analysis. Three case studies are used to demonstrate the efficacy of DLAS for dynamic reliability analysis. - Highlights: • Developed a novel adaptive sampling approach for dynamic reliability analysis. • POD Developed a new metric to quantify the accuracy of dynamic reliability estimation. • Developed a new sequential sampling scheme to efficiently update surrogate models. • Three case studies were used to demonstrate the efficacy of the new approach. • Case study results showed substantially enhanced efficiency with high accuracy

  14. An efficient sensitivity analysis method for modified geometry of Macpherson suspension based on Pearson correlation coefficient

    Science.gov (United States)

    Shojaeefard, Mohammad Hasan; Khalkhali, Abolfazl; Yarmohammadisatri, Sadegh

    2017-06-01

    The main purpose of this paper is to propose a new method for designing Macpherson suspension, based on the Sobol indices in terms of Pearson correlation which determines the importance of each member on the behaviour of vehicle suspension. The formulation of dynamic analysis of Macpherson suspension system is developed using the suspension members as the modified links in order to achieve the desired kinematic behaviour. The mechanical system is replaced with an equivalent constrained links and then kinematic laws are utilised to obtain a new modified geometry of Macpherson suspension. The equivalent mechanism of Macpherson suspension increased the speed of analysis and reduced its complexity. The ADAMS/CAR software is utilised to simulate a full vehicle, Renault Logan car, in order to analyse the accuracy of modified geometry model. An experimental 4-poster test rig is considered for validating both ADAMS/CAR simulation and analytical geometry model. Pearson correlation coefficient is applied to analyse the sensitivity of each suspension member according to vehicle objective functions such as sprung mass acceleration, etc. Besides this matter, the estimation of Pearson correlation coefficient between variables is analysed in this method. It is understood that the Pearson correlation coefficient is an efficient method for analysing the vehicle suspension which leads to a better design of Macpherson suspension system.

  15. 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.

  16. Dithiafulvene-based organic sensitizers using pyridine as the acceptor for dye-sensitized solar cells

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, Jun; Cao, Yaxiong; Liang, Xiaozhong; Zheng, Jingxia; Zhang, Fang [Ministry of Education Key Laboratory of Interface Science and Engineering in Advanced Materials, Research Center of Advanced Materials Science and Technology, Taiyuan University of Technology, Taiyuan 030024 (China); Wei, Shuxian; Lu, Xiaoqing [College of Science, China University of Petroleum, Qingdao, Shandong 266555 (China); Guo, Kunpeng, E-mail: guokunpeng@tyut.edu.cn [Ministry of Education Key Laboratory of Interface Science and Engineering in Advanced Materials, Research Center of Advanced Materials Science and Technology, Taiyuan University of Technology, Taiyuan 030024 (China); Yang, Shihe, E-mail: chsyang@ust.hk [Ministry of Education Key Laboratory of Interface Science and Engineering in Advanced Materials, Research Center of Advanced Materials Science and Technology, Taiyuan University of Technology, Taiyuan 030024 (China); Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong (China)

    2017-05-01

    Three dithiafulvene-based metal-free organic sensitizers all using pyridine as the acceptor but with different π-bridges of phenyl (DTF-Py1), thienyl (DTF-Py2) and phenyl-thienyl (DTF-Py3) have been designed, synthesized and used as photosensitizers for dye-sensitized solar cells (DSCs). Introducing thienyl unit into the π-bridge, as well as extension of the π-bridge can dramatically improve their light harvesting ability and suppress the electron recombination, thus uplifting the performance of DSCs. The overall power conversion efficiency of DSC based on DTF-Py3 shows the highest efficiency of 2.61% with a short-circuit photocurrent density of 7.99 mA cm{sup -2}, an open-circuit photovoltage of 630 mV, and a fill factor of 0.52, under standard global AM 1.5 solar light condition. More importantly, the long-term stability of the DTF-Py3 based DSCs under 500 h light-soaking has been demonstrated. - Highlights: • Dithiafulvene sensitizers using pyridine ring as the acceptor were synthesized for the first time. • The power conversion efficiency of 2.61% was obtained for DTF-Py3 sensitized cell. • DTF-Py3 loaded TiO{sub 2} film shows improved light harvesting ability and suppressed electron recombination.

  17. Variance-based Sensitivity Analysis of Large-scale Hydrological Model to Prepare an Ensemble-based SWOT-like Data Assimilation Experiments

    Science.gov (United States)

    Emery, C. M.; Biancamaria, S.; Boone, A. A.; Ricci, S. M.; Garambois, P. A.; Decharme, B.; Rochoux, M. C.

    2015-12-01

    Land Surface Models (LSM) coupled with River Routing schemes (RRM), are used in Global Climate Models (GCM) to simulate the continental part of the water cycle. They are key component of GCM as they provide boundary conditions to atmospheric and oceanic models. However, at global scale, errors arise mainly from simplified physics, atmospheric forcing, and input parameters. More particularly, those used in RRM, such as river width, depth and friction coefficients, are difficult to calibrate and are mostly derived from geomorphologic relationships, which may not always be realistic. In situ measurements are then used to calibrate these relationships and validate the model, but global in situ data are very sparse. Additionally, due to the lack of existing global river geomorphology database and accurate forcing, models are run at coarse resolution. This is typically the case of the ISBA-TRIP model used in this study.A complementary alternative to in-situ data are satellite observations. In this regard, the Surface Water and Ocean Topography (SWOT) satellite mission, jointly developed by NASA/CNES/CSA/UKSA and scheduled for launch around 2020, should be very valuable to calibrate RRM parameters. It will provide maps of water surface elevation for rivers wider than 100 meters over continental surfaces in between 78°S and 78°N and also direct observation of river geomorphological parameters such as width ans slope.Yet, before assimilating such kind of data, it is needed to analyze RRM temporal sensitivity to time-constant parameters. This study presents such analysis over large river basins for the TRIP RRM. Model output uncertainty, represented by unconditional variance, is decomposed into ordered contribution from each parameter. Doing a time-dependent analysis allows then to identify to which parameters modeled water level and discharge are the most sensitive along a hydrological year. The results show that local parameters directly impact water levels, while

  18. 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.

  19. 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.

  20. Sensitivity analysis of U238 cross section in thermal nuclear systems

    International Nuclear Information System (INIS)

    Amorim, E.S. do; D'Oliveira, A.B.; Oliveira, E.C. de; Moura Neto, C. de.

    1980-01-01

    A sensitivity analysis system is developed for assessing the implication of uncertainties in nuclear data and related computational methods for light water power reactor. Sensitivies, at equilibrium cycle condition, are carried out for the few group macroscopic cross section of the U 238 with respect to their 35 group microscopic absorption cross section using the batch depletion code SENTEAV similar to those calculation methods used in the industry. This investigation indicates that improvements are requested on specific range of energy. These results point out the direction for worth while experimental measurements based on an analysis of costs and economic benefits. (Author) [pt

  1. 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.

  2. Emissivity compensated spectral pyrometry—algorithm and sensitivity analysis

    International Nuclear Information System (INIS)

    Hagqvist, Petter; Sikström, Fredrik; Christiansson, Anna-Karin; Lennartson, Bengt

    2014-01-01

    In order to solve the problem of non-contact temperature measurements on an object with varying emissivity, a new method is herein described and evaluated. The method uses spectral radiance measurements and converts them to temperature readings. It proves to be resilient towards changes in spectral emissivity and tolerates noisy spectral measurements. It is based on an assumption of smooth changes in emissivity and uses historical values of spectral emissivity and temperature for estimating current spectral emissivity. The algorithm, its constituent steps and accompanying parameters are described and discussed. A thorough sensitivity analysis of the method is carried out through simulations. No rigorous instrument calibration is needed for the presented method and it is therefore industrially tractable. (paper)

  3. Comparative analysis of methicillin-sensitive and resistant Staphylococcus aureus exposed to emodin based on proteomic profiling.

    Science.gov (United States)

    Ji, Xiaoyu; Liu, Xiaoqiang; Peng, Yuanxia; Zhan, Ruoting; Xu, Hui; Ge, Xijin

    2017-12-09

    Emodin has a strong antibacterial activity, including methicillin-resistant Staphylococcus aureus (MRSA). However, the mechanism by which emodin induces growth inhibition against MRSA remains unclear. In this study, the isobaric tags for relative and absolute quantitation (iTRAQ) proteomics approach was used to investigate the modes of action of emodin on a MRSA isolate and methicillin-sensitive S. aureus ATCC29213(MSSA). Proteomic analysis showed that expression levels of 145 and 122 proteins were changed significantly in MRSA and MSSA, respectively, after emodin treatment. Comparative analysis of the functions of differentially expressed proteins between the two strains was performed via bioinformatics tools blast2go and STRING database. Proteins related to pyruvate pathway imbalance induction, protein synthesis inhibition, and DNA synthesis suppression were found in both methicillin-sensitive and resistant strains. Moreover, Interference proteins related to membrane damage mechanism were also observed in MRSA. Our findings indicate that emodin is a potential antibacterial agent targeting MRSA via multiple mechanisms. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Damage Detection Sensitivity of a Vehicle-based Bridge Health Monitoring System

    Science.gov (United States)

    Miyamoto, Ayaho; Yabe, Akito; Lúcio, Válter J. G.

    2017-05-01

    As one solution to the problem for condition assessment of existing short and medium span (10-30m) reinforced/prestressed concrete bridges, a new monitoring method using a public bus as part of a public transit system (called “Bus monitoring system”) was proposed, along with safety indices, namely, “characteristic deflection”, which is relatively free from the influence of dynamic disturbances due to such factors as the roughness of the road surface, and a structural anomaly parameter. In this study, to evaluate the practicality of the newly developed bus monitoring system, it has been field-tested over a period of about four years by using an in-service fixed-route bus operating on a bus route in the city of Ube, Yamaguchi Prefecture, Japan. In here, although there are some useful monitoring methods for short and medium span bridges based on the qualitative or quantitative information, the sensitivity of damage detection was newly discussed for safety assessment based on long term health monitoring data. The verification results thus obtained are also described in this paper, and also evaluates the sensitivity of the “characteristic deflection”, which is a bridge (health) condition indicator used by the bus monitoring system, in damage detection. Sensitivity of “characteristic deflection” is verified by introducing artificial damage into a bridge that has ended its service life and is awaiting removal. Furthermore, the sensitivity of “characteristic deflection” is verified by 3D FEM analysis.

  5. Impedance-based analysis and study of phase sensitivity in slow-wave two-beam accelerators

    International Nuclear Information System (INIS)

    Wurtele, J.S.; Whittum, D.H.; Sessler, A.M.

    1992-06-01

    This paper presents a new formalism which makes the analysis and understanding of both the relativistic klystron (RK) and the standing-wave free-electron laser (SWFEL) two-beam accelerator (TBA) available to a wide audience of accelerator physicists. A ''coupling impedance'' for both the RK and SWFEWL is introduced, which can include realistic cavity features, such as beam and vacuum ports, in a simple manner. The RK and SWFEL macroparticle equations, which govern the energy and phase evolution of successive bunches in the beam, are of identical form, differing only by multiplicative factors. Expressions are derived for the phase and amplitude sensitivities of the TBA schemes to errors (shot-to-shot jitter) in current and energy. The analysis allows, for the first time, relative comparisons of the RK and the SWFEL TBAs

  6. 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.

  7. 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)

  8. 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

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

    International Nuclear Information System (INIS)

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

    2004-01-01

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

  10. Sensitive Spectroscopic Analysis of Biomarkers in Exhaled Breath

    Science.gov (United States)

    Bicer, A.; Bounds, J.; Zhu, F.; Kolomenskii, A. A.; Kaya, N.; Aluauee, E.; Amani, M.; Schuessler, H. A.

    2018-06-01

    We have developed a novel optical setup which is based on a high finesse cavity and absorption laser spectroscopy in the near-IR spectral region. In pilot experiments, spectrally resolved absorption measurements of biomarkers in exhaled breath, such as methane and acetone, were carried out using cavity ring-down spectroscopy (CRDS). With a 172-cm-long cavity, an efficient optical path of 132 km was achieved. The CRDS technique is well suited for such measurements due to its high sensitivity and good spectral resolution. The detection limits for methane of 8 ppbv and acetone of 2.1 ppbv with spectral sampling of 0.005 cm-1 were achieved, which allowed to analyze multicomponent gas mixtures and to observe absorption peaks of 12CH4 and 13CH4. Further improvements of the technique have the potential to realize diagnostics of health conditions based on a multicomponent analysis of breath samples.

  11. Sensitivity analysis of Monju using ERANOS with JENDL-4.0

    Energy Technology Data Exchange (ETDEWEB)

    Tamagno, P. [Institut National des Sciences et Techniques Nucleaires, INSTN - Point Courrier no 35, Centre CEA de Saclay, F-91191 Gif-sur-Yvette Cedex (France); Van Rooijen, W. F. G.; Takeda, T. [Research Inst. of Nuclear Engineering, Univ. of Fukui, Kanawa-cho 1-2-4, T914-0055 Fukui-ken, Tsuruga-shi (Japan); Konomura, M. [Japan Atomic Energy Agency, FBR Plant Engineering Center, Shiraki 1, 919-1279 Fukui-ken, Tsuruga-shi (Japan)

    2012-07-01

    This paper deals with sensitivity analysis using JENDL-4.0 nuclear data applied to the Monju reactor. In 2010 the Japan Atomic Energy Agency - JAEA - released a new set of nuclear data: JENDL-4.0. This new evaluation is expected to contain improved data on actinides and covariance matrices. Covariance matrices are a key point in quantification of uncertainties due to basic nuclear data. For sensitivity analysis, the well-established ERANOS [1] code was chosen because of its integrated modules that allow users to perform a sensitivity analysis of complex reactor geometries. A JENDL-4.0 cross-section library is not available for ERANOS. Therefore a cross-section library had to be made from the original nuclear data set, available as ENDF formatted files. This is achieved by using the following codes: NJOY, CALENDF, MERGE and GECCO in order to create a library for the ECCO cell code (part of ERANOS). In order to make sure of the accuracy of the new ECCO library, two benchmark experiments have been analyzed: the MZA and MZB cores of the MOZART program measured at the ZEBRA facility in the UK. These were chosen due to their similarity to the Monju core. Using the JENDL-4.0 ECCO library we have analyzed the criticality of Monju during the restart in 2010. We have obtained good agreement with the measured criticality. Perturbation calculations have been performed between JENDL-3.3 and JENDL-4.0 based models. The isotopes {sup 239}Pu, {sup 238}U, {sup 241}Am and {sup 241}Pu account for a major part of observed differences. (authors)

  12. Sensitivity analysis on the effect of software-induced common cause failure probability in the computer-based reactor trip system unavailability

    International Nuclear Information System (INIS)

    Kamyab, Shahabeddin; Nematollahi, Mohammadreza; Shafiee, Golnoush

    2013-01-01

    Highlights: ► Importance and sensitivity analysis has been performed for a digitized reactor trip system. ► The results show acceptable trip unavailability, for software failure probabilities below 1E −4 . ► However, the value of Fussell–Vesley indicates that software common cause failure is still risk significant. ► Diversity and effective test is founded beneficial to reduce software contribution. - Abstract: The reactor trip system has been digitized in advanced nuclear power plants, since the programmable nature of computer based systems has a number of advantages over non-programmable systems. However, software is still vulnerable to common cause failure (CCF). Residual software faults represent a CCF concern, which threat the implemented achievements. This study attempts to assess the effectiveness of so-called defensive strategies against software CCF with respect to reliability. Sensitivity analysis has been performed by re-quantifying the models upon changing the software failure probability. Importance measures then have been estimated in order to reveal the specific contribution of software CCF in the trip failure probability. The results reveal the importance and effectiveness of signal and software diversity as applicable strategies to ameliorate inefficiencies due to software CCF in the reactor trip system (RTS). No significant change has been observed in the rate of RTS failure probability for the basic software CCF greater than 1 × 10 −4 . However, the related Fussell–Vesley has been greater than 0.005, for the lower values. The study concludes that consideration of risk associated with the software based systems is a multi-variant function which requires compromising among them in more precise and comprehensive studies

  13. 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

  14. Implementation and Optimization of GPU-Based Static State Security Analysis in Power Systems

    Directory of Open Access Journals (Sweden)

    Yong Chen

    2017-01-01

    Full Text Available Static state security analysis (SSSA is one of the most important computations to check whether a power system is in normal and secure operating state. It is a challenge to satisfy real-time requirements with CPU-based concurrent methods due to the intensive computations. A sensitivity analysis-based method with Graphics processing unit (GPU is proposed for power systems, which can reduce calculation time by 40% compared to the execution on a 4-core CPU. The proposed method involves load flow analysis and sensitivity analysis. In load flow analysis, a multifrontal method for sparse LU factorization is explored on GPU through dynamic frontal task scheduling between CPU and GPU. The varying matrix operations during sensitivity analysis on GPU are highly optimized in this study. The results of performance evaluations show that the proposed GPU-based SSSA with optimized matrix operations can achieve a significant reduction in computation time.

  15. Complex finite element sensitivity method for creep analysis

    International Nuclear Information System (INIS)

    Gomez-Farias, Armando; Montoya, Arturo; Millwater, Harry

    2015-01-01

    The complex finite element method (ZFEM) has been extended to perform sensitivity analysis for mechanical and structural systems undergoing creep deformation. ZFEM uses a complex finite element formulation to provide shape, material, and loading derivatives of the system response, providing an insight into the essential factors which control the behavior of the system as a function of time. A complex variable-based quadrilateral user element (UEL) subroutine implementing the power law creep constitutive formulation was incorporated within the Abaqus commercial finite element software. The results of the complex finite element computations were verified by comparing them to the reference solution for the steady-state creep problem of a thick-walled cylinder in the power law creep range. A practical application of the ZFEM implementation to creep deformation analysis is the calculation of the skeletal point of a notched bar test from a single ZFEM run. In contrast, the standard finite element procedure requires multiple runs. The value of the skeletal point is that it identifies the location where the stress state is accurate, regardless of the certainty of the creep material properties. - Highlights: • A novel finite element sensitivity method (ZFEM) for creep was introduced. • ZFEM has the capability to calculate accurate partial derivatives. • ZFEM can be used for identification of the skeletal point of creep structures. • ZFEM can be easily implemented in a commercial software, e.g. Abaqus. • ZFEM results were shown to be in excellent agreement with analytical solutions

  16. Estimating the Capacity of Urban Transportation Networks with an Improved Sensitivity Based Method

    Directory of Open Access Journals (Sweden)

    Muqing Du

    2015-01-01

    Full Text Available The throughput of a given transportation network is always of interest to the traffic administrative department, so as to evaluate the benefit of the transportation construction or expansion project before its implementation. The model of the transportation network capacity formulated as a mathematic programming with equilibrium constraint (MPEC well defines this problem. For practical applications, a modified sensitivity analysis based (SAB method is developed to estimate the solution of this bilevel model. The high-efficient origin-based (OB algorithm is extended for the precise solution of the combined model which is integrated in the network capacity model. The sensitivity analysis approach is also modified to simplify the inversion of the Jacobian matrix in large-scale problems. The solution produced in every iteration of SAB is restrained to be feasible to guarantee the success of the heuristic search. From the numerical experiments, the accuracy of the derivatives for the linear approximation could significantly affect the converging of the SAB method. The results also show that the proposed method could obtain good suboptimal solutions from different starting points in the test examples.

  17. Uncertainty Analysis of Few Group Cross Sections Based on Generalized Perturbation Theory

    International Nuclear Information System (INIS)

    Han, Tae Young; Lee, Hyun Chul; Noh, Jae Man

    2014-01-01

    In this paper, the methodology of the sensitivity and uncertainty analysis code based on GPT was described and the preliminary verification calculations on the PMR200 pin cell problem were carried out. As a result, they are in a good agreement when compared with the results by TSUNAMI. From this study, it is expected that MUSAD code based on GPT can produce the uncertainty of the homogenized few group microscopic cross sections for a core simulator. For sensitivity and uncertainty analyses for general core responses, a two-step method is available and it utilizes the generalized perturbation theory (GPT) for homogenized few group cross sections in the first step and stochastic sampling method for general core responses in the second step. The uncertainty analysis procedure based on GPT in the first step needs the generalized adjoint solution from a cell or lattice code. For this, the generalized adjoint solver has been integrated into DeCART in our previous work. In this paper, MUSAD (Modues of Uncertainty and Sensitivity Analysis for DeCART) code based on the classical perturbation theory was expanded to the function of the sensitivity and uncertainty analysis for few group cross sections based on GPT. First, the uncertainty analysis method based on GPT was described and, in the next section, the preliminary results of the verification calculation on a VHTR pin cell problem were compared with the results by TSUNAMI of SCALE 6.1

  18. Sensitivity analysis for the effects of multiple unmeasured confounders.

    Science.gov (United States)

    Groenwold, Rolf H H; Sterne, Jonathan A C; Lawlor, Debbie A; Moons, Karel G M; Hoes, Arno W; Tilling, Kate

    2016-09-01

    Observational studies are prone to (unmeasured) confounding. Sensitivity analysis of unmeasured confounding typically focuses on a single unmeasured confounder. The purpose of this study was to assess the impact of multiple (possibly weak) unmeasured confounders. Simulation studies were performed based on parameters estimated from the British Women's Heart and Health Study, including 28 measured confounders and assuming no effect of ascorbic acid intake on mortality. In addition, 25, 50, or 100 unmeasured confounders were simulated, with various mutual correlations and correlations with measured confounders. The correlated unmeasured confounders did not need to be strongly associated with exposure and outcome to substantially bias the exposure-outcome association at interest, provided that there are sufficiently many unmeasured confounders. Correlations between unmeasured confounders, in addition to the strength of their relationship with exposure and outcome, are key drivers of the magnitude of unmeasured confounding and should be considered in sensitivity analyses. However, if the unmeasured confounders are correlated with measured confounders, the bias yielded by unmeasured confounders is partly removed through adjustment for the measured confounders. Discussions of the potential impact of unmeasured confounding in observational studies, and sensitivity analyses to examine this, should focus on the potential for the joint effect of multiple unmeasured confounders to bias results. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. An introduction to sensitivity analysis for unobserved confounding in nonexperimental prevention research.

    Science.gov (United States)

    Liu, Weiwei; Kuramoto, S Janet; Stuart, Elizabeth A

    2013-12-01

    Despite the fact that randomization is the gold standard for estimating causal relationships, many questions in prevention science are often left to be answered through nonexperimental studies because randomization is either infeasible or unethical. While methods such as propensity score matching can adjust for observed confounding, unobserved confounding is the Achilles heel of most nonexperimental studies. This paper describes and illustrates seven sensitivity analysis techniques that assess the sensitivity of study results to an unobserved confounder. These methods were categorized into two groups to reflect differences in their conceptualization of sensitivity analysis, as well as their targets of interest. As a motivating example, we examine the sensitivity of the association between maternal suicide and offspring's risk for suicide attempt hospitalization. While inferences differed slightly depending on the type of sensitivity analysis conducted, overall, the association between maternal suicide and offspring's hospitalization for suicide attempt was found to be relatively robust to an unobserved confounder. The ease of implementation and the insight these analyses provide underscores sensitivity analysis techniques as an important tool for nonexperimental studies. The implementation of sensitivity analysis can help increase confidence in results from nonexperimental studies and better inform prevention researchers and policy makers regarding potential intervention targets.

  20. Missing data in clinical trials: control-based mean imputation and sensitivity analysis.

    Science.gov (United States)

    Mehrotra, Devan V; Liu, Fang; Permutt, Thomas

    2017-09-01

    In some randomized (drug versus placebo) clinical trials, the estimand of interest is the between-treatment difference in population means of a clinical endpoint that is free from the confounding effects of "rescue" medication (e.g., HbA1c change from baseline at 24 weeks that would be observed without rescue medication regardless of whether or when the assigned treatment was discontinued). In such settings, a missing data problem arises if some patients prematurely discontinue from the trial or initiate rescue medication while in the trial, the latter necessitating the discarding of post-rescue data. We caution that the commonly used mixed-effects model repeated measures analysis with the embedded missing at random assumption can deliver an exaggerated estimate of the aforementioned estimand of interest. This happens, in part, due to implicit imputation of an overly optimistic mean for "dropouts" (i.e., patients with missing endpoint data of interest) in the drug arm. We propose an alternative approach in which the missing mean for the drug arm dropouts is explicitly replaced with either the estimated mean of the entire endpoint distribution under placebo (primary analysis) or a sequence of increasingly more conservative means within a tipping point framework (sensitivity analysis); patient-level imputation is not required. A supplemental "dropout = failure" analysis is considered in which a common poor outcome is imputed for all dropouts followed by a between-treatment comparison using quantile regression. All analyses address the same estimand and can adjust for baseline covariates. Three examples and simulation results are used to support our recommendations. Copyright © 2017 John Wiley & Sons, Ltd.

  1. 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)

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  3. 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.

  4. Sensitivity and uncertainty analysis applied to a repository in rock salt

    International Nuclear Information System (INIS)

    Polle, A.N.

    1996-12-01

    This document describes the sensitivity and uncertainty analysis with UNCSAM, as applied to a repository in rock salt for the EVEREST project. UNCSAM is a dedicated software package for sensitivity and uncertainty analysis, which was already used within the preceding PROSA project. The use of UNCSAM provides a flexible interface to EMOS ECN by substituting the sampled values in the various input files to be used by EMOS ECN ; the model calculations for this repository were performed with the EMOS ECN code. Preceding the sensitivity and uncertainty analysis, a number of preparations has been carried out to facilitate EMOS ECN with the probabilistic input data. For post-processing the EMOS ECN results, the characteristic output signals were processed. For the sensitivity and uncertainty analysis with UNCSAM the stochastic input, i.e. sampled values, and the output for the various EMOS ECN runs have been analyzed. (orig.)

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

    International Nuclear Information System (INIS)

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

    1995-01-01

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

  6. Singularity-sensitive gauge-based radar rainfall adjustment methods for urban hydrological applications

    Directory of Open Access Journals (Sweden)

    L.-P. Wang

    2015-09-01

    Full Text Available Gauge-based radar rainfall adjustment techniques have been widely used to improve the applicability of radar rainfall estimates to large-scale hydrological modelling. However, their use for urban hydrological applications is limited as they were mostly developed based upon Gaussian approximations and therefore tend to smooth off so-called "singularities" (features of a non-Gaussian field that can be observed in the fine-scale rainfall structure. Overlooking the singularities could be critical, given that their distribution is highly consistent with that of local extreme magnitudes. This deficiency may cause large errors in the subsequent urban hydrological modelling. To address this limitation and improve the applicability of adjustment techniques at urban scales, a method is proposed herein which incorporates a local singularity analysis into existing adjustment techniques and allows the preservation of the singularity structures throughout the adjustment process. In this paper the proposed singularity analysis is incorporated into the Bayesian merging technique and the performance of the resulting singularity-sensitive method is compared with that of the original Bayesian (non singularity-sensitive technique and the commonly used mean field bias adjustment. This test is conducted using as case study four storm events observed in the Portobello catchment (53 km2 (Edinburgh, UK during 2011 and for which radar estimates, dense rain gauge and sewer flow records, as well as a recently calibrated urban drainage model were available. The results suggest that, in general, the proposed singularity-sensitive method can effectively preserve the non-normality in local rainfall structure, while retaining the ability of the original adjustment techniques to generate nearly unbiased estimates. Moreover, the ability of the singularity-sensitive technique to preserve the non-normality in rainfall estimates often leads to better reproduction of the urban

  7. Singularity-sensitive gauge-based radar rainfall adjustment methods for urban hydrological applications

    Science.gov (United States)

    Wang, L.-P.; Ochoa-Rodríguez, S.; Onof, C.; Willems, P.

    2015-09-01

    Gauge-based radar rainfall adjustment techniques have been widely used to improve the applicability of radar rainfall estimates to large-scale hydrological modelling. However, their use for urban hydrological applications is limited as they were mostly developed based upon Gaussian approximations and therefore tend to smooth off so-called "singularities" (features of a non-Gaussian field) that can be observed in the fine-scale rainfall structure. Overlooking the singularities could be critical, given that their distribution is highly consistent with that of local extreme magnitudes. This deficiency may cause large errors in the subsequent urban hydrological modelling. To address this limitation and improve the applicability of adjustment techniques at urban scales, a method is proposed herein which incorporates a local singularity analysis into existing adjustment techniques and allows the preservation of the singularity structures throughout the adjustment process. In this paper the proposed singularity analysis is incorporated into the Bayesian merging technique and the performance of the resulting singularity-sensitive method is compared with that of the original Bayesian (non singularity-sensitive) technique and the commonly used mean field bias adjustment. This test is conducted using as case study four storm events observed in the Portobello catchment (53 km2) (Edinburgh, UK) during 2011 and for which radar estimates, dense rain gauge and sewer flow records, as well as a recently calibrated urban drainage model were available. The results suggest that, in general, the proposed singularity-sensitive method can effectively preserve the non-normality in local rainfall structure, while retaining the ability of the original adjustment techniques to generate nearly unbiased estimates. Moreover, the ability of the singularity-sensitive technique to preserve the non-normality in rainfall estimates often leads to better reproduction of the urban drainage system

  8. 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

  9. 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...

  10. Global sensitivity analysis using sparse grid interpolation and polynomial chaos

    International Nuclear Information System (INIS)

    Buzzard, Gregery T.

    2012-01-01

    Sparse grid interpolation is widely used to provide good approximations to smooth functions in high dimensions based on relatively few function evaluations. By using an efficient conversion from the interpolating polynomial provided by evaluations on a sparse grid to a representation in terms of orthogonal polynomials (gPC representation), we show how to use these relatively few function evaluations to estimate several types of sensitivity coefficients and to provide estimates on local minima and maxima. First, we provide a good estimate of the variance-based sensitivity coefficients of Sobol' (1990) [1] and then use the gradient of the gPC representation to give good approximations to the derivative-based sensitivity coefficients described by Kucherenko and Sobol' (2009) [2]. Finally, we use the package HOM4PS-2.0 given in Lee et al. (2008) [3] to determine the critical points of the interpolating polynomial and use these to determine the local minima and maxima of this polynomial. - Highlights: ► Efficient estimation of variance-based sensitivity coefficients. ► Efficient estimation of derivative-based sensitivity coefficients. ► Use of homotopy methods for approximation of local maxima and minima.

  11. Justification of investment projects of biogas systems by the sensitivity analysis

    Directory of Open Access Journals (Sweden)

    Perebijnos Vasilij Ivanovich

    2015-06-01

    Full Text Available Methodical features of sensitivity analysis application for evaluation of biogas plants investment projects are shown in the article. Risk factors of the indicated investment projects have been studied. Methodical basis for the use of sensitivity analysis and calculation of elasticity coefficient has been worked out. Calculation of sensitivity analysis and elasticity coefficient of three biogas plants projects, which differ in direction of biogas transformation: use in co-generation plant, application of biomethane as motor fuel and resulting carbon dioxide as marketable product, has been made. Factors strongly affecting projects efficiency have been revealed.

  12. A high sensitivity nanomaterial based SAW humidity sensor

    Energy Technology Data Exchange (ETDEWEB)

    Wu, T-T; Chou, T-H [Institute of Applied Mechanics, National Taiwan University, Taipei 106, Taiwan (China); Chen, Y-Y [Department of Mechanical Engineering, Tatung University, Taipei 104, Taiwan (China)], E-mail: wutt@ndt.iam.ntu.edu.tw

    2008-04-21

    In this paper, a highly sensitive humidity sensor is reported. The humidity sensor is configured by a 128{sup 0}YX-LiNbO{sub 3} based surface acoustic wave (SAW) resonator whose operating frequency is at 145 MHz. A dual delay line configuration is realized to eliminate external temperature fluctuations. Moreover, for nanostructured materials possessing high surface-to-volume ratio, large penetration depth and fast charge diffusion rate, camphor sulfonic acid doped polyaniline (PANI) nanofibres are synthesized by the interfacial polymerization method and further deposited on the SAW resonator as selective coating to enhance sensitivity. The humidity sensor is used to measure various relative humidities in the range 5-90% at room temperature. Results show that the PANI nanofibre based SAW humidity sensor exhibits excellent sensitivity and short-term repeatability.

  13. Failure Bounding And Sensitivity Analysis Applied To Monte Carlo Entry, Descent, And Landing Simulations

    Science.gov (United States)

    Gaebler, John A.; Tolson, Robert H.

    2010-01-01

    In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.

  14. *Corresponding Author Sensitivity Analysis of a Physiochemical ...

    African Journals Online (AJOL)

    Michael Horsfall

    The numerical method of sensitivity or the principle of parsimony ... analysis is a widely applied numerical method often being used in the .... Chemical Engineering Journal 128(2-3), 85-93. Amod S ... coupled 3-PG and soil organic matter.

  15. New strategies of sensitivity analysis capabilities in continuous-energy Monte Carlo code RMC

    International Nuclear Information System (INIS)

    Qiu, Yishu; Liang, Jingang; Wang, Kan; Yu, Jiankai

    2015-01-01

    Highlights: • Data decomposition techniques are proposed for memory reduction. • New strategies are put forward and implemented in RMC code to improve efficiency and accuracy for sensitivity calculations. • A capability to compute region-specific sensitivity coefficients is developed in RMC code. - Abstract: The iterated fission probability (IFP) method has been demonstrated to be an accurate alternative for estimating the adjoint-weighted parameters in continuous-energy Monte Carlo forward calculations. However, the memory requirements of this method are huge especially when a large number of sensitivity coefficients are desired. Therefore, data decomposition techniques are proposed in this work. Two parallel strategies based on the neutron production rate (NPR) estimator and the fission neutron population (FNP) estimator for adjoint fluxes, as well as a more efficient algorithm which has multiple overlapping blocks (MOB) in a cycle, are investigated and implemented in the continuous-energy Reactor Monte Carlo code RMC for sensitivity analysis. Furthermore, a region-specific sensitivity analysis capability is developed in RMC. These new strategies, algorithms and capabilities are verified against analytic solutions of a multi-group infinite-medium problem and against results from other software packages including MCNP6, TSUANAMI-1D and multi-group TSUNAMI-3D. While the results generated by the NPR and FNP strategies agree within 0.1% of the analytic sensitivity coefficients, the MOB strategy surprisingly produces sensitivity coefficients exactly equal to the analytic ones. Meanwhile, the results generated by the three strategies in RMC are in agreement with those produced by other codes within a few percent. Moreover, the MOB strategy performs the most efficient sensitivity coefficient calculations (offering as much as an order of magnitude gain in FoMs over MCNP6), followed by the NPR and FNP strategies, and then MCNP6. The results also reveal that these

  16. Estimations of climate sensitivity based on top-of-atmosphere radiation imbalance

    Directory of Open Access Journals (Sweden)

    B. Lin

    2010-02-01

    Full Text Available Large climate feedback uncertainties limit the accuracy in predicting the response of the Earth's climate to the increase of CO2 concentration within the atmosphere. This study explores a potential to reduce uncertainties in climate sensitivity estimations using energy balance analysis, especially top-of-atmosphere (TOA radiation imbalance. The time-scales studied generally cover from decade to century, that is, middle-range climate sensitivity is considered, which is directly related to the climate issue caused by atmospheric CO2 change. The significant difference between current analysis and previous energy balance models is that the current study targets at the boundary condition problem instead of solving the initial condition problem. Additionally, climate system memory and deep ocean heat transport are considered. The climate feedbacks are obtained based on the constraints of the TOA radiation imbalance and surface temperature measurements of the present climate. In this study, the TOA imbalance value of 0.85 W/m2 is used. Note that this imbalance value has large uncertainties. Based on this value, a positive climate feedback with a feedback coefficient ranging from −1.3 to −1.0 W/m2/K is found. The range of feedback coefficient is determined by climate system memory. The longer the memory, the stronger the positive feedback. The estimated time constant of the climate is large (70~120 years mainly owing to the deep ocean heat transport, implying that the system may be not in an equilibrium state under the external forcing during the industrial era. For the doubled-CO2 climate (or 3.7 W/m2 forcing, the estimated global warming would be 3.1 K if the current estimate of 0.85 W/m2 TOA net radiative heating could be confirmed. With accurate long-term measurements of TOA radiation, the analysis method suggested by this study provides a great potential in the

  17. 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)

  18. Adjoint sensitivity analysis of high frequency structures with Matlab

    CERN Document Server

    Bakr, Mohamed; Demir, Veysel

    2017-01-01

    This book covers the theory of adjoint sensitivity analysis and uses the popular FDTD (finite-difference time-domain) method to show how wideband sensitivities can be efficiently estimated for different types of materials and structures. It includes a variety of MATLAB® examples to help readers absorb the content more easily.

  19. System reliability assessment via sensitivity analysis in the Markov chain scheme

    International Nuclear Information System (INIS)

    Gandini, A.

    1988-01-01

    Methods for reliability sensitivity analysis in the Markov chain scheme are presented, together with a new formulation which makes use of Generalized Perturbation Theory (GPT) methods. As well known, sensitivity methods are fundamental in system risk analysis, since they allow to identify important components, so to assist the analyst in finding weaknesses in design and operation and in suggesting optimal modifications for system upgrade. The relationship between the GPT sensitivity expression and the Birnbaum importance is also given [fr

  20. 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.

  1. 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

  2. N -annulated perylene-based push-pull-type sensitizers

    KAUST Repository

    Qi, Qingbiao; Wang, Xingzhu; Fan, Li; Zheng, Bin; Zeng, Wangdong; Luo, Jie; Huang, Kuo-Wei; Wang, Qing; Wu, Jishan

    2015-01-01

    Alkoxy-wrapped N-annulated perylene (NP) was synthesized and used as a rigid and coplanar π-linker for three push-pull type metal-free sensitizers QB1-QB3. Their optical and electrochemical properties were tuned by varying the structure of acceptor. These new dyes were applied in Co(II)/(III) based dye-sensitized solar cells, and power conversion efficiency up to 6.95% was achieved, indicating that NP could be used as a new building block for the design of high-performance sensitizers in the future.

  3. N -annulated perylene-based push-pull-type sensitizers

    KAUST Repository

    Qi, Qingbiao

    2015-02-06

    Alkoxy-wrapped N-annulated perylene (NP) was synthesized and used as a rigid and coplanar π-linker for three push-pull type metal-free sensitizers QB1-QB3. Their optical and electrochemical properties were tuned by varying the structure of acceptor. These new dyes were applied in Co(II)/(III) based dye-sensitized solar cells, and power conversion efficiency up to 6.95% was achieved, indicating that NP could be used as a new building block for the design of high-performance sensitizers in the future.

  4. Content sensitivity based access control framework for Hadoop

    Directory of Open Access Journals (Sweden)

    T.K. Ashwin Kumar

    2017-11-01

    Full Text Available Big data technologies have seen tremendous growth in recent years. They are widely used in both industry and academia. In spite of such exponential growth, these technologies lack adequate measures to protect data from misuse/abuse. Corporations that collect data from multiple sources are at risk of liabilities due to the exposure of sensitive information. In the current implementation of Hadoop, only file-level access control is feasible. Providing users with the ability to access data based on the attributes in a dataset or the user’s role is complicated because of the sheer volume and multiple formats (structured, unstructured and semi-structured of data. In this paper, we propose an access control framework, which enforces access control policies dynamically based on the sensitivity of the data. This framework enforces access control policies by harnessing the data context, usage patterns and information sensitivity. Information sensitivity changes over time with the addition and removal of datasets, which can lead to modifications in access control decisions. The proposed framework accommodates these changes. The proposed framework is automated to a large extent as the data itself determines the sensitivity with minimal user intervention. Our experimental results show that the proposed framework is capable of enforcing access control policies on non-multimedia datasets with minimal overhead.

  5. High sensitivity MOSFET-based neutron dosimetry

    International Nuclear Information System (INIS)

    Fragopoulou, M.; Konstantakos, V.; Zamani, M.; Siskos, S.; Laopoulos, T.; Sarrabayrouse, G.

    2010-01-01

    A new dosemeter based on a metal-oxide-semiconductor field effect transistor sensitive to both neutrons and gamma radiation was manufactured at LAAS-CNRS Laboratory, Toulouse, France. In order to be used for neutron dosimetry, a thin film of lithium fluoride was deposited on the surface of the gate of the device. The characteristics of the dosemeter, such as the dependence of its response to neutron dose and dose rate, were investigated. The studied dosemeter was very sensitive to gamma rays compared to other dosemeters proposed in the literature. Its response in thermal neutrons was found to be much higher than in fast neutrons and gamma rays.

  6. Verification and sensitivity analysis on the elastic stiffness of the leaf type holddown spring assembly

    International Nuclear Information System (INIS)

    Song, Kee Nam

    1998-01-01

    The elastic formula of leaf type hold down spring(HDS) assembly is verified by comparing the values of elastic stiffness with the characteristic test results of the HDS's specimens. The comparisons show that the derived elastic stiffness formula is useful in reliably estimating the elastic stiffness of leaf type HDS assembly. The elastic stiffness sensitivity of leaf type HDS assembly is analyzed using the formula and its gradient vectors obtained from the mid-point formula. As a result of sensitivity analysis, the elastic stiffness sensitivity with respect to each design variable is quantified and design variables of large sensitivity are identified. Among the design variables, leaf thickness is identified as the most sensitive design variable to the elastic of leaf type HDS assembly. In addition, the elastic stiffness sensitivity, with respect to design variable, is in power-law type correlation to the base thickness of the leaf. (author)

  7. 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.

  8. Sensitivity analysis of the energy demand of existing buildings based on the Danish Building and Dwelling Register (BBR)

    DEFF Research Database (Denmark)

    Nielsen, Anker; Wittchen, Kim Bjarne; Bertelsen, Niels Haldor

    2014-01-01

    performance certificate. The Danish Building Research Institute has described a method that can be applied for estimating the energy demand of dwellings. This is based on the information in the Danish Building and Dwelling Register and requirements in the Danish Building Regulations from the year......The EU Directive on the Energy Performance of Buildings requires that energy certification of buildings should be implemented in Denmark so that houses that are sold or let should have an energy performance certificate. The result is that only a small part of existing houses has an energy...... of construction of the house. The result is an estimate of the energy demand of each building with a variation. This makes it possible to make an automatic classification of all buildings. The paper discusses the uncertainties and makes a sensitivity analysis to find the important parameters. The variations...

  9. 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.

  10. 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

  11. Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors.

    Science.gov (United States)

    Mitra, A K; Mukherjee, U K; Harding, T; Jang, J S; Stessman, H; Li, Y; Abyzov, A; Jen, J; Kumar, S; Rajkumar, V; Van Ness, B

    2016-05-01

    Multiple myeloma (MM) is characterized by significant genetic diversity at subclonal levels that have a defining role in the heterogeneity of tumor progression, clinical aggressiveness and drug sensitivity. Although genome profiling studies have demonstrated heterogeneity in subclonal architecture that may ultimately lead to relapse, a gene expression-based prediction program that can identify, distinguish and quantify drug response in sub-populations within a bulk population of myeloma cells is lacking. In this study, we performed targeted transcriptome analysis on 528 pre-treatment single cells from 11 myeloma cell lines and 418 single cells from 8 drug-naïve MM patients, followed by intensive bioinformatics and statistical analysis for prediction of proteasome inhibitor sensitivity in individual cells. Using our previously reported drug response gene expression profile signature at the single-cell level, we developed an R Statistical analysis package available at https://github.com/bvnlabSCATTome, SCATTome (single-cell analysis of targeted transcriptome), that restructures the data obtained from Fluidigm single-cell quantitative real-time-PCR analysis run, filters missing data, performs scaling of filtered data, builds classification models and predicts drug response of individual cells based on targeted transcriptome using an assortment of machine learning methods. Application of SCATT should contribute to clinically relevant analysis of intratumor heterogeneity, and better inform drug choices based on subclonal cellular responses.

  12. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Jacques, J

    2005-12-15

    Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)

  14. Linear Parametric Sensitivity Analysis of the Constraint Coefficient Matrix in Linear Programs

    NARCIS (Netherlands)

    R.A. Zuidwijk (Rob)

    2005-01-01

    textabstractSensitivity analysis is used to quantify the impact of changes in the initial data of linear programs on the optimal value. In particular, parametric sensitivity analysis involves a perturbation analysis in which the effects of small changes of some or all of the initial data on an

  15. Variable screening and ranking using sampling-based sensitivity measures

    International Nuclear Information System (INIS)

    Wu, Y-T.; Mohanty, Sitakanta

    2006-01-01

    This paper presents a methodology for screening insignificant random variables and ranking significant important random variables using sensitivity measures including two cumulative distribution function (CDF)-based and two mean-response based measures. The methodology features (1) using random samples to compute sensitivities and (2) using acceptance limits, derived from the test-of-hypothesis, to classify significant and insignificant random variables. Because no approximation is needed in either the form of the performance functions or the type of continuous distribution functions representing input variables, the sampling-based approach can handle highly nonlinear functions with non-normal variables. The main characteristics and effectiveness of the sampling-based sensitivity measures are investigated using both simple and complex examples. Because the number of samples needed does not depend on the number of variables, the methodology appears to be particularly suitable for problems with large, complex models that have large numbers of random variables but relatively few numbers of significant random variables

  16. 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.

  17. High sensitivity phase retrieval method in grating-based x-ray phase contrast imaging

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Zhao; Gao, Kun; Chen, Jian; Wang, Dajiang; Wang, Shenghao; Chen, Heng; Bao, Yuan; Shao, Qigang; Wang, Zhili, E-mail: wangnsrl@ustc.edu.cn [National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230029 (China); Zhang, Kai [Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China); Zhu, Peiping; Wu, Ziyu, E-mail: wuzy@ustc.edu.cn [National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei 230029, China and Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China)

    2015-02-15

    Purpose: Grating-based x-ray phase contrast imaging is considered as one of the most promising techniques for future medical imaging. Many different methods have been developed to retrieve phase signal, among which the phase stepping (PS) method is widely used. However, further practical implementations are hindered, due to its complex scanning mode and high radiation dose. In contrast, the reverse projection (RP) method is a novel fast and low dose extraction approach. In this contribution, the authors present a quantitative analysis of the noise properties of the refraction signals retrieved by the two methods and compare their sensitivities. Methods: Using the error propagation formula, the authors analyze theoretically the signal-to-noise ratios (SNRs) of the refraction images retrieved by the two methods. Then, the sensitivities of the two extraction methods are compared under an identical exposure dose. Numerical experiments are performed to validate the theoretical results and provide some quantitative insight. Results: The SNRs of the two methods are both dependent on the system parameters, but in different ways. Comparison between their sensitivities reveals that for the refraction signal, the RP method possesses a higher sensitivity, especially in the case of high visibility and/or at the edge of the object. Conclusions: Compared with the PS method, the RP method has a superior sensitivity and provides refraction images with a higher SNR. Therefore, one can obtain highly sensitive refraction images in grating-based phase contrast imaging. This is very important for future preclinical and clinical implementations.

  18. High sensitivity phase retrieval method in grating-based x-ray phase contrast imaging

    International Nuclear Information System (INIS)

    Wu, Zhao; Gao, Kun; Chen, Jian; Wang, Dajiang; Wang, Shenghao; Chen, Heng; Bao, Yuan; Shao, Qigang; Wang, Zhili; Zhang, Kai; Zhu, Peiping; Wu, Ziyu

    2015-01-01

    Purpose: Grating-based x-ray phase contrast imaging is considered as one of the most promising techniques for future medical imaging. Many different methods have been developed to retrieve phase signal, among which the phase stepping (PS) method is widely used. However, further practical implementations are hindered, due to its complex scanning mode and high radiation dose. In contrast, the reverse projection (RP) method is a novel fast and low dose extraction approach. In this contribution, the authors present a quantitative analysis of the noise properties of the refraction signals retrieved by the two methods and compare their sensitivities. Methods: Using the error propagation formula, the authors analyze theoretically the signal-to-noise ratios (SNRs) of the refraction images retrieved by the two methods. Then, the sensitivities of the two extraction methods are compared under an identical exposure dose. Numerical experiments are performed to validate the theoretical results and provide some quantitative insight. Results: The SNRs of the two methods are both dependent on the system parameters, but in different ways. Comparison between their sensitivities reveals that for the refraction signal, the RP method possesses a higher sensitivity, especially in the case of high visibility and/or at the edge of the object. Conclusions: Compared with the PS method, the RP method has a superior sensitivity and provides refraction images with a higher SNR. Therefore, one can obtain highly sensitive refraction images in grating-based phase contrast imaging. This is very important for future preclinical and clinical implementations

  19. Sensitivity analysis of an environmental model: an application of different analysis methods

    International Nuclear Information System (INIS)

    Campolongo, Francesca; Saltelli, Andrea

    1997-01-01

    A parametric sensitivity analysis (SA) was conducted on a well known model for the production of a key sulphur bearing compound from algal biota. The model is of interest because of the climatic relevance of the gas (dimethylsulphide, DMS), an initiator of cloud particles. A screening test at low sample size is applied first (Morris method) followed by a computationally intensive variance based measure. Standardised regression coefficients are also computed. The various SA measures are compared with each other, and the use of bootstrap is suggested to extract empirical confidence bounds on the SA estimators. For some of the input factors, investigators guess about the parameters relevance was confirmed; for some others, the results shed new light on the system mechanism and on the data parametrisation

  20. Sensitivity analysis of an optimization-based trajectory planner for autonomous vehicles in urban environments

    Science.gov (United States)

    Hardy, Jason; Campbell, Mark; Miller, Isaac; Schimpf, Brian

    2008-10-01

    The local path planner implemented on Cornell's 2007 DARPA Urban Challenge entry vehicle Skynet utilizes a novel mixture of discrete and continuous path planning steps to facilitate a safe, smooth, and human-like driving behavior. The planner first solves for a feasible path through the local obstacle map using a grid based search algorithm. The resulting path is then refined using a cost-based nonlinear optimization routine with both hard and soft constraints. The behavior of this optimization is influenced by tunable weighting parameters which govern the relative cost contributions assigned to different path characteristics. This paper studies the sensitivity of the vehicle's performance to these path planner weighting parameters using a data driven simulation based on logged data from the National Qualifying Event. The performance of the path planner in both the National Qualifying Event and in the Urban Challenge is also presented and analyzed.

  1. Design and Performance Analysis of Laser Displacement Sensor Based on Position Sensitive Detector (PSD)

    International Nuclear Information System (INIS)

    Song, H X; Wang, X D; Ma, L Q; Cai, M Z; Cao, T Z

    2006-01-01

    By using PSD as sensitive element, and laser diode as emitting element, laser displacement sensor based on triangulation method has been widely used. From the point of view of design, sensor and its performance were studied. Two different sensor configurations were described. Determination of the dimension, sensing resolution and comparison of the two different configurations were presented. The factors affecting the performance of the laser displacement sensor were discussed and two methods, which can eliminate the affection of dark current and environment light, are proposed

  2. Sensitivity Analysis of Centralized Dynamic Cell Selection

    DEFF Research Database (Denmark)

    Lopez, Victor Fernandez; Alvarez, Beatriz Soret; Pedersen, Klaus I.

    2016-01-01

    and a suboptimal optimization algorithm that nearly achieves the performance of the optimal Hungarian assignment. Moreover, an exhaustive sensitivity analysis with different network and traffic configurations is carried out in order to understand what conditions are more appropriate for the use of the proposed...

  3. Applications of advances in nonlinear sensitivity analysis

    Energy Technology Data Exchange (ETDEWEB)

    Werbos, P J

    1982-01-01

    The following paper summarizes the major properties and applications of a collection of algorithms involving differentiation and optimization at minimum cost. The areas of application include the sensitivity analysis of models, new work in statistical or econometric estimation, optimization, artificial intelligence and neuron modelling.

  4. 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

  5. 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.

  6. 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

  7. Computing eigenvalue sensitivity coefficients to nuclear data based on the CLUTCH method with RMC code

    International Nuclear Information System (INIS)

    Qiu, Yishu; She, Ding; Tang, Xiao; Wang, Kan; Liang, Jingang

    2016-01-01

    Highlights: • A new algorithm is proposed to reduce memory consumption for sensitivity analysis. • The fission matrix method is used to generate adjoint fission source distributions. • Sensitivity analysis is performed on a detailed 3D full-core benchmark with RMC. - Abstract: Recently, there is a need to develop advanced methods of computing eigenvalue sensitivity coefficients to nuclear data in the continuous-energy Monte Carlo codes. One of these methods is the iterated fission probability (IFP) method, which is adopted by most of Monte Carlo codes of having the capabilities of computing sensitivity coefficients, including the Reactor Monte Carlo code RMC. Though it is accurate theoretically, the IFP method faces the challenge of huge memory consumption. Therefore, it may sometimes produce poor sensitivity coefficients since the number of particles in each active cycle is not sufficient enough due to the limitation of computer memory capacity. In this work, two algorithms of the Contribution-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method, namely, the collision-event-based algorithm (C-CLUTCH) which is also implemented in SCALE and the fission-event-based algorithm (F-CLUTCH) which is put forward in this work, are investigated and implemented in RMC to reduce memory requirements for computing eigenvalue sensitivity coefficients. While the C-CLUTCH algorithm requires to store concerning reaction rates of every collision, the F-CLUTCH algorithm only stores concerning reaction rates of every fission point. In addition, the fission matrix method is put forward to generate the adjoint fission source distribution for the CLUTCH method to compute sensitivity coefficients. These newly proposed approaches implemented in RMC code are verified by a SF96 lattice model and the MIT BEAVRS benchmark problem. The numerical results indicate the accuracy of the F-CLUTCH algorithm is the same as the C

  8. An overview of the design and analysis of simulation experiments for sensitivity analysis

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2005-01-01

    Sensitivity analysis may serve validation, optimization, and risk analysis of simulation models. This review surveys 'classic' and 'modern' designs for experiments with simulation models. Classic designs were developed for real, non-simulated systems in agriculture, engineering, etc. These designs

  9. 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.

  10. Low Power and High Sensitivity MOSFET-Based Pressure Sensor

    International Nuclear Information System (INIS)

    Zhang Zhao-Hua; Ren Tian-Ling; Zhang Yan-Hong; Han Rui-Rui; Liu Li-Tian

    2012-01-01

    Based on the metal-oxide-semiconductor field effect transistor (MOSFET) stress sensitive phenomenon, a low power MOSFET pressure sensor is proposed. Compared with the traditional piezoresistive pressure sensor, the present pressure sensor displays high performances on sensitivity and power consumption. The sensitivity of the MOSFET sensor is raised by 87%, meanwhile the power consumption is decreased by 20%. (cross-disciplinary physics and related areas of science and technology)

  11. Ecological Sensitivity Evaluation of Tourist Region Based on Remote Sensing Image - Taking Chaohu Lake Area as a Case Study

    Science.gov (United States)

    Lin, Y.; Li, W. J.; Yu, J.; Wu, C. Z.

    2018-04-01

    Remote sensing technology is of significant advantages for monitoring and analysing ecological environment. By using of automatic extraction algorithm, various environmental resources information of tourist region can be obtained from remote sensing imagery. Combining with GIS spatial analysis and landscape pattern analysis, relevant environmental information can be quantitatively analysed and interpreted. In this study, taking the Chaohu Lake Basin as an example, Landsat-8 multi-spectral satellite image of October 2015 was applied. Integrated the automatic ELM (Extreme Learning Machine) classification results with the data of digital elevation model and slope information, human disturbance degree, land use degree, primary productivity, landscape evenness , vegetation coverage, DEM, slope and normalized water body index were used as the evaluation factors to construct the eco-sensitivity evaluation index based on AHP and overlay analysis. According to the value of eco-sensitivity evaluation index, by using of GIS technique of equal interval reclassification, the Chaohu Lake area was divided into four grades: very sensitive area, sensitive area, sub-sensitive areas and insensitive areas. The results of the eco-sensitivity analysis shows: the area of the very sensitive area was 4577.4378 km2, accounting for about 37.12 %, the sensitive area was 5130.0522 km2, accounting for about 37.12 %; the area of sub-sensitive area was 3729.9312 km2, accounting for 26.99 %; the area of insensitive area was 382.4399 km2, accounting for about 2.77 %. At the same time, it has been found that there were spatial differences in ecological sensitivity of the Chaohu Lake basin. The most sensitive areas were mainly located in the areas with high elevation and large terrain gradient. Insensitive areas were mainly distributed in slope of the slow platform area; the sensitive areas and the sub-sensitive areas were mainly agricultural land and woodland. Through the eco-sensitivity analysis of

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Generalized tolerance sensitivity and DEA metric sensitivity

    OpenAIRE

    Neralić, Luka; E. Wendell, Richard

    2015-01-01

    This paper considers the relationship between Tolerance sensitivity analysis in optimization and metric sensitivity analysis in Data Envelopment Analysis (DEA). Herein, we extend the results on the generalized Tolerance framework proposed by Wendell and Chen and show how this framework includes DEA metric sensitivity as a special case. Further, we note how recent results in Tolerance sensitivity suggest some possible extensions of the results in DEA metric sensitivity.

  17. Generalized tolerance sensitivity and DEA metric sensitivity

    Directory of Open Access Journals (Sweden)

    Luka Neralić

    2015-03-01

    Full Text Available This paper considers the relationship between Tolerance sensitivity analysis in optimization and metric sensitivity analysis in Data Envelopment Analysis (DEA. Herein, we extend the results on the generalized Tolerance framework proposed by Wendell and Chen and show how this framework includes DEA metric sensitivity as a special case. Further, we note how recent results in Tolerance sensitivity suggest some possible extensions of the results in DEA metric sensitivity.

  18. Demonstration sensitivity analysis for RADTRAN III

    International Nuclear Information System (INIS)

    Neuhauser, K.S.; Reardon, P.C.

    1986-10-01

    A demonstration sensitivity analysis was performed to: quantify the relative importance of 37 variables to the total incident free dose; assess the elasticity of seven dose subgroups to those same variables; develop density distributions for accident dose to combinations of accident data under wide-ranging variations; show the relationship between accident consequences and probabilities of occurrence; and develop limits for the variability of probability consequence curves

  19. Evaluation of the Potential Sensitization of Chlorogenic Acid: A Meta-Analysis

    Directory of Open Access Journals (Sweden)

    Mingbao Lin

    2013-01-01

    Full Text Available Chlorogenic acid (CGA widely exists in many plants, which are used as medicinal substances in traditional Chinese medicine injectables (TCMIs that have been widely applied in clinical treatments. However, it is still controversial whether CGA is responsible for TCMIs-related hypersensitivity. Several studies have been performed to evaluate its potential sensitization property, but the results were inconclusive. Therefore, the aim of this study was to evaluate its potential sensitization systematically using meta-analysis based on data extracted from literatures, searching databases of PubMed, EMBASE, ISI Web of Knowledge, CNKI, VIP, and CHINAINFO from January 1979 to October 2012, a total of 108 articles were retrieved by electronic search strategy, out of which 13 studies met the inclusion criteria. In ASA test, odds ratio of behavior changes was 4.33 (1.62, 11.60, showing significant changes after CGA treatment (P=0.004. Serum IgG, serum histamine, PLN cellularity, and IgG1 AFCs were significantly enhanced after CGA treatment (P<0.05. Totally, these results indicated that CGA could induce a positive reaction in potential sensitization, and intravenous administration of it might be a key factor for sensitization triggering, which could at least warrant more careful application of TCMIs containing CGA in clinical practices.

  20. Sensitivity analysis of water consumption in an office building

    Science.gov (United States)

    Suchacek, Tomas; Tuhovcak, Ladislav; Rucka, Jan

    2018-02-01

    This article deals with sensitivity analysis of real water consumption in an office building. During a long-term real study, reducing of pressure in its water connection was simulated. A sensitivity analysis of uneven water demand was conducted during working time at various provided pressures and at various time step duration. Correlations between maximal coefficients of water demand variation during working time and provided pressure were suggested. The influence of provided pressure in the water connection on mean coefficients of water demand variation was pointed out, altogether for working hours of all days and separately for days with identical working hours.

  1. An Overview of the Design and Analysis of Simulation Experiments for Sensitivity Analysis

    NARCIS (Netherlands)

    Kleijnen, J.P.C.

    2004-01-01

    Sensitivity analysis may serve validation, optimization, and risk analysis of simulation models.This review surveys classic and modern designs for experiments with simulation models.Classic designs were developed for real, non-simulated systems in agriculture, engineering, etc.These designs assume a

  2. 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...

  3. 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)

  4. A sensitivity analysis of a radiological assessment model for Arctic waters

    DEFF Research Database (Denmark)

    Nielsen, S.P.

    1998-01-01

    A model based on compartment analysis has been developed to simulate the dispersion of radionuclides in Arctic waters for an assessment of doses to man. The model predicts concentrations of radionuclides in the marine environment and doses to man from a range of exposure pathways. A parameter sen...... scavenging, water-sediment interaction, biological uptake, ice transport and fish migration. Two independent evaluations of the release of radioactivity from dumped nuclear waste in the Kara Sea have been used as source terms for the dose calculations.......A model based on compartment analysis has been developed to simulate the dispersion of radionuclides in Arctic waters for an assessment of doses to man. The model predicts concentrations of radionuclides in the marine environment and doses to man from a range of exposure pathways. A parameter...... sensitivity analysis has identified components of the model that are potentially important contributors to the predictive accuracy of doses to individuals of critical groups as well as to the world population. The components investigated include features associated with water transport and mixing, particle...

  5. 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)

  6. An Introduction to Sensitivity Analysis for Unobserved Confounding in Non-Experimental Prevention Research

    Science.gov (United States)

    Kuramoto, S. Janet; Stuart, Elizabeth A.

    2013-01-01

    Despite that randomization is the gold standard for estimating causal relationships, many questions in prevention science are left to be answered through non-experimental studies often because randomization is either infeasible or unethical. While methods such as propensity score matching can adjust for observed confounding, unobserved confounding is the Achilles heel of most non-experimental studies. This paper describes and illustrates seven sensitivity analysis techniques that assess the sensitivity of study results to an unobserved confounder. These methods were categorized into two groups to reflect differences in their conceptualization of sensitivity analysis, as well as their targets of interest. As a motivating example we examine the sensitivity of the association between maternal suicide and offspring’s risk for suicide attempt hospitalization. While inferences differed slightly depending on the type of sensitivity analysis conducted, overall the association between maternal suicide and offspring’s hospitalization for suicide attempt was found to be relatively robust to an unobserved confounder. The ease of implementation and the insight these analyses provide underscores sensitivity analysis techniques as an important tool for non-experimental studies. The implementation of sensitivity analysis can help increase confidence in results from non-experimental studies and better inform prevention researchers and policymakers regarding potential intervention targets. PMID:23408282

  7. OECD/NEA expert group on uncertainty analysis for criticality safety assessment: Results of benchmark on sensitivity calculation (phase III)

    Energy Technology Data Exchange (ETDEWEB)

    Ivanova, T.; Laville, C. [Institut de Radioprotection et de Surete Nucleaire IRSN, BP 17, 92262 Fontenay aux Roses (France); Dyrda, J. [Atomic Weapons Establishment AWE, Aldermaston, Reading, RG7 4PR (United Kingdom); Mennerdahl, D. [E Mennerdahl Systems EMS, Starvaegen 12, 18357 Taeby (Sweden); Golovko, Y.; Raskach, K.; Tsiboulia, A. [Inst. for Physics and Power Engineering IPPE, 1, Bondarenko sq., 249033 Obninsk (Russian Federation); Lee, G. S.; Woo, S. W. [Korea Inst. of Nuclear Safety KINS, 62 Gwahak-ro, Yuseong-gu, Daejeon 305-338 (Korea, Republic of); Bidaud, A.; Sabouri, P. [Laboratoire de Physique Subatomique et de Cosmologie LPSC, CNRS-IN2P3/UJF/INPG, Grenoble (France); Patel, A. [U.S. Nuclear Regulatory Commission (NRC), Washington, DC 20555-0001 (United States); Bledsoe, K.; Rearden, B. [Oak Ridge National Laboratory ORNL, M.S. 6170, P.O. Box 2008, Oak Ridge, TN 37831 (United States); Gulliford, J.; Michel-Sendis, F. [OECD/NEA, 12, Bd des Iles, 92130 Issy-les-Moulineaux (France)

    2012-07-01

    The sensitivities of the k{sub eff} eigenvalue to neutron cross sections have become commonly used in similarity studies and as part of the validation algorithm for criticality safety assessments. To test calculations of the sensitivity coefficients, a benchmark study (Phase III) has been established by the OECD-NEA/WPNCS/EG UACSA (Expert Group on Uncertainty Analysis for Criticality Safety Assessment). This paper presents some sensitivity results generated by the benchmark participants using various computational tools based upon different computational methods: SCALE/TSUNAMI-3D and -1D, MONK, APOLLO2-MORET 5, DRAGON-SUSD3D and MMKKENO. The study demonstrates the performance of the tools. It also illustrates how model simplifications impact the sensitivity results and demonstrates the importance of 'implicit' (self-shielding) sensitivities. This work has been a useful step towards verification of the existing and developed sensitivity analysis methods. (authors)

  8. 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.

  9. 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....

  10. 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.)

  11. Sensitivity analysis of autotrophic N removal by a granule based bioreactor: Influence of mass transfer versus microbial kinetics

    DEFF Research Database (Denmark)

    Vangsgaard, Anna Katrine; Mauricio Iglesias, Miguel; Gernaey, Krist

    2012-01-01

    A comprehensive and global sensitivity analysis was conducted under a range of operating conditions. The relative importance of mass transfer resistance versus kinetic parameters was studied and found to depend on the operating regime as follows: Operating under the optimal loading ratio of 1.90 ...

  12. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-03-10

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

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

    International Nuclear Information System (INIS)

    Kala, Zdeněk

    2015-01-01

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

  15. 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.

  16. Deterministic sensitivity analysis of two-phase flow systems: forward and adjoint methods. Final report

    International Nuclear Information System (INIS)

    Cacuci, D.G.

    1984-07-01

    This report presents a self-contained mathematical formalism for deterministic sensitivity analysis of two-phase flow systems, a detailed application to sensitivity analysis of the homogeneous equilibrium model of two-phase flow, and a representative application to sensitivity analysis of a model (simulating pump-trip-type accidents in BWRs) where a transition between single phase and two phase occurs. The rigor and generality of this sensitivity analysis formalism stem from the use of Gateaux (G-) differentials. This report highlights the major aspects of deterministic (forward and adjoint) sensitivity analysis, including derivation of the forward sensitivity equations, derivation of sensitivity expressions in terms of adjoint functions, explicit construction of the adjoint system satisfied by these adjoint functions, determination of the characteristics of this adjoint system, and demonstration that these characteristics are the same as those of the original quasilinear two-phase flow equations. This proves that whenever the original two-phase flow problem is solvable, the adjoint system is also solvable and, in principle, the same numerical methods can be used to solve both the original and adjoint equations

  17. Water-Based Pressure Sensitive Paint

    Science.gov (United States)

    Oglesby, Donald M.; Ingram, JoAnne L.; Jordan, Jeffrey D.; Watkins, A. Neal; Leighty, Bradley D.

    2004-01-01

    Preparation and performance of a water-based pressure sensitive paint (PSP) is described. A water emulsion of an oxygen permeable polymer and a platinum porphyrin type luminescent compound were dispersed in a water matrix to produce a PSP that performs well without the use of volatile, toxic solvents. The primary advantages of this PSP are reduced contamination of wind tunnels in which it is used, lower health risk to its users, and easier cleanup and disposal. This also represents a cost reduction by eliminating the need for elaborate ventilation and user protection during application. The water-based PSP described has all the characteristics associated with water-based paints (low toxicity, very low volatile organic chemicals, and easy water cleanup) but also has high performance as a global pressure sensor for PSP measurements in wind tunnels. The use of a water-based PSP virtually eliminates the toxic fumes associated with the application of PSPs to a model in wind tunnels.

  18. Integrated thermal and nonthermal treatment technology and subsystem cost sensitivity analysis

    International Nuclear Information System (INIS)

    Harvego, L.A.; Schafer, J.J.

    1997-02-01

    The U.S. Department of Energy's (DOE) Environmental Management Office of Science and Technology (EM-50) authorized studies on alternative systems for treating contact-handled DOE mixed low-level radioactive waste (MLLW). The on-going Integrated Thermal Treatment Systems' (ITTS) and the Integrated Nonthermal Treatment Systems' (INTS) studies satisfy this request. EM-50 further authorized supporting studies including this technology and subsystem cost sensitivity analysis. This analysis identifies areas where technology development could have the greatest impact on total life cycle system costs. These areas are determined by evaluating the sensitivity of system life cycle costs relative to changes in life cycle component or phase costs, subsystem costs, contingency allowance, facility capacity, operating life, and disposal costs. For all treatment systems, the most cost sensitive life cycle phase is the operations and maintenance phase and the most cost sensitive subsystem is the receiving and inspection/preparation subsystem. These conclusions were unchanged when the sensitivity analysis was repeated on a present value basis. Opportunity exists for technology development to reduce waste receiving and inspection/preparation costs by effectively minimizing labor costs, the major cost driver, within the maintenance and operations phase of the life cycle

  19. 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)

  20. Source apportionment and sensitivity analysis: two methodologies with two different purposes

    Science.gov (United States)

    Clappier, Alain; Belis, Claudio A.; Pernigotti, Denise; Thunis, Philippe

    2017-11-01

    This work reviews the existing methodologies for source apportionment and sensitivity analysis to identify key differences and stress their implicit limitations. The emphasis is laid on the differences between source impacts (sensitivity analysis) and contributions (source apportionment) obtained by using four different methodologies: brute-force top-down, brute-force bottom-up, tagged species and decoupled direct method (DDM). A simple theoretical example to compare these approaches is used highlighting differences and potential implications for policy. When the relationships between concentration and emissions are linear, impacts and contributions are equivalent concepts. In this case, source apportionment and sensitivity analysis may be used indifferently for both air quality planning purposes and quantifying source contributions. However, this study demonstrates that when the relationship between emissions and concentrations is nonlinear, sensitivity approaches are not suitable to retrieve source contributions and source apportionment methods are not appropriate to evaluate the impact of abatement strategies. A quantification of the potential nonlinearities should therefore be the first step prior to source apportionment or planning applications, to prevent any limitations in their use. When nonlinearity is mild, these limitations may, however, be acceptable in the context of the other uncertainties inherent to complex models. Moreover, when using sensitivity analysis for planning, it is important to note that, under nonlinear circumstances, the calculated impacts will only provide information for the exact conditions (e.g. emission reduction share) that are simulated.

  1. Association between atopic dermatitis and contact sensitization: A systematic review and meta-analysis.

    Science.gov (United States)

    Hamann, Carsten R; Hamann, Dathan; Egeberg, Alexander; Johansen, Jeanne D; Silverberg, Jonathan; Thyssen, Jacob P

    2017-07-01

    It is unclear whether patients with atopic dermatitis (AD) have an altered prevalence or risk for contact sensitization. Increased exposure to chemicals in topical products together with impaired skin barrier function suggest a higher risk, whereas the immune profile suggests a lower risk. To perform a systematic review and meta-analysis of the association between AD and contact sensitization. The PubMed/Medline, Embase, and Cochrane databases were searched for articles that reported on contact sensitization in individuals with and without AD. The literature search yielded 10,083 citations; 417 were selected based on title and abstract screening and 74 met inclusion criteria. In a pooled analysis, no significant difference in contact sensitization between AD and controls was evident (random effects model odds ratio [OR] = 0.891; 95% confidence interval [CI] = 0.771-1.03). There was a positive correlation in studies that compared AD patients with individuals from the general population (OR 1.50, 95% CI 1.23-1.93) but an inverse association when comparing with referred populations (OR 0.753, 95% CI 0.63-0.90). Included studies used different tools to diagnose AD and did not always provide information on current or past disease. Patch test allergens varied between studies. No overall relationship between AD and contact sensitization was found. We recommend that clinicians consider patch testing AD patients when allergic contact dermatitis is suspected. Copyright © 2017 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

  2. EV range sensitivity analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ostafew, C. [Azure Dynamics Corp., Toronto, ON (Canada)

    2010-07-01

    This presentation included a sensitivity analysis of electric vehicle components on overall efficiency. The presentation provided an overview of drive cycles and discussed the major contributors to range in terms of rolling resistance; aerodynamic drag; motor efficiency; and vehicle mass. Drive cycles that were presented included: New York City Cycle (NYCC); urban dynamometer drive cycle; and US06. A summary of the findings were presented for each of the major contributors. Rolling resistance was found to have a balanced effect on each drive cycle and proportional to range. In terms of aerodynamic drive, there was a large effect on US06 range. A large effect was also found on NYCC range in terms of motor efficiency and vehicle mass. figs.

  3. Sensitivity and uncertainty analyses for performance assessment modeling

    International Nuclear Information System (INIS)

    Doctor, P.G.

    1988-08-01

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

  4. Logit and probit model in toll sensitivity analysis of Solo-Ngawi, Kartasura-Palang Joglo segment based on Willingness to Pay (WTP)

    Science.gov (United States)

    Handayani, Dewi; Cahyaning Putri, Hera; Mahmudah, AMH

    2017-12-01

    Solo-Ngawi toll road project is part of the mega project of the Trans Java toll road development initiated by the government and is still under construction until now. PT Solo Ngawi Jaya (SNJ) as the Solo-Ngawi toll management company needs to determine the toll fare that is in accordance with the business plan. The determination of appropriate toll rates will affect progress in regional economic sustainability and decrease the traffic congestion. These policy instruments is crucial for achieving environmentally sustainable transport. Therefore, the objective of this research is to find out how the toll fare sensitivity of Solo-Ngawi toll road based on Willingness To Pay (WTP). Primary data was obtained by distributing stated preference questionnaires to four wheeled vehicle users in Kartasura-Palang Joglo artery road segment. Further data obtained will be analysed with logit and probit model. Based on the analysis, it is found that the effect of fare change on the amount of WTP on the binomial logit model is more sensitive than the probit model on the same travel conditions. The range of tariff change against values of WTP on the binomial logit model is 20% greater than the range of values in the probit model . On the other hand, the probability results of the binomial logit model and the binary probit have no significant difference (less than 1%).

  5. 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.

  6. Sample application of sensitivity/uncertainty analysis techniques to a groundwater transport problem. National Low-Level Waste Management Program

    International Nuclear Information System (INIS)

    Seitz, R.R.; Rood, A.S.; Harris, G.A.; Maheras, S.J.; Kotecki, M.

    1991-06-01

    The primary objective of this document is to provide sample applications of selected sensitivity and uncertainty analysis techniques within the context of the radiological performance assessment process. These applications were drawn from the companion document Guidelines for Sensitivity and Uncertainty Analyses of Low-Level Radioactive Waste Performance Assessment Computer Codes (S. Maheras and M. Kotecki, DOE/LLW-100, 1990). Three techniques are illustrated in this document: one-factor-at-a-time (OFAT) analysis, fractional factorial design, and Latin hypercube sampling. The report also illustrates the differences in sensitivity and uncertainty analysis at the early and latter stages of the performance assessment process, and potential pitfalls that can be encountered when applying the techniques. The emphasis is on application of the techniques as opposed to the actual results, since the results are hypothetical and are not based on site-specific conditions

  7. 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.

  8. 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

  9. (abstract) Sensitivity to Forest Biomass Based on Analysis of Scattering Mechanism

    Science.gov (United States)

    Way, JoBea; Bachman, Jennifer E.; Paige, David A.

    1993-01-01

    The estimation of forest biomass on a global scale is an important input to global climate and carbon cycle models. Remote sensing using synthetic aperture radar offers a means to obtain such a data set. Although it has been clear for some time that radar signals penetrate forest canopies, only recently has it been demonstrated that these signals are indeed sensitive to biomass. Inasmuch as the majority of a forest's biomass is in the trunks, it is important that the radar is sensing the trunk biomass as opposed to the branch or leaf biomass. In this study we use polarimetric AIRSAR P- and L-band data from a variety of forests to determine if the radar penetrates to the trunk by examining the scattering mechanism as determined using van Zyl's scattering interaction model, and the levels at which saturation occurs with respect to sensitivity of radar backscatter to total biomass. In particular, the added sensitivity of P-band relative to L-band is addressed. Results using data from the Duke Forest in North Carolina, the Bonanza Creek Experimental Forest in Alaska, Shasta Forest in California, the Black Forest in Germany, the temporate/boreal transition forests in northern Michigan, and coastal forests along the Oregon Transect will be presented.

  10. Deterministic Local Sensitivity Analysis of Augmented Systems - I: Theory

    International Nuclear Information System (INIS)

    Cacuci, Dan G.; Ionescu-Bujor, Mihaela

    2005-01-01

    This work provides the theoretical foundation for the modular implementation of the Adjoint Sensitivity Analysis Procedure (ASAP) for large-scale simulation systems. The implementation of the ASAP commences with a selected code module and then proceeds by augmenting the size of the adjoint sensitivity system, module by module, until the entire system is completed. Notably, the adjoint sensitivity system for the augmented system can often be solved by using the same numerical methods used for solving the original, nonaugmented adjoint system, particularly when the matrix representation of the adjoint operator for the augmented system can be inverted by partitioning

  11. Nuclear data sensitivity/uncertainty analysis for XT-ADS

    International Nuclear Information System (INIS)

    Sugawara, Takanori; Sarotto, Massimo; Stankovskiy, Alexey; Van den Eynde, Gert

    2011-01-01

    Highlights: → The sensitivity and uncertainty analyses were performed to comprehend the reliability of the XT-ADS neutronic design. → The uncertainties deduced from the covariance data for the XT-ADS criticality were 0.94%, 1.9% and 1.1% by the SCALE 44-group, TENDL-2009 and JENDL-3.3 data, respectively. → When the target accuracy of 0.3%Δk for the criticality was considered, the uncertainties did not satisfy it. → To achieve this accuracy, the uncertainties should be improved by experiments under an adequate condition. - Abstract: The XT-ADS, an accelerator-driven system for an experimental demonstration, has been investigated in the framework of IP EUROTRANS FP6 project. In this study, the sensitivity and uncertainty analyses were performed to comprehend the reliability of the XT-ADS neutronic design. For the sensitivity analysis, it was found that the sensitivity coefficients were significantly different by changing the geometry models and calculation codes. For the uncertainty analysis, it was confirmed that the uncertainties deduced from the covariance data varied significantly by changing them. The uncertainties deduced from the covariance data for the XT-ADS criticality were 0.94%, 1.9% and 1.1% by the SCALE 44-group, TENDL-2009 and JENDL-3.3 data, respectively. When the target accuracy of 0.3%Δk for the criticality was considered, the uncertainties did not satisfy it. To achieve this accuracy, the uncertainties should be improved by experiments under an adequate condition.

  12. Performance and stability analysis of curcumin dye as a photo sensitizer used in nanostructured ZnO based DSSC

    Science.gov (United States)

    Sinha, D.; De, D.; Ayaz, A.

    2018-03-01

    Environmental friendly natural dye curcumin extracted from low-cost Curcumina longa stem is used as a photo-sensitizer for the fabrication of ZnO-based dye-sensitized solar cells (DSSC). Nanostructured ZnO is fabricated on a transparent conducting glass (TCO), using a cost-effective chemical bath deposition technique. Scanning electron microscopic images show hexagonal patterned ZnO nano-towers decorated with several nanosteps. The average length of ZnO nano-tower is 5 μm and diameter is 1.2 μm. The UV-Vis spectroscopic study of the curcumin dye is used to understand the light absorption behavior as well as band gap energy of the extracted natural dye. The dye shows wider absorption band-groups over 350-470 nm and 500-600 nm with two peaks positioned at 425 nm and 525 nm. The optical band gap energy and energy band position of the dye is derived which supports its stability and high electron affinity that makes it suitable for light harvesting and effortless electron transfer from dye to the semiconductor or interface between them. FTIR spectrum of curcumin dye-sensitized ZnO-based DSSC shows the presence of anchoring groups and colouring constitutes. The I-V and P-V curves of the fabricated DSSC are measured under simulated light (100 mW/cm2). The highest visible light to electric conversion efficiency of 0.266% (using ITO) and 0.33% (using FTO) is achieved from the curcumin dye-sensitized cell.

  13. Space-Based Diagnosis of Surface Ozone Sensitivity to Anthropogenic Emissions

    Science.gov (United States)

    Martin, Randall V.; Fiore, Arlene M.; VanDonkelaar, Aaron

    2004-01-01

    We present a novel capability in satellite remote sensing with implications for air pollution control strategy. We show that the ratio of formaldehyde columns to tropospheric nitrogen dioxide columns is an indicator of the relative sensitivity of surface ozone to emissions of nitrogen oxides (NO(x) = NO + NO2) and volatile organic compounds (VOCs). The diagnosis from these space-based observations is highly consistent with current understanding of surface ozone chemistry based on in situ observations. The satellite-derived ratios indicate that surface ozone is more sensitive to emissions of NO(x) than of VOCs throughout most continental regions of the Northern Hemisphere during summer. Exceptions include Los Angeles and industrial areas of Germany. A seasonal transition occurs in the fall when surface ozone becomes less sensitive to NOx and more sensitive to VOCs.

  14. ECOLOGICAL SENSITIVITY EVALUATION OF TOURIST REGION BASED ON REMOTE SENSING IMAGE – TAKING CHAOHU LAKE AREA AS A CASE STUDY

    Directory of Open Access Journals (Sweden)

    Y. Lin

    2018-04-01

    Full Text Available Remote sensing technology is of significant advantages for monitoring and analysing ecological environment. By using of automatic extraction algorithm, various environmental resources information of tourist region can be obtained from remote sensing imagery. Combining with GIS spatial analysis and landscape pattern analysis, relevant environmental information can be quantitatively analysed and interpreted. In this study, taking the Chaohu Lake Basin as an example, Landsat-8 multi-spectral satellite image of October 2015 was applied. Integrated the automatic ELM (Extreme Learning Machine classification results with the data of digital elevation model and slope information, human disturbance degree, land use degree, primary productivity, landscape evenness , vegetation coverage, DEM, slope and normalized water body index were used as the evaluation factors to construct the eco-sensitivity evaluation index based on AHP and overlay analysis. According to the value of eco-sensitivity evaluation index, by using of GIS technique of equal interval reclassification, the Chaohu Lake area was divided into four grades: very sensitive area, sensitive area, sub-sensitive areas and insensitive areas. The results of the eco-sensitivity analysis shows: the area of the very sensitive area was 4577.4378 km2, accounting for about 37.12 %, the sensitive area was 5130.0522 km2, accounting for about 37.12 %; the area of sub-sensitive area was 3729.9312 km2, accounting for 26.99 %; the area of insensitive area was 382.4399 km2, accounting for about 2.77 %. At the same time, it has been found that there were spatial differences in ecological sensitivity of the Chaohu Lake basin. The most sensitive areas were mainly located in the areas with high elevation and large terrain gradient. Insensitive areas were mainly distributed in slope of the slow platform area; the sensitive areas and the sub-sensitive areas were mainly agricultural land and woodland

  15. Probabilistic Sensitivity Analysis for Launch Vehicles with Varying Payloads and Adapters for Structural Dynamics and Loads

    Science.gov (United States)

    McGhee, David S.; Peck, Jeff A.; McDonald, Emmett J.

    2012-01-01

    This paper examines Probabilistic Sensitivity Analysis (PSA) methods and tools in an effort to understand their utility in vehicle loads and dynamic analysis. Specifically, this study addresses how these methods may be used to establish limits on payload mass and cg location and requirements on adaptor stiffnesses while maintaining vehicle loads and frequencies within established bounds. To this end, PSA methods and tools are applied to a realistic, but manageable, integrated launch vehicle analysis where payload and payload adaptor parameters are modeled as random variables. This analysis is used to study both Regional Response PSA (RRPSA) and Global Response PSA (GRPSA) methods, with a primary focus on sampling based techniques. For contrast, some MPP based approaches are also examined.

  16. Uncertainty and sensitivity analysis of flood risk management decisions based on stationary and nonstationary model choices

    Directory of Open Access Journals (Sweden)

    Rehan Balqis M.

    2016-01-01

    Full Text Available Current practice in flood frequency analysis assumes that the stochastic properties of extreme floods follow that of stationary conditions. As human intervention and anthropogenic climate change influences in hydrometeorological variables are becoming evident in some places, there have been suggestions that nonstationary statistics would be better to represent the stochastic properties of the extreme floods. The probabilistic estimation of non-stationary models, however, is surrounded with uncertainty related to scarcity of observations and modelling complexities hence the difficulty to project the future condition. In the face of uncertain future and the subjectivity of model choices, this study attempts to demonstrate the practical implications of applying a nonstationary model and compares it with a stationary model in flood risk assessment. A fully integrated framework to simulate decision makers’ behaviour in flood frequency analysis is thereby developed. The framework is applied to hypothetical flood risk management decisions and the outcomes are compared with those of known underlying future conditions. Uncertainty of the economic performance of the risk-based decisions is assessed through Monte Carlo simulations. Sensitivity of the results is also tested by varying the possible magnitude of future changes. The application provides quantitative and qualitative comparative results that satisfy a preliminary analysis of whether the nonstationary model complexity should be applied to improve the economic performance of decisions. Results obtained from the case study shows that the relative differences of competing models for all considered possible future changes are small, suggesting that stationary assumptions are preferred to a shift to nonstationary statistics for practical application of flood risk management. Nevertheless, nonstationary assumption should also be considered during a planning stage in addition to stationary assumption

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  19. A survey of cross-section sensitivity analysis as applied to radiation shielding

    International Nuclear Information System (INIS)

    Goldstein, H.

    1977-01-01

    Cross section sensitivity studies revolve around finding the change in the value of an integral quantity, e.g. transmitted dose, for a given change in one of the cross sections. A review is given of the principal methodologies for obtaining the sensitivity profiles-principally direct calculations with altered cross sections, and linear perturbation theory. Some of the varied applications of cross section sensitivity analysis are described, including the practice, of questionable value, of adjusting input cross section data sets so as to provide agreement with integral experiments. Finally, a plea is made for using cross section sensitivity analysis as a powerful tool for analysing the transport mechanisms of particles in radiation shields and for constructing models of how cross section phenomena affect the transport. Cross section sensitivities in the shielding area have proved to be highly problem-dependent. Without the understanding afforded by such models, it is impossible to extrapolate the conclusions of cross section sensitivity analysis beyond the narrow limits of the specific situations examined in detail. Some of the elements that might be of use in developing the qualitative models are presented. (orig.) [de

  20. A framework for sensitivity analysis of decision trees.

    Science.gov (United States)

    Kamiński, Bogumił; Jakubczyk, Michał; Szufel, Przemysław

    2018-01-01

    In the paper, we consider sequential decision problems with uncertainty, represented as decision trees. Sensitivity analysis is always a crucial element of decision making and in decision trees it often focuses on probabilities. In the stochastic model considered, the user often has only limited information about the true values of probabilities. We develop a framework for performing sensitivity analysis of optimal strategies accounting for this distributional uncertainty. We design this robust optimization approach in an intuitive and not overly technical way, to make it simple to apply in daily managerial practice. The proposed framework allows for (1) analysis of the stability of the expected-value-maximizing strategy and (2) identification of strategies which are robust with respect to pessimistic/optimistic/mode-favoring perturbations of probabilities. We verify the properties of our approach in two cases: (a) probabilities in a tree are the primitives of the model and can be modified independently; (b) probabilities in a tree reflect some underlying, structural probabilities, and are interrelated. We provide a free software tool implementing the methods described.

  1. Sensitivity analysis of limit state functions for probability-based plastic design

    Science.gov (United States)

    Frangopol, D. M.

    1984-01-01

    The evaluation of the total probability of a plastic collapse failure P sub f for a highly redundant structure of random interdependent plastic moments acted on by random interdepedent loads is a difficult and computationally very costly process. The evaluation of reasonable bounds to this probability requires the use of second moment algebra which involves man statistical parameters. A computer program which selects the best strategy for minimizing the interval between upper and lower bounds of P sub f is now in its final stage of development. The relative importance of various uncertainties involved in the computational process on the resulting bounds of P sub f, sensitivity is analyzed. Response sensitivities for both mode and system reliability of an ideal plastic portal frame are shown.

  2. Analytical sensitivity analysis of geometric errors in a three axis machine tool

    International Nuclear Information System (INIS)

    Park, Sung Ryung; Yang, Seung Han

    2012-01-01

    In this paper, an analytical method is used to perform a sensitivity analysis of geometric errors in a three axis machine tool. First, an error synthesis model is constructed for evaluating the position volumetric error due to the geometric errors, and then an output variable is defined, such as the magnitude of the position volumetric error. Next, the global sensitivity analysis is executed using an analytical method. Finally, the sensitivity indices are calculated using the quantitative values of the geometric errors

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

    International Nuclear Information System (INIS)

    Pin, F.G.

    1987-01-01

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

  4. Uncertainty and sensitivity analysis for the simulation of a station blackout scenario in the Jules Horowitz Reactor

    International Nuclear Information System (INIS)

    Ghione, Alberto; Noel, Brigitte; Vinai, Paolo; Demazière, Christophe

    2017-01-01

    Highlights: • A station blackout scenario in the Jules Horowitz Reactor is analyzed using CATHARE. • Input and model uncertainties relevant to the transient, are considered. • A statistical methodology for the propagation of the uncertainties is applied. • No safety criteria are exceeded and sufficiently large safety margins are estimated. • The most influential uncertainties are determined with a sensitivity analysis. - Abstract: An uncertainty and sensitivity analysis for the simulation of a station blackout scenario in the Jules Horowitz Reactor (JHR) is presented. The JHR is a new material testing reactor under construction at CEA on the Cadarache site, France. The thermal-hydraulic system code CATHARE is applied to investigate the response of the reactor system to the scenario. The uncertainty and sensitivity study was based on a statistical methodology for code uncertainty propagation, and the ‘Uncertainty and Sensitivity’ platform URANIE was used. Accordingly, the input uncertainties relevant to the transient, were identified, quantified, and propagated to the code output. The results show that the safety criteria are not exceeded and sufficiently large safety margins exist. In addition, the most influential input uncertainties on the safety parameters were found by making use of a sensitivity analysis.

  5. Experiment-Based Sensitivity Analysis of Scaled Carbon-Fiber-Reinforced Elastomeric Isolators in Bonded Applications

    Directory of Open Access Journals (Sweden)

    Farshad Hedayati Dezfuli

    2016-01-01

    Full Text Available Fiber-reinforced elastomeric isolators (FREIs are a new type of elastomeric base isolation systems. Producing FREIs in the form of long laminated pads and cutting them to the required size significantly reduces the time and cost of the manufacturing process. Due to the lack of adequate information on the performance of FREIs in bonded applications, the goal of this study is to assess the performance sensitivity of 1/4-scale carbon-FREIs based on the experimental tests. The scaled carbon-FREIs are manufactured using a fast cold-vulcanization process. The effect of several factors including the vertical pressure, the lateral cyclic rate, the number of rubber layers, and the thickness of carbon fiber-reinforced layers are explored on the cyclic behavior of rubber bearings. Results show that the effect of vertical pressure on the lateral response of base isolators is negligible. However, decreasing the cyclic loading rate increases the lateral flexibility and the damping capacity. Additionally, carbon fiber-reinforced layers can be considered as a minor source of energy dissipation.

  6. Sensitivity-based virtual fields for the non-linear virtual fields method

    Science.gov (United States)

    Marek, Aleksander; Davis, Frances M.; Pierron, Fabrice

    2017-09-01

    The virtual fields method is an approach to inversely identify material parameters using full-field deformation data. In this manuscript, a new set of automatically-defined virtual fields for non-linear constitutive models has been proposed. These new sensitivity-based virtual fields reduce the influence of noise on the parameter identification. The sensitivity-based virtual fields were applied to a numerical example involving small strain plasticity; however, the general formulation derived for these virtual fields is applicable to any non-linear constitutive model. To quantify the improvement offered by these new virtual fields, they were compared with stiffness-based and manually defined virtual fields. The proposed sensitivity-based virtual fields were consistently able to identify plastic model parameters and outperform the stiffness-based and manually defined virtual fields when the data was corrupted by noise.

  7. Methylation-sensitive amplified polymorphism-based genome-wide analysis of cytosine methylation profiles in Nicotiana tabacum cultivars.

    Science.gov (United States)

    Jiao, J; Wu, J; Lv, Z; Sun, C; Gao, L; Yan, X; Cui, L; Tang, Z; Yan, B; Jia, Y

    2015-11-26

    This study aimed to investigate cytosine methylation profiles in different tobacco (Nicotiana tabacum) cultivars grown in China. Methylation-sensitive amplified polymorphism was used to analyze genome-wide global methylation profiles in four tobacco cultivars (Yunyan 85, NC89, K326, and Yunyan 87). Amplicons with methylated C motifs were cloned by reamplified polymerase chain reaction, sequenced, and analyzed. The results show that geographical location had a greater effect on methylation patterns in the tobacco genome than did sampling time. Analysis of the CG dinucleotide distribution in methylation-sensitive polymorphic restriction fragments suggested that a CpG dinucleotide cluster-enriched area is a possible site of cytosine methylation in the tobacco genome. The sequence alignments of the Nia1 gene (that encodes nitrate reductase) in Yunyan 87 in different regions indicate that a C-T transition might be responsible for the tobacco phenotype. T-C nucleotide replacement might also be responsible for the tobacco phenotype and may be influenced by geographical location.

  8. Sensitive Multi-Species Emissions Monitoring: Infrared Laser-Based Detection of Trace-Level Contaminants

    Energy Technology Data Exchange (ETDEWEB)

    Steill, Jeffrey D. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Huang, Haifeng [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Hoops, Alexandra A. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Patterson, Brian D. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Birtola, Salvatore R. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Jaska, Mark [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Strecker, Kevin E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Chandler, David W. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Bisson, Soott [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

    2014-09-01

    This report summarizes our development of spectroscopic chemical analysis techniques and spectral modeling for trace-gas measurements of highly-regulated low-concentration species present in flue gas emissions from utility coal boilers such as HCl under conditions of high humidity. Detailed spectral modeling of the spectroscopy of HCl and other important combustion and atmospheric species such as H 2 O, CO 2 , N 2 O, NO 2 , SO 2 , and CH 4 demonstrates that IR-laser spectroscopy is a sensitive multi-component analysis strategy. Experimental measurements from techniques based on IR laser spectroscopy are presented that demonstrate sub-ppm sensitivity levels to these species. Photoacoustic infrared spectroscopy is used to detect and quantify HCl at ppm levels with extremely high signal-to-noise even under conditions of high relative humidity. Additionally, cavity ring-down IR spectroscopy is used to achieve an extremely high sensitivity to combustion trace gases in this spectral region; ppm level CH 4 is one demonstrated example. The importance of spectral resolution in the sensitivity of a trace-gas measurement is examined by spectral modeling in the mid- and near-IR, and efforts to improve measurement resolution through novel instrument development are described. While previous project reports focused on benefits and complexities of the dual-etalon cavity ring-down infrared spectrometer, here details on steps taken to implement this unique and potentially revolutionary instrument are described. This report also illustrates and critiques the general strategy of IR- laser photodetection of trace gases leading to the conclusion that mid-IR laser spectroscopy techniques provide a promising basis for further instrument development and implementation that will enable cost-effective sensitive detection of multiple key contaminant species simultaneously.

  9. 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)

  10. Sensitivity analysis of a discrete fracture network model for performance assessment of Aberg

    International Nuclear Information System (INIS)

    Outters, N.; Shuttle, D.

    2000-12-01

    This report presents a sensitivity analysis of pathway simulations in a DFN model. The DFN model consists of two sets of stochastic fractures at different scales and the canister locations of a hypothetical repository layout. The hydrogeological base case model is defined by constant head boundary conditions on the edges of a 2000 x 2000 x 1000 m 3 block. The pathway analysis carried out by the program PAWorks provides pathway parameters (pathway length, pathway width, transport aperture, reactive surface area, pathway transmissivity), canister statistics (average number of pathways per canister, percentage of canister locations with pathways) and visualisation of pathways. The project provided the following results from the alternative cases: Case 1: Model with a 100 m thick fracture network at the repository scale instead of 50 m in the base case. The model is little sensitive to the increase of the thickness of the local fracture network. Case 2: Model including fracture networks where the mean size and size standard deviation is twice the ones used in the base case. The travel times to the biosphere is slightly shortened by increasing the fracture diameter. Case 3: Two models with alternative hydraulic boundary conditions: two different flux boundary conditions are tested instead of head boundary conditions in the base case. The advective travel time is shortened by changing the boundary conditions in both alternative cases; in some cases it is reduced to less than a year. Case 4: Study of alternative pathway search algorithms: the pathway search is here based on minimum travel time. The pathway search algorithm of PAWorks based on minimum travel time gives much more optimistic results than the base case where the maximum flow rate was used. The mean travel time is about 5000 years. Due to editorial reasons only a subset of all this information is treated in this report

  11. 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...

  12. Visualization of Global Sensitivity Analysis Results Based on a Combination of Linearly Dependent and Independent Directions

    Science.gov (United States)

    Davies, Misty D.; Gundy-Burlet, Karen

    2010-01-01

    A useful technique for the validation and verification of complex flight systems is Monte Carlo Filtering -- a global sensitivity analysis that tries to find the inputs and ranges that are most likely to lead to a subset of the outputs. A thorough exploration of the parameter space for complex integrated systems may require thousands of experiments and hundreds of controlled and measured variables. Tools for analyzing this space often have limitations caused by the numerical problems associated with high dimensionality and caused by the assumption of independence of all of the dimensions. To combat both of these limitations, we propose a technique that uses a combination of the original variables with the derived variables obtained during a principal component analysis.

  13. Highly sensitive dendrimer-based nanoplasmonic biosensor for drug allergy diagnosis.

    Science.gov (United States)

    Soler, Maria; Mesa-Antunez, Pablo; Estevez, M-Carmen; Ruiz-Sanchez, Antonio Jesus; Otte, Marinus A; Sepulveda, Borja; Collado, Daniel; Mayorga, Cristobalina; Torres, Maria Jose; Perez-Inestrosa, Ezequiel; Lechuga, Laura M

    2015-04-15

    A label-free biosensing strategy for amoxicillin (AX) allergy diagnosis based on the combination of novel dendrimer-based conjugates and a recently developed nanoplasmonic sensor technology is reported. Gold nanodisks were functionalized with a custom-designed thiol-ending-polyamido-based dendron (d-BAPAD) peripherally decorated with amoxicilloyl (AXO) groups (d-BAPAD-AXO) in order to detect specific IgE generated in patient's serum against this antibiotic during an allergy outbreak. This innovative strategy, which follows a simple one-step immobilization procedure, shows exceptional results in terms of sensitivity and robustness, leading to a highly-reproducible and long-term stable surface which allows achieving extremely low limits of detection. Moreover, the viability of this biosensor approach to analyze human biological samples has been demonstrated by directly analyzing and quantifying specific anti-AX antibodies in patient's serum without any sample pretreatment. An excellent limit of detection (LoD) of 0.6ng/mL (i.e. 0.25kU/L) has been achieved in the evaluation of clinical samples evidencing the potential of our nanoplasmonic biosensor as an advanced diagnostic tool to quickly identify allergic patients. The results have been compared and validated with a conventional clinical immunofluorescence assay (ImmunoCAP test), confirming an excellent correlation between both techniques. The combination of a novel compact nanoplasmonic platform and a dendrimer-based strategy provides a highly sensitive label free biosensor approach with over two times better detectability than conventional SPR. Both the biosensor device and the carrier structure hold great potential in clinical diagnosis for biomarker analysis in whole serum samples and other human biological samples. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Using trajectory sensitivity analysis to find suitable locations of series compensators for improving rotor angle stability

    DEFF Research Database (Denmark)

    Nasri, Amin; Eriksson, Robert; Ghandhar, Mehrdad

    2014-01-01

    This paper proposes an approach based on trajectory sensitivity analysis (TSA) to find most suitable placement of series compensators in the power system. The main objective is to maximize the benefit of these devices in order to enhance the rotor angle stability. This approach is formulated...

  15. Sensitivity analysis of energy demands on performance of CCHP system

    International Nuclear Information System (INIS)

    Li, C.Z.; Shi, Y.M.; Huang, X.H.

    2008-01-01

    Sensitivity analysis of energy demands is carried out in this paper to study their influence on performance of CCHP system. Energy demand is a very important and complex factor in the optimization model of CCHP system. Average, uncertainty and historical peaks are adopted to describe energy demands. The mix-integer nonlinear programming model (MINLP) which can reflect the three aspects of energy demands is established. Numerical studies are carried out based on energy demands of a hotel and a hospital. The influence of average, uncertainty and peaks of energy demands on optimal facility scheme and economic advantages of CCHP system are investigated. The optimization results show that the optimal GT's capacity and economy of CCHP system mainly lie on the average energy demands. Sum of capacities of GB and HE is equal to historical heating demand peaks, and sum of capacities of AR and ER are equal to historical cooling demand peaks. Maximum of PG is sensitive with historical peaks of energy demands and not influenced by uncertainty of energy demands, while the corresponding influence on DH is adverse

  16. 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)

  17. 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

  18. A combined sensitivity analysis and kriging surrogate modeling for early validation of health indicators

    International Nuclear Information System (INIS)

    Lamoureux, Benjamin; Mechbal, Nazih; Massé, Jean-Rémi

    2014-01-01

    To increase the dependability of complex systems, one solution is to assess their state of health continuously through the monitoring of variables sensitive to potential degradation modes. When computed in an operating environment, these variables, known as health indicators, are subject to many uncertainties. Hence, the stochastic nature of health assessment combined with the lack of data in design stages makes it difficult to evaluate the efficiency of a health indicator before the system enters into service. This paper introduces a method for early validation of health indicators during the design stages of a system development process. This method uses physics-based modeling and uncertainties propagation to create simulated stochastic data. However, because of the large number of parameters defining the model and its computation duration, the necessary runtime for uncertainties propagation is prohibitive. Thus, kriging is used to obtain low computation time estimations of the model outputs. Moreover, sensitivity analysis techniques are performed upstream to determine the hierarchization of the model parameters and to reduce the dimension of the input space. The validation is based on three types of numerical key performance indicators corresponding to the detection, identification and prognostic processes. After having introduced and formalized the framework of uncertain systems modeling and the different performance metrics, the issues of sensitivity analysis and surrogate modeling are addressed. The method is subsequently applied to the validation of a set of health indicators for the monitoring of an aircraft engine’s pumping unit

  19. 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....

  20. Sensitivity analysis of network DEA illustrated in branch banking

    OpenAIRE

    N. Avkiran

    2010-01-01

    Users of data envelopment analysis (DEA) often presume efficiency estimates to be robust. While traditional DEA has been exposed to various sensitivity studies, network DEA (NDEA) has so far escaped similar scrutiny. Thus, there is a need to investigate the sensitivity of NDEA, further compounded by the recent attention it has been receiving in literature. NDEA captures the underlying performance information found in a firm?s interacting divisions or sub-processes that would otherwise remain ...