Many different techniques have been proposed for performing uncertainty and sensitivity analyses on computer models for complex processes. The objective of the present study is to investigate the applicability of three widely used techniques to three computer models having large uncertainties and varying degrees of complexity in order to highlight some of the problem areas that must be addressed in actual applications. The following approaches to uncertainty and sensitivity analysis are considered: (1) response surface methodology based on input determined from a fractional factorial design; (2) Latin hypercube sampling with and without regression analysis; and (3) differential analysis. These techniques are investigated with respect to (1) ease of implementation, (2) flexibility, (3) estimation of the cumulative distribution function of the output, and (4) adaptability to different methods of sensitivity analysis. With respect to these criteria, the technique using Latin hypercube sampling and regression analysis had the best overall performance. The models used in the investigation are well documented, thus making it possible for researchers to make comparisons of other techniques with the results in this study.

An Investigation of Uncertainty and Sensitivity Analysis Techniques for Computer Models

Sensitivity and Uncertainty Analysis, Data Assimilation, and Predictive Best-Estimate Model Calibration

The theory of a new methodology for quantifying and then reducing the uncertainties in the pressure vessel fluences (or fluxes) of a pressurized water reactor (PWR) is described. The theory involves combining the results of calculated and measured dosimetry integral experiments along wit differential data used in the calculations, together with covariances, into a generalized linear leastsquares adjustment code named LEPRICON. The procedure solves the translation problem necessitated by the use of ex situ PWR dosimetry, and its covariance reducing potential is further enhanced by simultaneously combining the PWR data with a data base consisting of the results of analysis of simpler benchmark experiments. Development of this data base and a demonstration of the uncertainty reduction with application to one of the benchmark experiments are also described. For the example chosen, covariances of the calculated fluxes were reduced by factors of between 4 and 8.

Theory of a new unfolding procedure in pressurized water reactor pressure vessel dosimetry and development of an associated benchmark data base

Application of adjoint operators to neural learning

Optimum procedures for the statistical improvement, or adjustment, of an existing data evaluation are redeveloped from first principles, consistently employing a minimum-variance viewpoint. A set o...

Evaluation of Correlated Data Using Partitioned Least Squares: A Minimum-Variance Derivation

An advanced methodology for performing systematic uncertainty analysis of time-dependent nonlinear systems is presented. This methodology includes a capability for reducing uncertainties in system ...

Uncertainty Analysis of Time-Dependent Nonlinear Systems: Theory and Application to Transient Thermal Hydraulics

The development of a systematic methodology for the reduction of uncertainties in transient thermal-hydraulics by using in-bundle measurement data is presented. The adjustment of the system parameters and responses and the reduction in their respective uncertainties is treated as a time-dependent constrained minimization problem. An on-line (i.e., real time) large scale optimization scheme is also outlined. Although formulated within the framework of reactor safety analysis, the proposed methodology can be directly applied to other areas, for instance to time-dependent fuel cycle optimization and uncertainty analysis.

Systematic methodology for the reduction of uncertainties in transient thermal-hydraulics by using in-bundle measurement data

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Uncertainty Analysis of Time-Dependent Nonlinear Systems: Theory and Application to Transient Thermal Hydraulics

Systematic methodology for the reduction of uncertainties in transient thermal-hydraulics by using in-bundle measurement data

VITAMIN E: a multipurpose ENDF/B-V coupled neutron-gamma cross section library