ANSWERS® TOOLS FOR UNCERTAINTY QUANTIFICATION AND VALIDATION

Paul N Smith,Christophe Murphy,Tim Fry,Geoff Dobson,Simon Richards,Magda Stefanowska,Richard Hiles,Dave Hanlon,M Margulis,P Blaise

doi:10.1051/epjconf/202124715015

Abstract

ANSWERS® is developing a set of uncertainty quantification (UQ) tools for use with its major physics codes: WIMS/PANTHER (reactor physics), MONK (criticality and reactor physics) and MCBEND (shielding and dosimetry). The Visual Workshop integrated development environment allows the user to construct and edit code inputs, launch calculations, post-process results and produce graphs, and recently uncertainty quantification and optimisation tools have been added. Prior uncertainties due to uncertainties in nuclear data or manufacturing tolerances can be estimated using the sampling method or using the sensitivity options in the physics codes combined with appropriate covariance matrices. To aid the user in the choice of appropriate validation experiments, the MONK categorisation scheme and/or a similarity index can be used. An interactive viewer has been developed which allows the user to search through, and browse details of, over 2,000 MONK validation experiments that have been analysed from the ICSBEP and IRPhE validation sets. A Bayesian updating approach is used to assimilate the measured data with the calculated results. It is shown how this process can be used to reduce bias in calculated results and reduce the calculated uncertainty on those results. This process is illustrated by application to a PWR fuel assembly.

Highlights

When calculating best estimate reactor parameters of interest it is important to provide an accurate estimated value of a given parameter, and to provide a reliable estimate of the uncertainty on that estimated value
Initial uncertainty quantification (UQ) tool development focused on the sampling method in which the user can specify statistical distributions rather than numerical values for user-specified input parameters [3]
Capabilities have been included in the physics codes to calculate sensitivities which can be combined with a covariance matrix for the input parameters as an alternative way of undertaking UQ

Summary

INTRODUCTION

When calculating best estimate reactor parameters of interest it is important to provide an accurate estimated value of a given parameter, and to provide a reliable estimate of the uncertainty on that estimated value. For some years ANSWERS has been developing Visual Workshop, an Integrated Development Environment to accompany the physics codes This allows the user to construct and edit code inputs, launch calculations, post-process results and produce graphs, and recently uncertainty quantification and optimisation tools have been added. These methods are described and results for a PWR fuel assembly are presented. In this paper we concentrate on the Bayesian updating approach and describe how this is implemented in ANSWERS software It is shown how this process can be used to reduce bias in calculated results and reduce the uncertainty on the estimated quantities. This process is illustrated by application to a PWR fuel assembly

VISUAL WORKSHOP

VALIDATION DATABASE VIEWER

SIMILARITY INDEX

VALIDATION

EXAMPLE CALCULATION

CONCLUSIONS