Abstract

Uncertainty quantification (UQ) was performed using the Consortium for the Advanced Simulation of Light Water Reactors (CASL) multiphysics core simulator VERA. Typically, only nuclear data cross sections are considered when trying to obtain uncertainty information in reactor simulation applications. In this paper, uncertainty in both nuclear cross section data and fuel manufacturing processes is analyzed using VERA. Uncertainties due to cross sections was determined by generating one thousand perturbed cross section libraries using the cross section covariance data provided in the evaluated nuclear data library. Uncertainty due to manufacturing was also determined using stochastic sampling and VERA. The use of similar stochastic sampling techniques for the same problems allows for the direct comparison of uncertainty stemming from the two sources of uncertainty. Sample size is considered due to the potentially large computational cost of stochastic sampling techniques, as is demonstrated in a full core depletion. It was found that for the Pressurized Water Reactor (PWR) pincell case at Hot Zero Power (HZP), the standard deviation in the neutron multiplication factor produced by material uncertainty was 101 pcm, while the standard deviation in the neutron multiplication factor produced by cross section uncertainty was 730 pcm. While the uncertainty in neutron multiplication factor due to cross section uncertainty is larger than uncertainty due to manufacturing uncertainties, neglecting manufacturing uncertainties may be an unacceptable oversight in certain high-precision simulation applications.

Highlights

  • Uncertainty is inherent in any real system

  • Uncertainties in cross sections and material parameters will be propagated through the Consortium for the Advanced Simulation of Light Water Reactors’ (CASL) code system, the Virtual Environment for Reactor Applications (VERA)

  • Material uncertainties were only examined in the Pressurized Water Reactor (PWR) pincell at Hot Zero Power (HZP)

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Summary

Introduction

While uncertainty is sometimes neglected when modeling systems, its quantification is extremely important. If uncertainty can be accurately estimated, greater confidence can be placed in simulated results. Having greater confidence in the validity of simulated results is hugely beneficial, as non-simulated experimental results are extremely expensive to obtain. In this project, uncertainties in cross sections and material parameters will be propagated through the Consortium for the Advanced Simulation of Light Water Reactors’ (CASL) code system, the Virtual Environment for Reactor Applications (VERA). Due to the noninvasive nature of stochastic sampling, computer codes can be used as models to propagate uncertainty which is beneficial when performing multiphysics simulations

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