Inverse uncertainty quantification of reactor simulations under the Bayesian framework using surrogate models constructed by polynomial chaos expansion
X Wu, T Kozlowski - Nuclear Engineering and Design, 2017 - Elsevier
Modeling and simulations are naturally augmented by extensive Uncertainty Quantification
(UQ) and sensitivity analysis requirements in the nuclear reactor system design, in which
uncertainties must be quantified in order to prove that the investigated design stays within
acceptance criteria. Historically, expert judgment has been used to specify the nominal
values, probability density functions and upper and lower bounds of the simulation code
random input parameters for the forward UQ process. The purpose of this paper is to replace …
(UQ) and sensitivity analysis requirements in the nuclear reactor system design, in which
uncertainties must be quantified in order to prove that the investigated design stays within
acceptance criteria. Historically, expert judgment has been used to specify the nominal
values, probability density functions and upper and lower bounds of the simulation code
random input parameters for the forward UQ process. The purpose of this paper is to replace …
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