Xu Wu

TL;DR: In this paper, an optimized FeCrAl cladding design from a detailed parametric study in literature is adopted, which suggests reducing the cladding thickness and slightly increasing the fuel enrichment.

TL;DR: In this article, the authors used Bayesian analysis to establish the inverse UQ formulation, with systematic and rigorously derived metamodels constructed by Gaussian Process (GP), and proposed an improved modular Bayesian approach that can avoid extrapolating the model discrepancy that is learnt from the inverse uncertainty quantification domain to the validation/prediction domain.

TL;DR: In this paper, inverse Uncertainty Quantification (UQ) under the Bayesian framework is applied to BISON code FGR model based on Riso-AN3 time series experimental data and the posterior distributions for the uncertain input factors can be used to replace the expert specifications for future uncertainty/sensitivity analysis.

TL;DR: This research addresses the “lack of input uncertainty information” issue for TRACE physical input parameters, which was usually ignored or described using expert opinion or user self-assessment in previous work.

TL;DR: This research solves the problem of lack of uncertainty information for TRACE physical model parameters for the closure relations by replacing such ad-hoc expert judgment with inverse Uncertainty Quantification (UQ) based on OECD/NRC BWR Full-size Fine-Mesh Bundle Tests (BFBT) benchmark steady-state void fraction data.