Lognormal-Based Sampling for Fission Product Yields Uncertainty Propagation in Pebble-Bed HTGR

Autor: Jinlin Niu, Menglei Cui, Yingjie Wu, Baokun Liu, Yizhen Wang, Fu Li, Jiong Guo
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Science and Technology of Nuclear Installations, Vol 2020 (2020)
ISSN: 1687-6075
DOI: 10.1155/2020/8014521
Popis: Uncertainty analyses of fission product yields are indispensable in evaluating reactor burnup and decay heat calculation credibility. Compared with neutron cross section, there are fewer uncertainty analyses conducted and it has been a controversial topic by lack of properly estimated covariance matrix as well as adequate sampling method. Specifically, the conventional normal-based sampling method in sampling large uncertainty independent fission yields could inevitably generate nonphysical negative samples. Cutting off these samples would introduce bias into uncertainty results. Here, we evaluate thermal neutron-induced U-235 independent fission yields covariance matrix by the Bayesian updating method, and then we use lognormal-based sampling method to overcome the negative fission yields samples issue. Fission yields uncertainty contribution to effective multiplication factor and several fission products’ atomic densities at equilibrium core of pebble-bed HTGR are quantified and investigated. The results show that the lognormal-based sampling method could prevent generating negative yields samples and maintain the skewness of fission yields distribution. Compared with the zero cut-off normal-based sampling method, the lognormal-based sampling method evaluates the uncertainty of effective multiplication factor and atomic densities are larger. This implies that zero cut-off effect in the normal-based sampling method would underestimate the fission yields uncertainty contribution. Therefore, adopting the lognormal-based sampling method is crucial for providing reliable uncertainty analysis results in fission product yields uncertainty analysis.
Databáze: OpenAIRE
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