Decay Branch Ratio Sampling Method with Dirichlet Distribution

Yizhen Wang, Menglei Cui, Jiong Guo (), Han Zhang, Yingjie Wu and Fu Li
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Yizhen Wang: Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advance Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084, China
Menglei Cui: Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advance Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084, China
Jiong Guo: Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advance Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084, China
Han Zhang: Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advance Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084, China
Yingjie Wu: Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advance Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084, China
Fu Li: Institute of Nuclear and New Energy Technology, Collaborative Innovation Center of Advance Nuclear Energy Technology, Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education, Tsinghua University, Beijing 100084, China

Energies, 2023, vol. 16, issue 4, 1-17

Abstract: The decay branch ratio is evaluated nuclear data related to the decay heat calculation in reactor safety analysis. Decay branch ratio data are inherently subjected to the “sum-to-one” constraint, making it difficult to generate perturbed samples while preserving their suggested statistics in a library of evaluated nuclear data. Therefore, a stochastic-sampling-based uncertainty analysis method is hindered in quantifying the uncertainty contribution of the decay branch ratio to the decay heat calculation. In the present work, two alternative sampling methods are introduced, based on Dirichlet and generalized Dirichlet distribution, to tackle the decay branch ratio sampling issue. The performance of the introduced methods is justified by three-branch decay data retrieved from ENDF/B-VIII.0. The results show that the introduced sampling methods are capable of generating branch ratio samples and preserving their suggested statistics in an evaluated nuclear data library while satisfying their inherent “sum-to-one” constraint. These decay-branch-ratio sampling methods are expected to be alternative procedures in conducting stochastic-sampling-based uncertainty analyses of the decay branch ratio in reactor simulations.

Keywords: decay branch ratio; Dirichlet distribution; generalized Dirichlet distribution; stochastic sampling; uncertainty analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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