Mesh‑free semi‑quantitative variance underestimation elimination method in Monte Caro algorithm  

作　　者：Peng‑Fei Shen Xiao‑Dong Huo Ze‑Guang Li Zeng Shao Hai‑Feng Yang Peng Zhang Kan Wang 

机构地区：[1]Department of Engineering Physics,Tsinghua University,Beijing 100084,China [2]China Nuclear Power Engineering Corporation,Beijing 100840,China

出　　处：《Nuclear Science and Techniques》2023年第1期157-171,共15页核技术（英文）

基　　金：supported by China Nuclear Power Engineering Co.,Ltd.Scientific Research Project(No.KY22104);the fellowship of China Postdoctoral Science Foundation(No.2022M721793).

摘　　要：The inter-cycle correlation of fission source distributions(FSDs)in the Monte Carlo power iteration process results in variance underestimation of tallied physical quantities,especially in large local tallies.This study provides a mesh-free semiquantitative variance underestimation elimination method to obtain a credible confidence interval for the tallied results.This method comprises two procedures:Estimation and Elimination.The FSD inter-cycle correlation length is estimated in the Estimation procedure using the Sliced Wasserstein distance algorithm.The batch method was then used in the elimination procedure.The FSD inter-cycle correlation length was proved to be the optimum batch length to eliminate the variance underestimation problem.We exemplified this method using the OECD sphere array model and 3D PWR BEAVRS model.The results showed that the average variance underestimation ratios of local tallies declined from 37 to 87%to within±5%in these models.

关 键 词：Monte Carlo algorithm Power iteration process Inter-cycle correlation Variance underestimation Sliced Wasserstein distance 

分 类 号：O57[理学—粒子物理与原子核物理]