原子能科学技术2018，Vol.52Issue(6)：987-993,7.DOI:10.7538/yzk.2017.youxian.0510
全局减方差方法的HBR-2基准题应用
Global Variance Reduction Method Applied to HBR-2 Benchmark
郑征 1梅其良 1邓力2
作者信息
- 1. 上海核工程研究设计院有限公司,上海 200233
- 2. 北京应用物理与计算数学研究所,北京 100190
- 折叠
摘要
Abstract
For deep-penetration shielding problem,it is a great challenge to obtain relia-ble results with Monte Carlo(MC)method in reasonable time.Local variance reduction(LVR)method and global variance reduction(GVR)method based on discrete ordinate(SN)method can decrease tally error of deep-penetration problem in MC calculation.Calculation efficiencies of LVR method and GVR method for the HBR-2 benchmark were compared in this paper.Numerical results show that LVR method and GVR meth-od both obtain satisfied results for the HBR-2 benchmark.GVR method can optimize both tallies of radiation surveillance capsule and ex-core detector at once,therefore it is more convenient and efficient.关键词
全局减方差方法/离散纵标方法/蒙特卡罗方法/源偏倚/权窗Key words
global variance reduction method/discrete ordinate method/Monte Carlo method/source biasing/weight window分类
能源科技引用本文复制引用
郑征,梅其良,邓力..全局减方差方法的HBR-2基准题应用[J].原子能科学技术,2018,52(6):987-993,7.
