S_N共轭函数用于蒙特卡罗粒子输运自动减方差的研究  

Application of S_N Adjoint Function on Automated Variance Reduction for Monte Carlo Particle Transport Calculation

作　　者：刘聪[1] 张斌[1] 张亮 郑君萧 陈义学[1] LIU Cong;ZHANG Bin;ZHANG Liang;ZHENG Junxiao;CHEN Yixuel(School of Nuclear Science and Engineering,North China Electric Power University,Beijing 102206,China;China Nuclear Power Technology Research Institute,Shenzhen 518026,China)

机构地区：[1]华北电力大学核科学与工程学院,北京102206 [2]中广核研究院有限公司,深圳518026

出　　处：《计算物理》2018年第5期535-544,共10页Chinese Journal of Computational Physics

基　　金：国家自然科学基金(11505059;11575061);中央高校基本科研业务费专项资金(2017XS087)资助项目

摘　　要：基于SN输运计算平台ARES编制了三维共轭输运计算模块,根据一致性共轭驱动重要性抽样方法自动生成减方差参数,用于加速MCNP5计算.数值结果表明,自动生成的减方差参数可有效提高蒙特卡罗计算效率,并保证结果无偏.自动减方差技术利用SN共轭函数可更经济准确的估计粒子重要性,避免手动估算减方差参数的复杂工作,对于复杂屏蔽问题的蒙特卡罗计算具有较好的应用前景.Three-dimensional adjoint transport calculation module was integrated into S_N transport code ARES in which automated variance reduction parameters are generated based on consistent adjoint driven importance sampling method to accelerate calculation of MCNP5. It shows that automated variance reduction parameters are effective to improve MC calculational efficiency and to produce unbiased statistical results. Automated variance reduction technique with S_N function estimates particle importance more economically and accurately. It avoids obstacles of manual estimation and could be applied for MC simulation of large-scale,complicated shielding problems.

关 键 词：离散纵标法 蒙特卡罗方法 共轭输运 权重窗 源偏倚 

分 类 号：TL328[核科学技术—核技术及应用]