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

doi:10.19596/j.cnki.1001-246x.7735

Abstract

Abstract: 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.

Key words: discrete ordinates method, Monte Carlo method, adjoint transport, weight window, source biasing

CLC Number:

TL328

LIU Cong, ZHANG Bin, ZHANG Liang, ZHENG Junxiao, CHEN Yixue. Application of S_N Adjoint Function on Automated Variance Reduction for Monte Carlo Particle Transport Calculation[J]. CHINESE JOURNAL OF COMPUTATIONAL PHYSICS, 2018, 35(5): 535-544.

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

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