Construction and Verification of Variance Reduction Technique System Based on Automatic Importance Sampling

Abstract

According to different objectives, shielding calculation problems can be divided into regional problem, source-detector problem, and global problem. To solve the deep penetration problem of the three kinds of problems, the MCShield research team systematically proposed a series of variance reduction methods. According to these works, this article constructed a variance reduction technique system based on the automatic importance sampling (AIS) method, and conducted some verification work. For the source-detector problem, the NUREG/CR-6115 PWR pressure vessel calculation benchmark was used to verify the small detector automatic importance sampling (SDAIS) method. The result shows that the SDAIS method is more efficient than the AIS method for the source-detector problem. In addition, an AIS-based Monte Carlo coupled variance reduction (AIS-CADIS) method was also proposed which introduces the AIS method into Monte Carlo adjoint calculations and was verified against benchmark problems. For global problems, the grid-based AIS method was proposed and verified using a simplified reactor shielding calculation problem. The results show that compared with the AIS method and analog Monte Carlo methods, the grid-based AIS method can improve calculation efficiency.

Keywords

• monte carlo
• automatic importance sampling method
• variance reduction technique
• mcshield program