用于厚屏蔽小探测器的蒙特卡罗模拟减方差方法研究

反应堆屏蔽计算中经常出现厚屏蔽、小探测器问题，常规蒙特卡罗方法难以有效解决。基于自动重要抽样（AIS）方法，本文提出了小探测器自动重要抽样(SDAIS)方法，并针对小探测器问题，优化了AIS方法的虚粒子赌分裂算法。该方法在自主开发的蒙特卡罗屏蔽程序MCShield上进行了实现。使用NUREG/CR-6115 PWR基准题验证该方法的正确性和计算效率。结果表明，SDAIS方法可有效地解决厚屏蔽小探测器问题，相比AIS方法及传统的重要性方法，计算效率提升1~2个量级。

Study on Monte Carlo Variance Reduction Method for Thick Shield and Small Detector Problem

Thick shield and small detector problem often occurs in reactor shielding calculation. It is difficult to solve it by the conventional Monte Carlo method. A variance reduction method called small detector auto-importance sampling (SDAIS) method was proposed for the thick shield and small detector problem. The SDAIS method is the improved method of the auto-importance sampling (AIS) method in the case of small detector problem. The virtual particle Russian roulette method was used based on the detector position instead of the weight. The SDAIS method was implemented in the self-developed Monte Carlo program MCShield. The NUREG/CR-6115 PWR benchmark was used to verify the correctness and computational efficiency of the method. The results show that compared with the AIS method and the traditional importance method, the calculation efficiency of SDAIS method has an improvement of 1-2 orders of magnitude. SDAIS method can effectively solve the problem of thick shield and small detector.