| 用于厚屏蔽小探测器的蒙特卡罗模拟减方差方法研究 |
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| 引用本文： | 杲申申,李君利,武祯,马锐垚,王鑫,邱睿,李春艳,张辉. 用于厚屏蔽小探测器的蒙特卡罗模拟减方差方法研究[J]. 原子能科学技术, 2020, 54(7): 1294-1300. DOI: 10.7538/yzk.2019.youxian.0371 |
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| 作者姓名： | 杲申申 李君利 武祯 马锐垚 王鑫 邱睿 李春艳 张辉 |
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| 作者单位： | 清华大学 工程物理系,北京100084;粒子技术与辐射成像教育部重点实验室,北京100084;同方威视技术股份有限公司,北京100084;北京应用物理与计算数学研究所,北京100094 |
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| 摘 要： | 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。
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| 关 键 词： | 减方差 厚屏蔽 小探测器 自动重要抽样 |
Study on Monte Carlo Variance Reduction Method for Thick Shield and Small Detector Problem |
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| GAO Shenshen,LI Junli,WU Zhen,MA Ruiyao,WANG Xin,QIU Rui,LI Chunyan,ZHANG Hui. Study on Monte Carlo Variance Reduction Method for Thick Shield and Small Detector Problem[J]. Atomic Energy Science and Technology, 2020, 54(7): 1294-1300. DOI: 10.7538/yzk.2019.youxian.0371 |
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| Authors: | GAO Shenshen LI Junli WU Zhen MA Ruiyao WANG Xin QIU Rui LI Chunyan ZHANG Hui |
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| Affiliation: | Department of Engineering Physics, Tsinghua University, Beijing 100084, China;Key Laboratory of Particle & Radiation Imaging of Ministry of Education, Beijing 100084, China;Nuctech Company Limited, Beijing 100084, China;Institute of Applied Physics and Computational Mathematics, Beijing 100094, China |
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| Abstract: | 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. |
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| Keywords: | variance reduction method thick shield small detector auto-importance sampling method |
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