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基于嵌入蒙特卡罗模拟计算的遗传算法对多重测量装置~3He管排布的优化
Assignment of ~3He Tubes in Neutron Multiplicity Counter by Genetic Algorithm Based on Monte Carlo Code
【摘要】 为提高NDA方法测试分析精度,降低统计误差,在研制中子多重测量装置时通常将探测效率作为重要的设计目标。本文将蒙特卡罗模拟嵌入遗传算法中,以假想的90根3 He管中子多重测量装置为例,利用该方法对其3 He管分布进行理论模拟和优化,在短时间内求出探测效率为37%的最优排布。同时,利用蒙特卡罗模拟了随机抽样产生的1 000个有效排布,并对随机抽样分析与遗传算法结果进行比对分析。结果表明:利用遗传算法确定3 He管分布是快速有效的。
【Abstract】 A method for optimizing the most effective neutron multiplicity counter was proposed.The method used program of genetic algorithm and Monte Carlo method which coded by C++ to get 3He tubes assignment to maximize counter efficiency.The results validate the genetic algorithm based on Monte Carlo code for neutron calculations of more than 1 000 valid assignment of 3He is effective.
【关键词】 3He管排布;
蒙特卡罗模拟;
中子多重测量;
遗传算法;
【Key words】 assignment of 3He tubes; Monte Carlo simulation; neutron multiplicity; genetic algorithm;
【Key words】 assignment of 3He tubes; Monte Carlo simulation; neutron multiplicity; genetic algorithm;
- 【文献出处】 原子能科学技术 ,Atomic Energy Science and Technology , 编辑部邮箱 ,2011年11期
- 【分类号】O571.53
- 【被引频次】2
- 【下载频次】99