基于遗传算法的中子屏蔽材料组分优化研究

辐射防护 ›› 2020, Vol. 40 ›› Issue (1): 38-44.

基于遗传算法的中子屏蔽材料组分优化研究

陈法国, 李国栋, 杨明明, 韩毅, 梁润成

中国辐射防护研究院,山西太原 030006

收稿日期:2019-04-22 发布日期:2020-05-15
作者简介:陈法国(1987—),男,2008年本科毕业于清华大学核工程与核技术专业,2011年硕士毕业于中国辐射防护研究院辐射防护及环境保护专业,副研究员。E-mail:chenfaguo1@126.com

Optimization research on neutron shielding material component based on genetic algorithm

CHEN Faguo, LI Guodong, YANG Mingming, HAN Yi, LIANG Runcheng

China Institute for Radiation Protection, Taiyuan 030006

Received:2019-04-22 Published:2020-05-15

摘要/Abstract

摘要： 基于快速非支配排序遗传算法NSGA-II,开展了多目标屏蔽优化设计研究,建立了中子复合屏蔽材料组分的自动优化设计程序。以屏蔽剂量和材料密度最小化为目标,以聚乙烯、铅、硼、锂、铁、铝等材料均匀混合组成30 cm厚平板屏蔽结构为例,验证了优化算法程序的有效性。将基于遗传算法的屏蔽优化方法与设计人员的经验相结合,可更高效地实现多目标屏蔽优化设计。

关键词: 遗传算法, 多目标优化, 中子屏蔽, 材料组分

Abstract: Based on the fast non-dominated sorting genetic algorithm NSGA-II, multi-objective optimization of shielding design was studied, and automatic optimization design code for composite neutron shielding material component was developed. Aiming at the minimum shielding dose and material density, the effectiveness of the code is demonstrated by an example of 30 cm thick slab shield, which is composed of polyethylene, lead, steel, aluminum, boron and lithium homogeneously. Combining the shielding optimization method based on genetic algorithm and the experience of designer, multi-objective optimization of shielding design can be achieved more efficiently.

Key words: genetic algorithm, multi-objective optimization, neutron shielding, material component

中图分类号:

TL72

陈法国, 李国栋, 杨明明, 韩毅, 梁润成. 基于遗传算法的中子屏蔽材料组分优化研究[J]. 辐射防护, 2020, 40(1): 38-44.

CHEN Faguo, LI Guodong, YANG Mingming, HAN Yi, LIANG Runcheng. Optimization research on neutron shielding material component based on genetic algorithm[J]. RADIATION PROTECTION, 2020, 40(1): 38-44.

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