摘要
新型核能与核动力装置的发展对辐射屏蔽设计方法提出了更高要求。面对空间堆、船用堆等装置的小型化、轻量化设计需求,传统辐射屏蔽多目标优化方法存在优化目标少、优化参数单一、全局性差等缺陷,难以满足辐射屏蔽智能设计的需求。本文基于第三代非支配排序遗传算法和改进多目标人工蜂群算法开展面向反应堆屏蔽层重量、体积和特定区域辐射剂量等多目标约束条件下的辐射屏蔽优化方法研究,并对各算法的优化性能、优化方案进行对比分析。结果表明,本文方法相较于传统屏蔽智能设计方法展现了更好的优化性能,并在实际工程问题中体现了可靠性,可为辐射屏蔽设计优化提供新思路。
The objective of radiation shielding design for nuclear reactors is to minimize external radiation doses(ALARA principle)by selecting appropriate shielding materials and structures to meet safety requirements for personnel.Furthermore,given the extensive use of nuclear energy in various sectors,shielding design must strike a balance between safety standards and considerations of compactness and lightweight design,as seen in marine nuclear power,land-based nuclear power sources,and space reactors.Thus,radiation shielding design for nuclear reactors poses a typical multi-objective combinatorial optimization challenge,involving various design objectives and parameters,including radiation dose rate,volume,weight,and more.Traditional multi-objective optimization methods for radiation shielding suffer from limitations such as a restricted number of optimization objectives,a limited set of optimization parameters,and suboptimal global optimization,rendering them inadequate for intelligent radiation shielding design.This paper introduced two multi-objective evolutionary algorithms,utilizing a non-dominated sorting genetic algorithm(NSGA-Ⅲ)based on reference point selection and a multi-objective artificial bee colony(MOABC)algorithm based on crowding distance selection.These algorithms were employed to conduct optimization studies for reactor shielding layer weight,volume,and specific region radiation dose.The algorithms’performance was evaluated on a simple three-dimensional shielding structure,and practical engineering tests were performed on complex shielding structures.In the initial set of tests,the numerical results demonstrate that the proposed methods outperform traditional optimization methods,as evidenced by superior hyper volume indicators and excellent performance in terms of average objective values for weight and volume dimensions under varying mutation probabilities.For complex models,the lightest optimized solution is selected for presentation.After MOABC optimization,the solution demonstrates reductio
作者
刘程伟
陈珍平
杨超
张华健
孙爱扣
雷济充
于涛
LIU Chengwei;CHEN Zhenping;YANG Chao;ZHANG Huajian;SUN Aikou;LEI Jichong;YU Tao(School of Nuclear Science and Technology,University of South China,Hengyang 421001,China;Key Laboratory of Advanced Nuclear Energy Design and Safety,Ministry of Education,University of South China,Hengyang 421001,China)
出处
《原子能科学技术》
EI
CAS
CSCD
北大核心
2024年第6期1261-1270,共10页
Atomic Energy Science and Technology
基金
国家自然科学基金(12175101)
湖南省自然科学基金(2022JJ40345)
衡阳市科技创新项目(202250045336)。
关键词
辐射屏蔽设计
多目标优化
进化算法
核反应堆
radiation shielding design
multi-objective optimization
evolutionary algorithm
nuclear reactor
