遗传算法在高通量工程试验堆燃料管理优化中的应用  

Application of Genetic Algorithm in the Fuel Management Optimization for the High Flux Engineering Test Reactor

作　　者：师学明[1] 吴宏春[1] 孙寿华 刘水清 

机构地区：[1]西安交通大学能动学院,710049 [2]中国核动力研究设计研究院,成都610041

出　　处：《核动力工程》2003年第4期317-322,共6页Nuclear Power Engineering

基　　金：国家自然科学基金资助(19901026)

摘　　要：建立了基于遗传算法的高通量工程试验堆(HFETR)堆内燃料管理优化模型。根据HFETR的实际情况,提出了基于组件位置的二进制编码/解码技术。研究了不同选择策略对算法性能的影响,探讨了遗传算法和专家经验的结合,吸收了自适应遗传算法的思想,得到了可直接应用于HFETR的优化换料方案。The in-core fuel management optimization model based on the genetic algorithm has been established. An encode/decode technique based on the assemblies position is presented according to the characteristics of HFETR. Different reproduction strategies have been studied. The expert knowledge and the adaptive genetic algorithms were incorporated into the code to get the optimized loading patterns that can be used in HFETR.

关 键 词：高通量工程试验堆 燃料管理 优化 遗传算法 

分 类 号：TL411.3[核科学技术—核技术及应用] TL32