基于粒子群优化算法的压水堆换料优化初步研究

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基金项目:

中央高校基本科研业务费专项资金(11lgpy90)

“百人计划”引进人才科研启动经费

教育部“新世纪优秀人才支持计划”(NCET-10-0846)

Study on Fuel Loading Pattern Optimization for A Pressurized Water Reactor Using Particles Warm Method

1. School of Physics and Engineering, Sun Yat-sen University, Guangzhou, 510275, China;
2. Sino-French Institute of' Nuclear Engineering & Technology, Sun Yat-sen University, Guangzhou, 510275, China

摘要: 基于大亚湾核电站压水堆堆芯燃料组件布置建立优化的数学模型,采用离散的多目标粒子群优化算法和基于有限元法的堆芯计算软件"Donjon",及组件计算软件"Dragon",将粒子群程序与堆芯物理计算软件结合,编制完整的堆芯燃料管理优化程序。应用此优化程序对大亚湾核电站初装料进行优化的结果表明:粒子群优化算法得到的优化方案与参考方案相比,k_eff增加11.9%,且功率峰因子低于1.4,满足安全限值。
- 压水堆 /
- 换料优化 /
- 粒子群算法
Abstract: A mathematical model for the loading pattern（LP） optimization for a pressurized water reactor（PWR） was established based on Daya Bay Nuclear Power Plant.The discreet,multi-objective particle swarm optimization algorithm was integrated with the core physics calculation code "Donjon" based on finite element method,and assembles group constant calculation code "Dragon",developing an optimizing code for fuel arrangement.This code is applied to optimize the first cycle loading of Daya Bay Nuclear Power Plant.The result shows that,compared with the reference LP,the core effective multiplication factor increases by 9.16%,while the local power peaking factor is lower than 1.4,satisfying the safety requirement.
- Pressurized Water Reactor（PWR） /
- Refueling optimization /
- Particle swarm method