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结合多群GMRES的IRAM算法用于求解矩阵MOC方程

IRAM combined with multi-group GMRES for solving Matrix MOC

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【作者】 吴文斌李庆王侃

【Author】 WU Wen-bin;LI Qing;WANG Kan;Department of Engineering Physics,Tsinghua University;Science Technology on Reactor System Design Technology Laboratory,Nuclear Power Institute of China;

【机构】 清华大学工程物理系中国核动力研究设计院核反应堆系统设计技术重点实验室

【摘要】 矩阵MOC方法通过构造并求解线性方程组,代替传统MOC方法中反复地特征线扫描。求解中子输运方程临界问题时,通常采用幂迭代法求得keff。然而幂迭代法的收敛速度严重依赖于占优比,实际的较大规模的堆芯占优比接近于1,收敛很慢。本研究采用隐式再启动的Arnoldi算法(IRAM)求解keff,并应用多群耦合的GMRES算法直接求解含有上散射的多群问题,以避免能群间的散射迭代。采用C++语言编写了相关计算程序,对多个基准题如2D C5G7的数值结果表明,和幂迭代法相比,结合多群GMRES的IRAM算法具有良好的计算精度和更高的计算效率。

【Abstract】 In the Matrix MOC,a linear algebraic equation system can be constructed by sweeping only once,and then solving the linear system takes the place of repeatedly characteristics sweeping.In neutron transport critical problems,keff is traditionally computed by power iteration(PI),whose convergence rate is deeply dependent on the dominance ratio.Large problems of practical interest often have dominance ratios close to 1,leading to slow convergence of PI.In this study,keff is computed by the Implicitly Restarted Arnoldi Method(IRAM) combined with multi-group GMRES,in which multi-group problems coupled by upscatter are solved directly,avoiding upscatter iteration.Numerical results of several benchmarks such as 2D C5G7 demonstrate that IRAM combined with multi-group GMRES can obtain good accuracy and higher efficiency compared with PI.

【关键词】 矩阵MOC幂迭代法IRAM算法多群耦合GMRES
【Key words】 matrix MOCpower iterationIRAMmulti-group GMRES
  • 【会议录名称】 中国核科学技术进展报告(第三卷)——中国核学会2013年学术年会论文集第6册(核物理分卷、计算物理分卷、粒子加速器分卷)
  • 【会议名称】中国核学会2013年学术年会
  • 【会议时间】2013-09-11
  • 【会议地点】中国黑龙江哈尔滨
  • 【分类号】TL329.2
  • 【主办单位】中国核学会
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