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基于蒙特卡罗正算输运的全局减方差方法

史涛 马纪敏 邱有恒 黄洪文 李正宏 钱达志

史涛, 马纪敏, 邱有恒, 等. 基于蒙特卡罗正算输运的全局减方差方法[J]. 强激光与粒子束, 2018, 30: 016006. doi: 10.11884/HPLPB201830.170163
引用本文: 史涛, 马纪敏, 邱有恒, 等. 基于蒙特卡罗正算输运的全局减方差方法[J]. 强激光与粒子束, 2018, 30: 016006. doi: 10.11884/HPLPB201830.170163
Shi Tao, Ma Jimin, Qiu Youheng, et al. Global variance reduction based on forward Monte Carlo calculation[J]. High Power Laser and Particle Beams, 2018, 30: 016006. doi: 10.11884/HPLPB201830.170163
Citation: Shi Tao, Ma Jimin, Qiu Youheng, et al. Global variance reduction based on forward Monte Carlo calculation[J]. High Power Laser and Particle Beams, 2018, 30: 016006. doi: 10.11884/HPLPB201830.170163

基于蒙特卡罗正算输运的全局减方差方法

doi: 10.11884/HPLPB201830.170163
基金项目: 

国家磁约束聚变能研究专项 2015GB108003

详细信息
    作者简介:

    史涛(1989—),男,博士研究生,从事反应堆物理和蒙特卡罗屏蔽计算方法研究; shitao5210@126.com

    通讯作者:

    钱达志(1968—),男,研究生导师,现从事反应堆物理、热工水力和工程管理工作; qdz1968@vip.sina.com

  • 中图分类号: TL328

Global variance reduction based on forward Monte Carlo calculation

  • 摘要: 蒙特卡罗方法是当前形势下辐射屏蔽计算的首选分析工具。小概率深穿透问题则是屏蔽计算的关键与亟待解决的核心问题,需要使用有效的减方差技巧。针对全局问题,利用蒙特卡罗正算输运得到的粒子通量或探测响应来构建权重窗参数,将现有的粒子位置偏移拓展到位置和能量偏倚。利用国际屏蔽基准题进行测试验证,通过使用该方法,粒子被引导到模型的所有位置。平均相对误差降低到10%以下,几乎所有网格区域都有粒子统计。结果表明,基于蒙特卡罗正算输运的输运偏倚参数构建方法能够实现全局减方差。
  • 图  1  简单屏蔽区域和复杂堆芯区域

    Figure  1.  Bulk shield zone and complex geometry zone

    图  2  蒙特卡罗辐射屏蔽问题

    Figure  2.  Monte Carlo radiation shielding problem

    图  3  EURACOS国际屏蔽基准题的总体布置

    Figure  3.  Geometry of EURACOS model and source

    图  4  不同计算方案的通量分布

    Figure  4.  Flux distribution of different calculation schemes

    图  5  不同计算方案的相对误差分布

    Figure  5.  Relative error distribution of different calculation schemes

    表  1  不同方案的计算结果

    Table  1.   Results of different calculation schemes

    case time/min average relative error/% FOM empty mesh ratio/% sample rate/min-1
    analog 30 57.76 0.066 32.96 1.521×105
    1st iteration 30 32.34 0.145 9.906 0.827×105
    2nd iteration 30 15.34 0.271 1.099 0.832×105
    3rd iteration 30 10.37 0.527 0.055 0.845×105
    4th iteration 30 9.100 0.540 0.001 25 0.836×105
    5th iteration 30 8.130 0.545 0.000 42 0.848×105
    下载: 导出CSV
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出版历程
  • 收稿日期:  2017-05-08
  • 修回日期:  2017-09-14
  • 刊出日期:  2018-01-15

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