蒙特卡罗自动建模中的空腔简化算法研究
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  • 英文篇名:Improved Void Filling Algorithm for Automatic Monte Carlo Modeling
  • 作者:俞盛朋 ; 程梦云 ; 龙鹏程 ; 胡丽琴
  • 英文作者:YU Sheng-peng;CHENG Meng-yun;LONG Peng-cheng;HU Li-qin;Key Laboratory of Neutronics and Radiation Safety,Institute of Nuclear Energy Safety Technology,Chinese Academy of Sciences;
  • 关键词:SuperMC/MCAM ; 蒙特卡罗 ; 空腔简化
  • 英文关键词:SuperMC/MCAM;;Monte Carlo;;improved void filling
  • 中文刊名:YZJS
  • 英文刊名:Atomic Energy Science and Technology
  • 机构:中国科学院核能安全技术研究所中国科学院中子输运理论与辐射安全重点实验室;
  • 出版日期:2015-05-20
  • 出版单位:原子能科学技术
  • 年:2015
  • 期:v.49
  • 基金:中国科学院战略性先导科技专项资助项目(XDA03040000);中国科学院科技数据资源整合与共享工程“重点数据库”资助项目(XXH12504-1-09);; 国家自然科学基金资助项目(91026004,11305205);; 973计划资助项目(2014GB112001)
  • 语种:中文;
  • 页:YZJS2015S1006
  • 页数:5
  • CN:S1
  • ISSN:11-2044/TL
  • 分类号:44-48
摘要
考虑到粒子跟踪效率,在基于面描述的蒙特卡罗粒子输运模拟程序的计算模型中,除描述系统各部件的几何实体外,还需对非实体空间即空腔进行几何描述。由于空腔几何需严格填满实体间空隙,其建模复杂度通常较实体几何高,所以复杂系统常因空腔复杂度过高而严重制约蒙特卡罗建模和计算效率。本文研究了一种基于凸实体的自动空腔简化算法,该算法首先将栅元实体分解为凸实体集合,利用与子空间相交的凸实体的补集描述该子空间区域的空腔。该算法已在多物理耦合分析自动建模软件SuperMC/MCAM中实现,并使用国际热核聚变实验堆ITER中子学基准模型进行了测试。测试结果表明,相比基准算法,该算法可简化空腔表达式到1/60,提升转换效率25倍及生成模型的计算效率1.4倍。
        Considering the transport efficiency,all the spaces including solids and void space need to be described for Monte Carlo transport codes.Since the void space needs to be described accurately,the void space modeling is more complicated than the solids modeling.For system with complex geometry,the void filling may generate too complicated Monte Carlo description for efficient modeling and calculation.Based on the multi-physics coupling analysis modeling program SuperMC/MCAM,an improved void filling algorithm based on convex solids was developed.This algorithm would test all the convex solids generated by decomposing the CAD solids with sub-spaces and generate the void description by complementary describing convex volumes intersected with the sub-spaces.This algorithm was tested with ITER reference neutronics model.The result shows that this algorithm simplifies the description of the void to 1/60,accelerates the void space modeling by 25 times and speeds up calculation by 1.4times compa-ring to benchmark algorithm.
引文
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