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Uniform variance method for accelerated Monte Carlo criticality calculation
Progress in Nuclear Energy ( IF 3.3 ) Pub Date : 2021-06-30 , DOI: 10.1016/j.pnucene.2021.103858
Qingquan Pan , Kan Wang

The problem of the non-uniform distribution of relative errors is encountered during the Monte Carlo criticality calculation, which not only reduces the efficiency and the accuracy of some local tallies, but also affects the stability of the Monte Carlo multi-physics coupling calculation. To solve this problem, the uniform variance method is proposed. In this method, the global information is recorded and updated during the inactive cycles, and the source bias technique and the weight windows technique are combined to achieve the uniform distribution of relative errors. The modified C5G7 benchmark is tested by the uniform variance method, and it is found that the variance is reduced in almost all tallies compared with that of the direct simulation. So the uniform variance method is helpful for the global variance reduction, and can be used for the acceleration of the Monte Carlo criticality calculation.



中文翻译:

用于加速蒙特卡罗临界计算的均匀方差方法

蒙特卡罗临界性计算中遇到相对误差分布不均匀的问题,不仅降低了部分局部计数的效率和精度,而且影响了蒙特卡罗多物理场耦合计算的稳定性。为了解决这个问题,提出了均匀方差法。该方法在非活动周期内记录和更新全局信息,并结合源偏差技术和权窗技术来实现相对误差的均匀分布。修改后的 C5G7 基准测试通过均匀方差法进行测试,发现与直接模拟相比,几乎所有计数中的方差都减少了。所以均匀方差法有助于全局方差的减少,

更新日期:2021-06-30
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