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首页> 外文期刊>Annals of nuclear energy >Optimization treatment of point-wise nuclear data in Monte Carlo criticality and burnup calculations
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Optimization treatment of point-wise nuclear data in Monte Carlo criticality and burnup calculations

机译：蒙特卡洛临界度和燃耗计算中的点状核数据的优化处理

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摘要

The Monte Carlo codes used for neutron transport calculations are always time consuming, a large proportion of which is possessed by the treatment of continuous-energy cross sections. In this paper, two companion methods are developed for the optimization treatment of point-wise nuclear data, the first of which is called Computational-Expense Oriented (CEO) method based on the unionized energy grid approach and reconstructs only the computationally expensive cross sections in neutron transport simulation, and the other of which is called energy bin (EB) method, a companion of CEO method when the reaction rate tallies for MC-coupling burnup calculation are performed. These two methods are implemented in the code RMC, a Monte Carlo (MC) code used for reactor analysis, and tested on fast reactor core and BWR assembly problems. The numerical results show that CEO method, in comparison with reconstructing all cross sections under the unionized grid, requires the sharply decreased computer memory while achieving almost the same computational efficiency, and EB method can optimize the processing of nuclide-specific energy grid search and thus effectively reduce the total search number while reauirine verv small comDuter memorv.
机译：用于中子输运计算的蒙特卡洛法则总是很耗时，其中很大一部分是连续能截面的处理。本文针对点状核数据的优化开发了两种伴随方法，第一种方法是基于联合能量网格方法的面向计算费用的导向（CEO）方法，仅重建了计算量大的截面。中子输运模拟，另一种称为能量箱（EB）方法，是执行MC耦合燃耗计算的反应速率计算时的CEO方法的一种辅助方法。这两种方法在代码RMC（用于反应堆分析的蒙特卡罗（MC）代码）中实现，并在快速反应堆堆芯和BWR组装问题上进行了测试。数值结果表明，与重建联合网格下的所有横截面相比，CEO方法需要大幅减少计算机内存，同时实现几乎相同的计算效率，而EB方法可以优化对特定核素的能量网格搜索的处理，因此有效地减少了总搜索数量，同时减少了计算机消耗。

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