Accuracy and Performance of 3D MOC for Full-Core PWR Problems
Accuracy and Performance of 3D MOC for Full-Core PWR Problems
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发表时间：
2017
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通讯作者：
S. Shaner;William Boyd;B. Forget
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作者：
S. Shaner;William Boyd;B. Forget
特征线法（MOC）由于其计算格子物理问题的准确性和效率，在反应堆物理中引起了广泛的兴趣。虽然它的大部分用途是在解决二维问题，最近一直有兴趣在扩展MOC到三维，以更准确地计算三维功率分布在轻水堆。虽然该方法是自然可扩展到3D，它提出了显着的计算困难。在这项研究中，我们提出了PWR的OpenMOC的结果，通过使用区域分解，有效的跟踪生成，轴向挤出射线跟踪，CMFD加速，和线性源近似，减轻了三维MOC的计算困难。使用OpenMC分析BEAVRS基准，以从OpenMOC的Monte Carlo模拟生成多群截面。首先对单个组件进行MOC和CMFD参数研究，以确定MOC和CMFD参数。使用最佳参数，以减少计算负担，并保持解决方案的精度，三维MOC结果的BEAVRS基准的全核心模拟。
The Method of Characteristics (MOC) has seen wide interest in reactor physics because of its accuracy and efficiency in computing lattice physics problems. While most of its use has been in solving 2D problems, there has been recent interest in extending MOC to 3D in order to more accurately calculate 3D power distributions in LWRs. While the method is naturally extensible to 3D, it presents significant computational difficulties. In this study we present PWR results from OpenMOC which mitigate the computational difficulties of 3D MOC by using domain decomposition, efficient track generation, axially extruded ray tracing, CMFD acceleration, and a linear source approximation. The BEAVRS benchmark is analyzed using OpenMC to generate multi-group cross-sections from Monte Carlo simulations for OpenMOC. First MOC and CMFD parameter studies are conducted on a single assembly to determine the MOC and CMFD parameters. Using optimal parameters to reduce computational burden and maintain solution accuracy, 3D MOC results are presented for the full core simulation of the BEAVRS benchmark.