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A COMPARISON OF MONTE CARLO PARTICLE TRANSPORT ALGORITHMS FOR BINARY STOCHASTIC MIXTURES

机译:二元随机混合物蒙特卡罗粒子传输算法的比较

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Two Monte Carlo algorithms originally proposed by Zimmerman and Zimmerman and Adams for particle transport through a binary stochastic mixture are numerically compared using a standard set of planar geometry benchmark problems. In addition to previously-published comparisons of the ensemble-averaged probabilities of reflection and transmission, we include comparisons of detailed ensemble-averaged total and material scalar flux distributions. Because not all benchmark scalar flux distribution data used to produce plots in previous publications remains available, we have independently regenerated the benchmark solutions including scalar flux distributions. Both Monte Carlo transport algorithms robustly produce physically-realistic scalar flux distributions for the transport problems examined. The first algorithm reproduces the standard Levermore-Pomraning model results for the probabilities of reflection and transmission. The second algorithm generally produces significantly more accurate probabilities of reflection and transmission and also significantly more accurate total and material scalar flux distributions.
机译:使用标准的平面几何基准问题进行数值比较了Zimmerman和Zimmerman和Zimmerman和Zimmerman和Adams的两个Monte Carlo算法,用于通过二进制随机混合物进行粒子传输。除了先前公布的集合平均反射和传输概率的比较外,我们还包括详细集合平均的总和和材料标量磁通量分布的比较。因为没有用于在以前的出版物中生产图的所有基准标量助焊剂分布数据仍然可用,我们已独立重新再生基准解决方案,包括标量磁通量分布。两个蒙特卡罗传输算法都强大地生产了检查运输问题的物理逼真的标量磁通量。第一算法再现标准的杠杆射线模型结果,了解反射和传输的概率。第二种算法通常产生明显更准确的反射和传输的概率,并且还具有显着的总计和材料标量磁通量分布。

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