A Comparison of Monte Carlo Particle Transport Algorithms for Binary Stochastic Mixtures

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