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- W3104055917 abstract "This paper presents mathematical formulations and methods to predict the effect of forced-flight variance reduction on Monte Carlo tally variance and calculation time. This includes deducing biasing operators that are then used to construct a history-score probability density function (HSPDF), which represents all possible Monte Carlo random walks and gives the probability of a Monte Carlo history scoring in a tally from a particular phase-space position. The history-score moment equations (HSMEs), the statistical moments of the HSPDF, are then derived to calculate the statistical behavior of the Monte Carlo tally when forced-flight variance reduction is applied. In addition, the future-time equation (FTE) is derived to predict the Monte Carlo computational time as a result of applying forced-flight variance reduction. The solutions of the HSMEs and FTE can be used to predict Monte Carlo computational cost. This work also describes a discrete ordinates method to solve the forced-flight HSMEs and FTE. Several 1-D and 2-D test problems verify that the derivations are performed and implemented correctly." @default.
- W3104055917 created "2020-11-23" @default.
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- W3104055917 date "2021-03-01" @default.
- W3104055917 modified "2023-10-16" @default.
- W3104055917 title "Discrete ordinates analysis of the forced-flight variance reduction technique in Monte Carlo neutral particle transport simulations" @default.
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- W3104055917 doi "https://doi.org/10.1016/j.jcp.2020.109997" @default.
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