Home / Store / Journals / Electronic Articles / Nuclear Science and Engineering / Volume 148 / Number 3 / Pages 391-402
Thomas E. Booth
Nuclear Science and Engineering / Volume 148 / Number 3 / Pages 391-402
Format:electronic copy (download)
The variance in Monte Carlo particle transport calculations is often dominated by a few particles whose importance increases manyfold on a single transport step. This paper describes a novel variance reduction method that uses a large importance change as a trigger to resample the offending transport step. That is, the method is employed only after (ex post facto) a random walk attempts a transport step that would otherwise introduce a large variance in the calculation.Improvements in two Monte Carlo transport calculations are demonstrated empirically using an ex post facto method. First, the method is shown to reduce the variance in a penetration problem with a cross-section window. Second, the method empirically appears to modify a point detector estimator from an infinite variance estimator to a finite variance estimator.
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