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Abstract The source biased sampling method reduces the variance and improves the efficiency of Monte Carlo particle transport calculations. This paper gives a multi-region, multi-weight shooting model to simulate the source in transport processes. The density function gives the minimum variance for source biased sampling. The model is solved using a random numerical method to verify the correctness of the function. A particle transportation problem is then simulated to show the significant effect of the variance reduction. This method can be used as a general variance reduction technique in Monte Carlo particle transport analyses to construct the density function for biased source sampling for various particle source parameters, such as the transmission location and direction. It gives the best partition coefficient with the minimum variance in stratified sampling.
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| Keywords
Monte Carlo method
source biasing sampling
variance reduction
optimal bias density function
stratified sampling
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Issue Date: 15 February 2014
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2014,
Vol. 54
),Jianping CHENG,Junli LI
