Mesh-free semi-quantitative variance underestimation elimination method in Monte Caro algorithm

The inter-cycle correlation of fission source distributions (FSDs) in the Monte Carlo power iteration process results in variance underestimation of tallied physical quantities, especially in large local tallies. This study provides a mesh-free semi-quantitative variance underestimation elimination method to obtain a credible confidence interval for the tallied results. This method comprises two procedures: Estimation and Elimination. The FSD inter-cycle correlation length is estimated in the Estimation procedure using the Sliced Wasserstein distance algorithm. The batch method was then used in the elimination procedure. The FSD inter-cycle correlation length was proved to be the optimum batch length to eliminate the variance underestimation problem. We exemplified this method using the OECD sphere array model and 3D PWR BEAVRS model. The results showed that the average variance underestimation ratios of local tallies declined from 37 to 87