Chord length sampling correction analysis for dispersion fuel in Monte Carlo simulation

Abstract

Dispersion fuels, knowned for their excellent safety performance, are widely used in advanced reactors, such as high-temperature gas-cooled reactors. Compared with deterministic methods, the Monte Carlo method has more advantages in the geometric modeling of stochastic media. The explicit modeling method has high computational accuracy and high computational cost. The chord length sampling (CLS) method can improve computational efficiency by sampling the chord length during neutron transport using the matrix chord length's probability density function. This study shows that the excluded-volume effect in realistic stochastic media can introduce certain deviations into the CLS. A chord length correction approach is proposed to obtain the chord length correction factor by developing the Particle code based on equivalent transmission probability. Through numerical analysis against reference solutions from explicit modeling in the RMC code, it was demonstrated that CLS with the proposed correction method provides good accuracy for addressing the excluded-volume effect in realistic infinite stochastic media.