Virtual lattice method for efficient Monte Carlo transport simulation of dispersion nuclear fuels

Abstract

The randomly dispersed Tristructural-isotropic (TRISO) particle fuel is an attractive nuclear fuel type widely used in advanced reactor designs. However, the massive randomly-distributed fuel elements and the prohibitive computational costs pose challenges for high-fidelity modeling and simulation of dispersion fuels. To address this, we present a virtual lattice optimization method for accelerating the Monte Carlo particle transport simulation of nuclear systems with dispersion fuels. The new method involves using a regular overlaid mesh on the dispersed fuel region to improve geometry processing in Monte Carlo simulations. We describe the optimization methodology in our paper and construct a theoretical performance model to determine the optimal lattice pitch size that minimizes calculation cost. We then develop and implement the algorithm of the virtual method in the open-source Monte Carlo code OpenMC. To demonstrate the efficacy of the new algorithm, high-fidelity HTR-PM full core models based on the Shidao-Bay nuclear power plant are constructed, including an explicit representation of up to 420,000 fuel pebbles. Criticality and depletion simulations are performed on large-scale models. Results show that the k-effective derived by the optimized code agrees well with both the experiment and the original code. Further performance comparison shows that the virtual lattice method exhibits lower time consumption, higher parallel efficiency, and lower storage requirement in comparison to the conventional physical lattice method. The study establishes the effectiveness of the proposed methodology in facilitating efficient and accurate high-fidelity simulations of large-scale dispersion fuel models.