Development of a New Monte Carlo Code for High-Fidelity Power Reactor Analysis

Department of Nuclear EngineeringThe high-fidelity multiphysics simulation using transport codes are being mainstream in the reactor physics society. Monte Carlo neutron transport code is one of the most promising candidates of neutronics code of multiphysics simulation since it has advantages of using continuous energy cross section and explicit geometry modeling. Most of the methods required for the Monte Carlo multiphysics simulation has been developed and studied well individually. However, Monte Carlo method have not been able to be applied for large-scale multiphysics simulation such as Pressurized Water Reactor analysis because of the limited computing power, memory storage and especially lack of Monte Carlo codes adapted for large-scale power reactor simulation. Development of Monte Carlo multiphysics code is a challenging due to two aspect: implementing various state of the art techniques into one single code system and making it feasible running simulations on practical computing machines. A new Monte Carlo multiphysics code named MCS was developed for large-scale power reactor analysis. Various state-of-the art techniques were implemented to make it practical tool for multiphysics simulation including thermal hydraulics, depletion, equilibrium xenon, eigenvalue search, on-the-fly cross section generation, hash-indexing, parallel fission bank. The high performance of MCS was achieved and demonstrated. The test result confirmed that the overhead of massive number of tallies is only a one percent up to 13M tally bins, and the parallel efficiency was maintained above 90% up to 1,120 processors when solving power reactor simulation. The fundamental study of power reactor analysis was performed to decide calculation condition including burnup sensitivity, mesh sensitivity, history sensitivity against pressurized water reactor benchmark problem BEAVRS Cycle 1. Finally, capability of power reactor analysis was demonstrated against BEAVRS Cycle 1 and 2.ope

Performance evaluation of CMFD on inter-cycle correlation reduction of Monte Carlo simulation

This paper presents a performance examination of the Coarse Mesh Finite Difference (CMFD) method for a reduction of inter-cycle correlations in Monte Carlo (MC) active cycle simulations. Sensitivity tests using the UNIST in-house MC code 'MCS' reveal the characteristics of CMFD effectiveness depending on problem sizes, dimensions, and cross-section dependency on neutron energy (multi-group vs. continuous). Also, by applying this method to the three-dimensional BEAVRS whole core problem, it is successfully demonstrated that the CMFD can reduce the inter-cycle correlations of practical, large size, and high dominance ratio problems, and that the figure of merit of efficiency for a practical reactor problem increases by a factor of six