Host: The Japan Society of Mechanical Engineers
Name : The 30th International Conference on Nuclear Engineering (ICONE30)
Date : May 21, 2023 - May 26, 2023
The Method of Characteristics (MOC) has been widely used for high-fidelity reactor physics analysis, due to its numerical accuracy and geometrical flexibility. At the same time, the MOC method has a high demand for computing resources. The selection of Flat Source Region (FSR) discretization and track generation parameters will have a great impact on MOC calculation time and accuracy. Therefore, appropriate parameter selection and optimization are necessary. This work applies a multi-objective genetic algorithm to optimize the parameters of OpenMOC for the calculation of the 2D C5G7 benchmark problem, aiming at reducing the error of keff and power distribution and the calculation time. After optimization, the parameters solution with the highest calculation efficiency can be selected in the Pareto-optimal set according to the required calculation accuracy in the practical engineering application. The results of this work demonstrate that genetic algorithms can effectively optimize the selection of MOC parameters. When using OpenMOC to solve the 2D C5G7 benchmark problem, the optimized parameters can improve the solving speed by up to several tens of times compared to the default parameters while achieving the same accuracy. At the same time, these optimized MOC parameters also show applicability in 2D NuScale simulation.
