Integrative two-state optimization for core design of BWR using genetic algorithms

Boiling water reactors (BWRs) represent a large fraction of the world´s installed nuclear power capacity. The core model of a BWR is very complex because it has many fuel assemblies and strong axial heterogeneities such as coolant voiding, partial control rod insertion, and non-uniform fuel assembly design. The core design of BWR is a hard optimization problem with a nonlinear objective function and nonlinear constraints. In this paper, we propose an integrative two-stage optimization method of dynamic stage and static stage based on Genetic Algorithm (GA). This algorithm provides both good convergence performance and global searching ability. Therefore, this optimization system realized the practical application for the real BWR core design. Through calculation in an actual plant, it was confirmed that the optimization could be realized within a reasonable computation time. This two-stage optimization algorithm made the automation of core design tasks possible.