Application of genetic algorithms to optimize burnable poison placement in pressurized water reactors

An efficient and a practical genetic algorithm (GA) tool was developed and applied successfully to Burnable Poison (BP) placement optimization problem in the reference Three Mile Island-1 (TMI-1) core. Core BP optimization problem means developing a BP loading map for a given core loading pattern that minimizes the total Gadolinium (Gd) amount in the core without violating any design constraints. The number of UO2/Gd2O3 pins and Gd2O3 concentrations for each fresh fuel location in the core are the decision variables. The objective function was to minimize the total amount of Gd in the core together with the residual Gd reactivity binding at the End-of-Cycle (EOC). The constraints are to keep the maximum peak pin power during the core depletion and soluble boron (SOB) concentration at the Beginning of Cycle (BOC) both less than their limit values. The innovation of this study was to search all of the possible UO2/Gd2O3 fuel assembly designs with variable number of UO2/Gd2O3 fuel pins and concentration of Gd2O3 in the overall decision space. The use of different fitness functions guided the solution towards desired (good solutions) region in the solution space, which accelerated the GA solution. The main objective of this study was to develop a practical and efficient GA tool and to apply this tool to designing an optimum BP pattern for a given core loading.