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

  • Authors:

  • Serkan Yilmaz;Kostadin Ivanov;Samuel Levine

  • Affiliations:

  • Penn State University, University Park, PA;Penn State University, University Park, PA;Penn State University, University Park, PA

  • Venue:
  • GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
  • Year:
  • 2005

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Abstract

An efficient and a practical genetic algorithm tool was developed and applied successfully to Burnable Poisons (BPs) 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 configuration 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 and the total amount of the Gd in the core is in the objective function. The main objective is to develop the BP loading pattern to minimize the total Gd in the core together with the with residual binding at End-of-Cycle (EOC) and to keep the maximum peak pin power and Soluble Boron Concentration (SOB) at the Beginning of Cycle (BOC) both less than their limit values during core depletion. The innovation of this study was to search all of the feasible U/Gd fuel assembly designs with variable number of U/Gd pins and concentration of Gd2O3 in the overall decision space. The use of different fitness functions guides the solution towards desired (good solutions) region in the solution space, which accelerates the GA solution. The main objective of this study was to develop a practical and efficient GA tool and to apply this tool for designing BP patterns of a given core loading.