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A many-reactor power plant with a shared used fuel pool presents significant challenges and a novel opportunity for fuel management optimization. We develop a Python package and interface it with optimization software and core modeling software to automate exploration of the design space for the multireactor multicycle problem. A genetic algorithm is used to search the core reload design space for a two-reactor system, with and without used fuel sharing. With equal computational effort, we find that the fuel-sharing strategy slightly lowers cost.

Core Reload Design Using Genetic Optimization for Cost Savings in a Two-Reactor Power Plant With Used Fuel Sharing