Abstract
Common objectives of high-performance research reactors include neutron scattering, materials irradiation, and isotope production. The design of a core that optimizes these multiple objectives often presents a multidimensional (i.e., in design space), multiobjective optimization problem. The developed systematic approach discussed herein draws on response surface methodology to validate and leverage a surrogate model to serve in place of high-fidelity computational analyses. Optimization and design analysis methods leverage this surrogate model to provide a flexible tool for generating optimized designs and understanding the impact of design decisions on desired metrics. In applications to High Flux Isotope Reactor (HFIR) low-enriched uranium (LEU) core designs, neutronic, isotopic evolution, and thermal hydraulic analyses are used to generate key performance and safety metrics for assessing the feasibility and fitness of given designs. Three optimized designs that consider different desired metrics and constraints (e.g., key metric weighting and fabrication constraints) are presented, providing potential design options that satisfy the requirements for HFIR’s conversion from high enriched uranium to LEU fuel.
