Shield for Fusion (S4F): A Proof-of-Concept Neutronics Genetic Algorithm Optimization of Shielding Cabinets for Nuclear Fusion Applications

Nuclear energy production requires robust shielding solutions to ensure the safety of personnel and equipment across a wide range of reactor technologies. Shield for Fusion (S4F) is a new development in nuclear analysis models, and codes a computational framework for optimizing radiation shielding design in fusion reactor applications using OpenMC neutronics simulations and genetic algorithms (GAs). The framework addresses four-layer shielding cabinets with six commercially viable materials, exploring 10,000 possible configurations through a template-based approach with density correction factors. The genetic algorithm efficiently converges to optimal solutions in approximately 100 simulations by balancing competing objectives: neutron flux attenuation, dose minimization, material cost, and weight. Compared to uniform sampling, the GA demonstrates superior performance by identifying high-performing parameter regions with improved attenuation and reduced cost. The framework includes an inverse design tool for rapid retrieval of configurations matching target performance criteria requested by external users, currently available for selected neutron source spectra. Results demonstrate effective multi-objective optimization for fusion shielding applications, with the open-source code available for adaptation to different simulation setups.