NUCLEAR-FUEL MANAGEMENT OPTIMIZATION USING GENETIC ALGORITHMS

The code independent genetic algorithm reactor optimization (CIGARO) system has been developed to optimize nuclear reactor loading patterns. It uses genetic algorithms (GAs) and a code-independent interface, so any reactor physics code (e.g., CASMO-3/SIMULATE-3) can be used to evaluate the loading patterns. The system is compared to other GA-based loading pattern optimizers. Tests were carried out to maximize the beginning of cycle k(eff) for a pressurized water reactor core loading with a penalty function to limit power peaking. The CIC;ARO system performed well, increasing the k(eff) after lowering the peak power. Tests of a prototype parallel evaluation method showed the potential for a significant speedup.