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 CIGARO 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.