Nuclear Technology · 1995 · 54 citations · 0 references
EngineeringComputational EngineeringNuclear EngineeringDesign OptimizationOptimizationReactor PhysicsEvolutionary ComputationEvolutionary OptimizationGenetic AlgorithmsReactor Core DesignReactor DesignReactor ModelingCore Design OptimizationCore Loading Pattern OptimizationNuclear Reactor DesignPressurized Water ReactorsPrototype EvaluationReactor Core PhysicsReactor OptimizationReactor Performance Optimization
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{sub eff} for a pressurized water reactor core loading with a penalty function to limit power peaking. The CIGARO system performed well, increasing the k{sub eff} after lowering the peak power. Tests of a prototype parallel evaluation method showed the potential for a significant speedup.