AI-driven optimization in nuclear reactor core operations: advances in prediction, management, and fault diagnosis for enhanced safety

The application of Artificial Intelligence (AI) in nuclear reactor core management offers significant enhancements in efficiency, safety, and performance. AI-driven methods, including Artificial Neural Networks (ANNs), Genetic Algorithms (GA), and Particle Swarm Optimization (PSO), optimize fuel loading patterns, power distribution, and core parameters, addressing complex optimization challenges. This paper reviews advancements in AI applications within reactor core management, highlighting successes in automating and refining processes traditionally dependent on manual calculations. Implementations of AI optimize fuel reload patterns, enhance safety margins, and more effectively manage the nuclear fuel lifecycle, thereby contributing to operational efficiency and sustainability. Future directions for AI integration focus on predictive maintenance, advanced modeling, and next-generation reactor design optimization.