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

• DOI: 10.1049/icp.2024.3630
• Publication Date: 2025-01-08T15:43:01Z
• Authors: Qi You; Jing Zhang; Yueguang Chen; Hongxing Lu; Quanyi Lin

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