DEVELOPMENT OF A MACHINE LEARNING-ASSISTED CORE SIMULATION FOR BOILING WATER REACTOR OPERATIONS

<p dir="ltr">The research focuses on improving core simulation procedures in Boiling Water Reactors (BWRs) by leveraging machine learning techniques. Aimed at better fuel planning and enhanced safety, a machine learning model has been developed to predict errors in existing low-fidelity, diffusion-based core simulators. The machine learning models have demonstrated the capability to accurately and efficiently predict errors in core eigenvalue and power distribution in BWR Operations. This results in a significant improvement over conventional simulation methods in nuclear reactors without increasing computational complexity.</p>