Dr. Majdi Radaideh leads the AIMS lab (Artificial Intelligence and Multiphysics Simulations), which focuses on the intersection between reactor design, nuclear multiphysics modeling and simulation, advanced computational methods, and machine learning algorithms to drive advanced reactor research and improve the sustainability of the current nuclear reactor fleet. We develop data-driven and physics-based methods for design optimization, control, and uncertainty quantification for complex nuclear systems and recently started to leverage large language models to assess nuclear power support in social media. AIMS focuses on three broad thrust areas:
1- Multiphysics Reactor Design: We study high-fidelity multiphysics phenomena and safety aspects of light water, advanced, small modular, and microreactors. The topics of interest are: Reactor design, multiphysics coupling, core, and design optimization, nuclear data assessment, spent fuel analysis, accident & safety analysis, and experimental validation.
2- Advanced Computing: We develop and apply advanced computing algorithms for all fields of nuclear engineering. We focus on both algorithms research and real-world applications in the field. The topics of interest are: Physics-informed machine learning, deep learning, uncertainty quantification, surrogate modeling, evolutionary optimization, and Bayesian inversion.
3-Autonomous control: We develop and apply physics-based and data-driven modeling techniques on continuous data streams for control in digital electronics to improve system efficiency and reduce operation and maintenance costs. The topics of interest are: Digital twins, anomaly detection, fault prognostics, reinforcement learning, model predictive control, and component health monitoring.
Artificial Intelligence & Multiphysics Simulations