NEUP DECP-29865: An Optimization and Control Hub for Advanced Reactors: A Step Toward Modernizing Nuclear Engineering Education

This proposal aims to develop a foundational paradigm that provides innovative optimization and control solutions to support DOE-NE synergistic advanced reactor programs. Our hub is based on an established framework enhanced with novel contributions: (1) diverse bio-inspired ensemble optimizer with surrogate modeling for reactor siting & core-reload optimization, (2) hybrid model predictive reinforcement learning controller for microreactors, and (3) modern integrated research and teaching plan.

Additional Info

Field	Value
Awarded Institution	University of Michigan
PI	Majdi Radaideh