NEUP CINR-23-29324: Active Learning Estimation and Optimization (ALEO) of Irradiation Experimental Design for Efficient Accelerated Fuel Qualification

This collaborative proposal creates novel AI/ML models and algorithms integrated with physical knowledge and expertise to explore more efficient ways to calculate irradiation temperatures and fuel specimen burnups for new fuel sample configurations of MiniFuel experiments proposed for irradiation in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL).

Additional Info

Field	Value
Awarded Institution	University of Texas at San Antonio
PI	Adel Alaeddini