• UT Austin PI: Tan Bui-Thanh
  • Collaborating Institutions: Los Alamos National Lab, University of Florida, and Penn State
  • Funding Source: Department of Energy
  • Award: $3.3M (UT Share $510K)
  • Award Date: 09/01/23 - 08/31/26

The project objective is to bridge the predictive science and engineering application gap in real-time fusion system control. This work develops ML/AI methods to translate computationally expensive predictive science to DNN surrogates that are computationally efficient at deployment as engineering control models.