Machine learning-accelerated predictions of power and particle exhaust in a fusion pilot plant

January 17, 2023

This project will utilize LLNL expertise in the development of machine learning-based surrogate models for predicting plasma detachment in a fusion pilot plant (FPP) under conceptual design at General Atomics. Built upon a latent space representation, the surrogate models will be used to identify promising regimes for handling the extreme heat and particle loads that will occur in the FPP. The results will be used to guide higher fidelity physics and engineering design activities.

General Atomics

DUNS / SAM UEI: 067638957

Dr. Jonathan Yu, [email protected]

Lawrence Livermore National Laboratory (LLNL)

Ben Zhu, Ben Zhu