University and National Laboratory Collaborate on AI-Based Plasma Models
Artificial intelligence will be used to model extreme plasma behaviors for nuclear fusion and high-energy-density environments.
The University of California, Santa Barbara and the Lawrence Livermore National Laboratory have launched a collaborative effort to integrate artificial intelligence technologies to model extreme plasma behaviors in nuclear fusion and high-energy-density environments.
Project Goal and Collaboration
The new collaboration established between the University of California, Santa Barbara and the Lawrence Livermore National Laboratory incorporates artificial intelligence into the modeling of extreme plasma behaviors, one of the most computationally demanding areas of modern physics.
Funding and Selection Process
As one of five projects selected out of 29 applications by the LLNL Academic Collaboration Team, this study will be supported with $536,000 annually for three years.
AI-Powered Models
Led by Haewon Jeong, the team is working alongside LLNL scientists to build AI-based surrogate models that can significantly reduce the time required for large-scale plasma simulations.
Cost in Physics Simulations
Traditional physics simulations are extremely costly, and AI-based surrogate modeling aims to approximate results at a lower computational cost by eliminating the need to solve partial differential equations.
Thermodynamic Equilibrium States
The project combines expertise in machine learning, plasma physics, and high-performance computing aimed at developing faster and more efficient simulation tools for studying non-local thermodynamic non-equilibrium (non-LTE) plasmas.
Fusion Energy and the Future
Laser fusion is seen as one of the most promising scientific pathways toward providing abundant and clean energy for humanity, and understanding the non-LTE states that affect system performance is of great importance.