The US Department of Energy (DOE) on 20 August announced a plan to provide up to $21 million to support research in artificial intelligence (AI) and machine learning (ML) for fusion energy.
“These awards will enable fusion researchers to take advantage of recent rapid advances in artificial intelligence and machine learning,” said Dr Chris Fall, Director of DOE’s Office of Science. “AI and ML will help us to accelerate progress in fusion and keep American scientists at the forefront of fusion research.”
The selected awards will seek to improve operational efficiencies at Office of Science fusion facilities by automating data analysis workflows and enabling real-time control algorithms. Researchers are expected to make use of the world-leading supercomputing resources at DOE national laboratories.
The awards were made based on competitive peer review under a DOE Funding Opportunity Announcement. The $21 million in funding is for projects lasting up to three years in duration, with $8 million in Fiscal Year 2020 dollars and outyear funding contingent on congressional appropriations. The effort is part of DOE’s Scientific Discovery through Advanced Computing programme – a joint effort by the Offices of Fusion Energy Sciences (FES) and Advanced Scientific Computing Research within the DOE’s Office of Science.
FES has four strategies:
- Advance the fundamental science of magnetically confined plasmas to develop the predictive capability needed for a sustainable fusion energy source;
- Support the development of the scientific understanding required to design and deploy the materials needed to support a burning plasma environment;
- Pursue scientific opportunities and grand challenges in high energy density plasma science to better understand our universe, and to enhance national security and economic competitiveness;
- Increase the fundamental understanding of basic plasma science, including both burning plasma and low temperature plasma science and engineering, to enhance economic competiveness and to create opportunities for a broader range of science-based applications.
The awards went to 16 different researchers. Their names and projects were published on the FES website.
