LEMONT, Ill.–(BUSINESS WIRE)–If you could build a star on Earth and harness its energy, you’d need to know exactly how to store it and keep it stable. Fusion energy scientists have been working for decades to make this a reality. They now have a potent new tool at their disposal: the Aurora supercomputer at the U.S. Department of Energy’s (DOE) Argonne National Laboratory.
Housed at the Argonne Leadership Computing Facility (ALCF), Aurora is among the three fastest computers in the world, capable of performing a quintillion calculations per second. That exascale power makes it a critical tool in solving grand scientific challenges, including fusion energy. The ALCF is a DOE Office of Science user facility.
Fusion, in theory, would solve a lot of problems related to our growing need for energy. One of its main inputs, deuterium, can be derived from water. The fusion reaction is straightforward to extinguish, making it a safe prospect as a long-term energy source. Indeed, the reaction’s fragility is fusion energy’s primary hurdle — commercially viable power plants need a reliable, tunable resource. To get there, scientists are using Aurora to simulate conditions inside tokamaks, doughnut-shaped machines where fusion occurs.
To achieve fusion energy requires creating an environment where two atomic nuclei join together and form one heavier nucleus, releasing energy in the process.
Magnetic fields within tokamaks form a sort of “bottle” that confines the plasma. Understanding the tokamak’s inner workings requires simulating plasma flow and energy — a computationally intensive task. “Even just regular fluids are a very complicated scientific problem. When they become turbulent, it’s very chaotic,” said Argonne assistant computational scientist Kyle Felker. “In tokamaks, we’re complicating this by adding magnetic fields and extreme conditions that don’t occur anywhere on Earth.”
Aurora also enables AI-driven research. Felker works with Princeton Plasma Physics Laboratory (PPPL) scientist William Tang on a project that uses AI to predict disruptions in tokamak plasma. Trained on data from experimental machines like DIII-D and the Joint European Torus, the AI can assign a “disruption score” within milliseconds.
“We have lots and lots of data from historical campaigns. So we can take AI to learn what we can about these instabilities and hopefully avoid them entirely,” Felker said.
PPPL researcher Choongseok Chang focuses on edge-plasma physics — what happens when plasma meets its magnetic boundary. Simulating tungsten particles breaking off from tokamak walls or analyzing divertor plate risks, which remove exhaust heat from the system, helps anticipate and prevent confinement issues. Aurora makes these complex, multi-trillion particle calculations feasible, completing in hours what previously took days.
“These machines are powerful tools, but they also tell you what you don’t know,” Tang said. With exascale computing, AI, and skilled researchers, scientists are closer than ever to understanding and controlling fusion, bringing practical fusion energy within reach.
Contacts
Christopher J. Kramer
Head of External Communications
Argonne National Laboratory
Office: 630.252.5580
Email: [email protected]
