Exploring the Power of AI in Controlling Fusion Reactions at Princeton Plasma Physics Laboratory

Wednesday - May 15 2024, 17:33 UTC - 6 months ago

Researchers at the Princeton Plasma Physics Laboratory are using machine learning to improve their control over fusion reactions. The AI system is able to predict and avoid disruptions in the plasma, achieving stable H-mode on two different tokamaks. This breakthrough has significant implications for the future of fusion energy and its potential to provide clean, reliable power.

The pursuit of clean, reliable energy has long been a grand challenge for humanity. With the growing urgency to address climate change and reduce our dependence on fossil fuels, scientists have been exploring various alternative energy sources. Among them, fusion energy stands out for its potential to provide an essentially unlimited source of clean energy.At the leading edge of this pursuit is the U .

S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL). Here, the intricate dance of atoms fusing and releasing energy to create plasma is being studied in great detail. And now, with the power of artificial intelligence (AI), researchers are pushing the boundaries of fusion energy research even further.Unlike traditional computer code, machine learning – a type of AI – isn’t simply a set of instructions .

Instead, it is software that can analyze data, infer relationships between features, learn from this new knowledge, and adapt. PPPL researchers believe that this ability to learn and adapt could greatly enhance their control over fusion reactions.In a recent breakthrough, PPPL researchers published a paper in Nature Communications showcasing how they used machine learning to avoid magnetic perturbations, or disruptions, that can destabilize fusion plasma .

Lead author SangKyeun Kim, a staff research physicist at PPPL, noted that the results were particularly impressive because they were achieved on two different tokamaks – the donut-shaped fusion vessels used to hold plasma – using the same code.According to Egemen Kolemen, associate professor at the department of mechanical and aerospace engineering at Princeton University, who is jointly appointed with the Andlinger Center for Energy and the Environment and PPPL, “There are instabilities in plasma that can lead to severe damage to the fusion device .

We can’t have those in a commercial fusion vessel. Our work advances the field and shows that artificial intelligence could play an important role in managing fusion reactions going forward, avoiding instabilities while allowing the plasma to generate as much fusion energy as possible.”One of the most impressive aspects of the system is its speed in making decisions to control the plasma. Kolemen’s system can make decisions in milliseconds and automatically adjust the settings for the fusion vessel to maintain stability .

This includes predicting disruptions, figuring out the necessary settings changes, and making those changes all before the instabilities occur.The system was successfully deployed on two tokamaks – the DIII-D and KSTAR – both achieving high-confinement mode (H-mode) without disruptions. H-mode refers to when the plasma is heated enough for the confinement of the plasma to improve significantly, and turbulence at the plasma’s edge effectively disappears .

This is the most difficult mode to stabilize, but also the mode that will be necessary for commercial power generation.The results are especially significant because, in both cases, the plasma was in H-mode. Furthermore, this was the first time that researchers were able to achieve an error-free H-mode on both devices using the same code. In the case of DIII-D, the machine learning system performed 1,000 simulations to predict a disruption and developed a control plan in just 40 milliseconds .

The potential impact of AI in fusion energy research cannot be overstated. With further development and optimization of the AI system, researchers could greatly improve the efficiency, stability, and reliability of fusion reactions. This could bring us one step closer to harnessing the same energy source that powers the sun and stars, and revolutionize the way we generate power on Earth. As we move towards a cleaner, greener future, the fusion of AI and fusion energy research at PPPL is a shining example of human ingenuity and innovation at work .