MIT team creates model to prevent plasma disruptions in tokamaks

Scientists at MIT have developed a novel method to predict and manage plasma behavior during the rampdown process in tokamak nuclear reactors. Rampdown involves safely reducing the plasma current, which circulates at extremely high speeds and temperatures, to prevent instability that can damage the reactor’s interior. However, the rampdown itself can sometimes destabilize the plasma, causing costly damage. To address this, the MIT team combined physics-based plasma dynamic models with machine learning techniques, training their model on experimental data from the Swiss TCV tokamak. This hybrid approach allowed the model to accurately and quickly predict plasma evolution and potential instabilities during rampdown using relatively small datasets. The new model not only enhances prediction accuracy but also translates these predictions into actionable control instructions, or “trajectories,” that a tokamak’s control system can implement to maintain plasma stability. This capability was successfully tested on multiple TCV experimental runs, demonstrating safer plasma rampdowns and potentially improving the reliability and safety of future nuclear fusion reactors. The research,