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New ML framework predicts shifts between shots at DIII-D
An artist's sketch and a cross-section view of the DIII-D tokamak. (Images: General Atomics)
At the DIII-D National Fusion Facility near San Diego, Calif., home to the largest operating tokamak in North America, researchers from Thomas Jefferson National Accelerator Facility worked to develop a machine learning framework capable of adaptively predicting changes in a tokamak’s hardware.
The team’s research was recently published in the journal Machine Learning with Applications.
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