Machine learning facilitates ‘turbulence tracking’ in fusion reactors
Researchers demonstrated the use of computer-vision models to monitor turbulent structures that appear in plasma created in controlled-nuclear-fusion research. They created a synthetic dataset to train these models to identify and track the structures, which can affect the interactions between the plasma and the walls of the plasma vessel.
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