Machine learning facilitates ’turbulence tracking’ in fusion reactors

A team of researchers has demonstrated the use of computer vision models to moni
A team of researchers has demonstrated the use of computer vision models to monitor turbulent structures, known as ’blobs,’ that appear on the edge of the super-hot fuel used in controlled-nuclear-fusion research. The super-hot fuel, or plasma, is held inside a tokamak device (right photo). On the left, a ’blob’ highlighted in yellow is shown in a synthetic image. Credits : Tokamak image courtesy École Polytechnique Fédérale de Lausanne and A. Herzog. Foreground ’blob’ image courtesy of the researchers. Edited by MIT News.
A team of researchers has demonstrated the use of computer vision models to monitor turbulent structures, known as 'blobs,' that appear on the edge of the super-hot fuel used in controlled-nuclear-fusion research. The super-hot fuel, or plasma, is held inside a tokamak device ( right photo ). On the left, a 'blob' highlighted in yellow is shown in a synthetic image. Credits : Tokamak image courtesy École Polytechnique Fédérale de Lausanne and A. Herzog. Foreground 'blob' image courtesy of the researchers. Edited by MIT News. A new approach sheds light on the behavior of turbulent structures that can affect the energy generated during fusion reactions, with implications for reactor design.
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