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  • title: Continuous Convolutional Neural Networks for Disruption Prediction in Nuclear Fusion Plasmas
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            Continuous Convolutional Neural Networks for Disruption Prediction in Nuclear Fusion Plasmas
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            Continuous Convolutional Neural Networks for Disruption Prediction in Nuclear Fusion Plasmas

            Dez 15, 2023

            Sprecher:innen

            WA

            William Arnold

            Řečník · 0 sledujících

            LS

            Lucas Spangher

            Řečník · 0 sledujících

            CR

            Cristina Rea

            Řečník · 0 sledujících

            Über

            Grid decarbonization for climate change requires dispatchable carbon-free energy like nuclear fusion. The tokamak concept offers a promising path for fusion, but one of the foremost challenges in implementation is the occurrence of energetic plasma disruptions. In this study, we delve into Machine Learning approaches to predict plasma state outcomes. Our contributions are twofold: (1) We present a novel application of Continuous Convolutional Neural Networks for disruption prediction and (2) We…

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            NeurIPS 2023

            Účet · 645 sledujících

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