ELM suppressed high performance fusion scenarios achieved with Feedback Adaptive RMP ELM Control
ORAL
Abstract
To eliminate all ELMs, additional capabilities are added, such as ELM suppression-loss precursor detection using Dα-emission. When the detector detects a precursor, an RMP pulse is applied. This mechanism demonstrated its ability to prevent imminent ELMs. As observed, the optimized RMP will change during long pulses because of plasma evolution. Since detailed models are too computationally expensive in real-time, an ML algorithm has been developed that determines the optimized spectrum in real-time. This could allow the controller to adjust significantly during long pulses, in a way where it sustains ELM suppression throughout.
[1] R. Shousha et al., Phys. Plasmas, 29, 032514 (2022).
[2] S. K. Kim et al., Nucl. Fusion, 62, 026043 (2022).
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Publication: [1] R. Shousha et al., Phys. Plasmas, 29, 032514 (2022).<br>[2] S. K. Kim et al., Nucl. Fusion, 62, 026043 (2022).
Presenters
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Ricardo Shousha
Princeton University
Authors
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Ricardo Shousha
Princeton University
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SangKyeun Kim
Princeton University, Princeton University, U.S.A., PPPL, PU
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Keith Erickson
Princeton Plasma Physics Laboratory, PPPL
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Jong-Kyu Park
Princeton Plasma Physics Laboratory, Princeton Plasma Physics Laboratory, U.S.A., PPPL
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SeongMoo Yang
Princeton Plasma Physics Laboratory, Princeton Plasma Physics Laboratory, U.S.A., PPPL
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Minwoo Kim
Korea Institute of Fusion Energy, KFE, Korean Intitute of Fusion Energy
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Giwook Shin
Korea institute of Fusion Energy, Korea Institute of Fusion Energy, KFE
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Sanghee Hahn
Korea Institute of Fusion Energy, Korea institute of Fusion Energy, Korea Institute of Fusion Energy, Korea, KFE
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Gunyoung Park
Korea Institute of Fusion Energy, KFE
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Y.M. Jeon
Korea Institute of Fusion Energy
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Nikolas C Logan
Lawrence Livermore Natl Lab, LLNL
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Egemen Kolemen
Princeton University