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Data-Derived Operational Boundaries of RMP ELM Suppression in ASDEX Upgrade and DIII-D

POSTER

Abstract

Linear discriminant analysis (LDA) is performed on datasets of discharges from the ASDEX Upgrade and DIII-D tokamaks, revealing unexpected decision boundaries in elongation (κ) and internal inductance for RMP ELM suppression access. Suppression of ELMs by application of RMP fields has been demonstrated in many tokamaks, however, the access criteria are not fully understood. In this work, LDA enables decision boundaries for determining a discharge’s classification as ELMy or ELM-suppressed to be derived for each device and compared to known experimental threshold conditions. In particular, a clear decision boundary between κ and lower triangularity (δl) is found, which indicates suppression loss at high κ when at elevated δl. This is consistent with observations from ASDEX Upgrade. Furthermore, including discharges with different heating mixes blurs the boundary between ELMy and ELM-suppressed phases, indicating access criteria strongly related to heating power. Finally, consistency of the decision boundaries between devices is also explored. This work provides a further understanding of the parameter space required for ELMs to be suppressed by RMPs and can inform real-time ELM control schemes.

Presenters

  • Priyansh Lunia

    Columbia University

Authors

  • Priyansh Lunia

    Columbia University

  • Nils Leuthold

    Columbia University

  • Carlos A Paz-Soldan

    Columbia University

  • Wolfgang Suttrop

    Max Planck Institute for Plasma Physics

  • Matthias Willensdorfer

    Max Planck Institute for Plasma Physics

  • J. K. Park

    Princeton Plasma Physics Laboratory, Seoul National University

  • Nikolas C Logan

    Columbia University, Lawrence Livermore Natl Lab