1. Pedestal electron collisionality and toroidal rotation during ELM-crash suppression phase under n = 1 RMP in KSTAR
- Author
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J. W. Juhn, G.Y. Park, Jinhyuck Lee, Minwoo Kim, Won-Ha Ko, Jaehyun Lee, Sang-hee Hahn, Young-Mu Jeon, W. Suttrop, S. K. Kim, and Y. In
- Subjects
Physics ,Toroid ,Phase (waves) ,Plasma ,Collisionality ,Condensed Matter Physics ,01 natural sciences ,010305 fluids & plasmas ,Computational physics ,Pedestal ,KSTAR ,0103 physical sciences ,010306 general physics ,Linear combination ,Rotation (mathematics) - Abstract
Excellent reproducibility of KSTAR resonant magnetic perturbation (RMP)-driven, edge-localized mode (ELM)-crash suppression enables us to construct a database reliably for the study of ELM-crash suppression conditions. To establish a high-fidelity database, we have selected one of the frequently used RMP configurations in KSTAR, n = 1, + 90 ° phasing RMP-coil configuration. A series of fitting curves based on edge profile diagnostics data is used for normalized electron collisionality ( ν e *) and plasma toroidal rotation ( V tor) at pedestal top. Since ITER is expected to employ slowly rotating, low-collisionality, high-density plasmas whose conditions are not readily accessible in the existing devices, the exploration and understanding of these two parameters would be important not only for RMP-driven, ELM-crash-suppression physics but also for the success of ITER. The data points for the ELM-crash suppression phase are in the range of 0.2 40 km/s. Suppression thresholds or boundaries in ν e , ped * or V tor , ped are not confirmed in the investigated parameter ranges so far. The KSTAR database still needs additional experimental datasets in ITER-relevant conditions ( ν e , ped * ∼ 0.1 and low-torque low-rotation) to confirm the boundary of the ELM-crash suppression window in KSTAR and reduce the uncertainties of the RMP ELM-crash control technique in ITER. In both ν e , ped * and V tor , ped parameters, the phase-space distribution of the ELM-crash suppression has no clear distinction from that of the ELM-crash mitigation. Linear discriminant analysis provides a linear combination of parameters relevant to ELM-crash suppression, best separating two data categories. Recursive feature elimination indicates that n e , ped and I RMP, as well as ν e , ped * and V tor , ped, are critical variables in the separation of the data groups.
- Published
- 2020
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