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- Title
Alternative Detection of n = 1 Modes Slowing Down on ASDEX Upgrade.
- Authors
Peluso, Emmanuele; Rossi, Riccardo; Murari, Andrea; Gaudio, Pasqualino; Gelfusa, Michela
- Abstract
Featured Application: This article describes a physical based criterion to track the slowing down of n = 1 instabilities on the ASDEX upgrade (AUG) Tokamak. It can provide automatically the time instance of the locking of the instability in the frame of reference of the laboratory. Immediate applications are possible both in real time and off-line, for mitigation and avoidance purposes respectively. Disruptions in tokamaks are very often associated with the slowing down of magneto-hydrodynamic (MHD) instabilities and their subsequent locking to the wall. To improve the understanding of the chain of events ending with a disruption, a statistically robust and physically based criterion has been devised to track the slowing down of modes with toroidal mode numbers n = 1 and mostly poloidal mode number m = 2, providing an alternative and earlier detection tool compared to simple threshold based indicators. A database of 370 discharges of axially symmetric divertor experiment—upgrade (AUG) has been studied and results compared with other indicators used in real time. The estimator is based on a weighted average value of the fast Fourier transform of the perturbed radial n = 1 magnetic field, caused by the rotation of the modes. The use of a carrier sinusoidal wave helps alleviating the spurious influence of non-sinusoidal magnetic perturbations induced by other instabilities like Edge localized modes (ELMs). The indicator constitutes a good candidate for further studies including machine learning approaches for mitigation and avoidance since, by deploying it systematically to evaluate the time instance for the expected locking, multi-machine databases can be populated. Furthermore, it can be thought as a contribution to a wider approach to dynamically tracking the chain of events leading to disruptions.
- Subjects
FAST Fourier transforms; FUSION reactor divertors; MAGNETOHYDRODYNAMIC instabilities; FUSION reactors; MACHINE learning; MAGNETIC fields; TIME management
- Publication
Applied Sciences (2076-3417), 2020, Vol 10, Issue 21, p7891
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app10217891