Erlangen 2018 – wissenschaftliches Programm
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P: Fachverband Plasmaphysik
P 6: Codes and Modelling
P 6.5: Vortrag
Montag, 5. März 2018, 17:30–17:45, KI 1.174
Protection of the First Wall of Wendelstein 7-X with Artificial Neural Networks — •Daniel Böckenhoff1, Marko Blatzheim1,2, Hauke Hölbe1, Roger Labahn2, and Thomas Sunn Pedersen1 — 1Max-Planck-Institut für Plasmaphysik, Wendelsteinstraße 1, 17491 Greifswald — 2Institut fur Mathematik, Universitat Rostock, Ulmenstraße 69, 18057 Rostock
One of the main objectives of the nuclear fusion experiment Wendelstein 7-X is to demonstrate steady state capability of the stellarator confinement concept. To ensure the safety of the first wall and protect the plasma from impurities, heat load pattern control is essential for long term operation.
It is demonstrated that artificial neural networks can be used to accurately and efficiently predict details of the magnetic topology at the plasma edge of Wendelstein 7-X, based on simulated as well as measured heat load patterns onto plasma-facing components observed with infrared cameras. The use of a neural network makes it feasible to analyze and control the plasma exhaust in real-time, an important goal for Wendelstein 7-X, and for magnetic confinement fusion research in general.