Towards Applications of Deep Learning Techniques to Establish Surrogate Models 
for the Power Exhaust in Tokamaks

Brenzke, M.; Wiesen, S.; Bernert, M.; Coster, D. P.; Toussaint, U. von; EUROfusion MST1 Team; ASDEX Upgrade Team, Max Planck Institute for Plasma Physics, Max Planck Society

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Towards Applications of Deep Learning Techniques to Establish Surrogate Models for the Power Exhaust in Tokamaks

Brenzke, M., Wiesen, S., Bernert, M., Coster, D. P., Toussaint, U. v., EUROfusion MST1 Team, et al. (2019). Towards Applications of Deep Learning Techniques to Establish Surrogate Models for the Power Exhaust in Tokamaks. Poster presented at 46th EPS Conference on Plasma Physics, Milan.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0004-83E2-8 Version Permalink: https://hdl.handle.net/21.11116/0000-0004-83E3-7

Genre: Poster

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Creators:
Brenzke, M.¹, Author
Wiesen, S.¹, Author
Bernert, M.², Author
Coster, D. P.³, Author
Toussaint, U. von⁴, Author
EUROfusion MST1 Team, Author
ASDEX Upgrade Team, Max Planck Institute for Plasma Physics, Max Planck Society, Author

Affiliations:
1External Organizations, ou_persistent22
2Plasma Edge and Wall (E2M), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856327
3Tokamak Theory (TOK), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856309
4Numerical Methods in Plasma Physics (NMPP), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856344

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Language(s): eng - English

Dates: Submitted: 2019

Publication Status: Submitted

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Title: 46th EPS Conference on Plasma Physics

Place of Event: Milan

Start-/End Date: 2019-07-08 - 2019-07-12

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