English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
  Local TagsRelease HistoryDetailsSummary

Released
Poster

Heat Load Control for Wendelstein 7-X with Machine Learning Approaches

MPS-Authors
/persons/resource/persons203650

Böckenhoff,  D.
Stellarator Edge and Divertor Physics (E4), Max Planck Institute for Plasma Physics, Max Planck Society;

/persons/resource/persons203652

Blatzheim,  M.
Stellarator Edge and Divertor Physics (E4), Max Planck Institute for Plasma Physics, Max Planck Society;

/persons/resource/persons110123

Pedersen,  T. S.
Stellarator Edge and Divertor Physics (E4), Max Planck Institute for Plasma Physics, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Böckenhoff, D., Blatzheim, M., Labahn, R., Pedersen, T. S., & for the Wendelstein 7-X Team Collaboration (2019). Heat Load Control for Wendelstein 7-X with Machine Learning Approaches. Poster presented at DPG-Frühjahrstagung 2019 der Sektion Materie und Kosmos (SMuK), München.


Cite as: https://hdl.handle.net/21.11116/0000-0003-1EFD-0
Abstract
There is no abstract available