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Neural networks: from image recognition to tokamak plasma tomography

Published online by Cambridge University Press:  17 April 2019

Axel Jardin Open the ORCID record for Axel Jardin [Opens in a new window] ,
Jakub Bielecki Open the ORCID record for Jakub Bielecki [Opens in a new window] ,
Didier Mazon ,
Jan Dankowski Open the ORCID record for Jan Dankowski [Opens in a new window] ,
Krzysztof Król ,
Yves Peysson  and
Marek Scholz Open the ORCID record for Marek Scholz [Opens in a new window]
Axel Jardin*
Affiliation:
Institute of Nuclear Physics Polish Academy of Sciences (IFJ PAN), PL-31-342, Krakow, Poland
Jakub Bielecki
Affiliation:
Institute of Nuclear Physics Polish Academy of Sciences (IFJ PAN), PL-31-342, Krakow, Poland
Didier Mazon
Affiliation:
CEA, IRFM F-13108 Saint Paul-lez-Durance, France
Jan Dankowski
Affiliation:
Institute of Nuclear Physics Polish Academy of Sciences (IFJ PAN), PL-31-342, Krakow, Poland
Krzysztof Król
Affiliation:
Institute of Nuclear Physics Polish Academy of Sciences (IFJ PAN), PL-31-342, Krakow, Poland
Yves Peysson
Affiliation:
CEA, IRFM F-13108 Saint Paul-lez-Durance, France
Marek Scholz
Affiliation:
Institute of Nuclear Physics Polish Academy of Sciences (IFJ PAN), PL-31-342, Krakow, Poland
*
Author for correspondence: Axel Jardin, Institute of Nuclear Physics Polish Academy of Sciences (IFJ PAN), PL-31-342, Krakow, Poland. E-mail: [email protected]
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Abstract

In this paper, the possibility of using neural networks for fast tomographic reconstructions of tokamak plasma soft X-ray (SXR) emissivity is investigated. Indeed, the radiative cooling of heavy impurities like tungsten could be detrimental for the plasma core performances of ITER, thus developing robust and fast SXR diagnostic tools is a crucial issue to monitor the impurities and to mitigate in real-time their central accumulation. As preliminary work, a database of emissivity phantoms with associated synthetic measurements is used to train the neural network to solve the inversion problem. The inversion method, training process, and first tomographic reconstructions are presented with the perspectives about our future work.

Keywords

Neural networkssoft X raystokamaksimpuritiestomography
Type
Research Article
Information
Laser and Particle Beams , Volume 37 , Issue 2 , June 2019 , pp. 171 - 175
Copyright
Copyright © Cambridge University Press 2019 

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