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Fusion Science and Technology Volume 74, 2018 - Issue 1-2: Selected papers from the Second IAEA Technical Meeting on Fusion Data Processing, Validation, and Analysis
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Technical Papers

Full-Pulse Tomographic Reconstruction with Deep Neural Networks

Diogo R. FerreiraEUROfusion Consortium, JET, Culham Science Centre, Abingdon, OX14 3DB, United Kingdom;Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade de Lisboa, 1049-001Lisboa, PortugalCorrespondence[email protected]
ORCID Iconhttp://orcid.org/0000-0001-5818-9406
ORCID Icon,
Pedro J. CarvalhoEUROfusion Consortium, JET, Culham Science Centre, Abingdon, OX14 3DB, United Kingdom;Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade de Lisboa, 1049-001Lisboa, PortugalORCID Iconhttp://orcid.org/0000-0002-8480-0499
ORCID Icon,
Horácio FernandesEUROfusion Consortium, JET, Culham Science Centre, Abingdon, OX14 3DB, United Kingdom;Instituto de Plasmas e Fusão Nuclear, Instituto Superior Técnico, Universidade de Lisboa, 1049-001Lisboa, PortugalORCID Iconhttp://orcid.org/0000-0001-6542-7767
ORCID Icon &
JET ContributorsEUROfusion Consortium, JET, Culham Science Centre, Abingdon, OX14 3DB, United Kingdom
Pages 47-56 | Received 28 Jun 2017, Accepted 25 Sep 2017, Published online: 02 Feb 2018

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Diogo R. Ferreira, Pedro J. Carvalho, Carlo Sozzi, Peter J. Lomas & JET Contributors. (2020) Deep Learning for the Analysis of Disruption Precursors Based on Plasma Tomography. Fusion Science and Technology 76:8, pages 901-911.
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Articles from other publishers (19)

Menghua Yang, Zhengbo Cheng, Shouzhi Wang, Binbin Wang, Yi Tan & Zhe Gao. (2023) Compressive sensing-based tomography for Absolute X-ray UltraViolet (AXUV) diagnostics. Review of Scientific Instruments 94:6.
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Bradley T. Wolfe, Michael J. Falato, Xinhua Zhang, Nga T. T. Nguyen-Fotiadis, J. P. Sauppe, P. M. Kozlowski, P. A. Keiter, R. E. Reinovsky, S. A. Batha & Zhehui Wang. (2023) Machine learning for detection of 3D features using sparse x-ray tomographic reconstruction. Review of Scientific Instruments 94:2.
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William E. Lewis, Patrick F. Knapp, Eric C. Harding & Kristian Beckwith. (2022) Statistical characterization of experimental magnetized liner inertial fusion stagnation images using deep-learning-based fuel–background segmentation. Journal of Plasma Physics 88:5.
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Tianbo Wang, Bingli Li, Jinming Gao, Wulyu Zhong, Hui Li, Zengchen Yang, Jiang Min, Kairui Fang, Guoliang Xiao, Yiren Zhu, Mingkun Han, Jianqiang Xu, Didier Mazon, Geert Verdoolaege, Kai Zhang, Chunfeng Dong, Yipo Zhang & Xiao-Lan Zou. (2022) Monitoring of two-dimensional tungsten concentration profiles on the HL-2A tokamak. Plasma Physics and Controlled Fusion 64:8, pages 084003.
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E. Aymerich, G. Sias, F. Pisano, B. Cannas, S. Carcangiu, C. Sozzi, C. Stuart, P.J. Carvalho, A. Fanni & JET Contributors. (2022) Disruption prediction at JET through deep convolutional neural networks using spatiotemporal information from plasma profiles. Nuclear Fusion 62:6, pages 066005.
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Diogo R FERREIRA, Pedro J CARVALHO, Ivo S CARVALHO, Chris I STUART & Peter J LOMAS. (2022) Investigating the physics of disruptions with real-time tomography at JET. Plasma Science and Technology 24:3, pages 035103.
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Diogo R Ferreira. (2021) Using HPC infrastructures for deep learning applications in fusion research. Plasma Physics and Controlled Fusion 63:8, pages 084006.
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A. Jardin, J. Bielecki, D. Mazon, Y. Peysson, K. Król, D. Dworak & M. Scholz. (2021) Implementing an X-ray tomography method for fusion devices. The European Physical Journal Plus 136:7.
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A. Pavone, J. Svensson, M. Krychowiak, U. Hergenhahn, V. Winters, P. Kornejew, S. Kwak, U. Hoefel, R. Koenig & R. C. Wolf. (2021) Neural network surrogates of Bayesian diagnostic models for fast inference of plasma parameters. Review of Scientific Instruments 92:3.
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Diogo R. Ferreira, Pedro J. Carvalho, Ivo S. Carvalho, Chris Stuart & Peter J. Lomas. (2021) Monitoring the plasma radiation profile with real-time bolometer tomography at JET. Fusion Engineering and Design 164, pages 112179.
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A. Jardin, J. Bielecki, D. Mazon, J. Dankowski, K. Król, Y. Peysson & M. Scholz. (2020) Synthetic X-ray Tomography Diagnostics for Tokamak Plasmas. Journal of Fusion Energy 39:5, pages 240-250.
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A. Piccione, J.W. Berkery, S.A. Sabbagh & Y. Andreopoulos. (2020) Physics-guided machine learning approaches to predict the ideal stability properties of fusion plasmas. Nuclear Fusion 60:4, pages 046033.
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A Pavone, J Svensson, S Kwak, M Brix & R C Wolf. (2020) Neural network approximated Bayesian inference of edge electron density profiles at JET. Plasma Physics and Controlled Fusion 62:4, pages 045019.
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Semin Joung, Jaewook Kim, Sehyun Kwak, J.G. Bak, S.G. Lee, H.S. Han, H.S. Kim, Geunho Lee, Daeho Kwon & Y.-C. Ghim. (2020) Deep neural network Grad–Shafranov solver constrained with measured magnetic signals. Nuclear Fusion 60:1, pages 016034.
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E. Peluso, T. Craciunescu, A. Murari, P. Carvalho & M. Gelfusa. (2019) A comprehensive study of the uncertainties in bolometric tomography on JET using the maximum likelihood method. Review of Scientific Instruments 90:12.
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D.D. Carvalho, D.R. Ferreira, P.J. Carvalho, M. Imrisek, J. Mlynar, H. Fernandes & JET Contributors. (2019) Deep neural networks for plasma tomography with applications to JET and COMPASS. Journal of Instrumentation 14:09, pages C09011-C09011.
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Jan Mlynar, Teddy Craciunescu, Diogo R. Ferreira, Pedro Carvalho, Ondrej Ficker, Ondrej Grover, Martin Imrisek & Jakub Svoboda. (2018) Current Research into Applications of Tomography for Fusion Diagnostics. Journal of Fusion Energy 38:3-4, pages 458-466.
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Naoki KENMOCHI, Masaki NISHIURA, Kaori NAKAMURA & Zensho YOSHIDA. (2019) Tomographic Reconstruction of Imaging Diagnostics with a Generative Adversarial Network. Plasma and Fusion Research 14:0, pages 1202117-1202117.
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Axel Jardin, Jakub Bielecki, Didier Mazon, Jan Dankowski, Krzysztof Król, Yves Peysson & Marek Scholz. (2019) Neural networks: from image recognition to tokamak plasma tomography. Laser and Particle Beams 37:2, pages 171-175.
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