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  Evaluation of the Dreicer runaway generation rate in the presence of high-Z impurities using a neural network

Hesslow, L., Unnerfelt, L., Vallhagen, O., Embreus, O., Hoppe, M., Papp, G., et al. (2019). Evaluation of the Dreicer runaway generation rate in the presence of high-Z impurities using a neural network. Journal of Plasma Physics, 85(6): 475850601. doi:10.1017/S0022377819000874.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0005-6DF8-A Version Permalink: https://hdl.handle.net/21.11116/0000-000C-DEA5-0
Genre: Journal Article

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hesslow_evaluation.pdf (Supplementary material), 492KB
 
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https://doi.org/10.1017/S0022377819000874 (Publisher version)
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Open Access
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 Creators:
Hesslow, L.1, Author
Unnerfelt, L.1, Author
Vallhagen, O.1, Author
Embreus, O.1, Author
Hoppe, M.1, Author
Papp, G.2, Author           
Fülöp, T.1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Office of the Director (DI), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856325              

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Language(s): eng - English
 Dates: 20192019
 Publication Status: Published in print
 Pages: 15 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1017/S0022377819000874
 Degree: -

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Project name : Euratom Research and Training Programme 2014-2018 and 2019-2020 – EUROfusion
Grant ID : 633053
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Journal of Plasma Physics
Source Genre: Journal
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Publ. Info: London : Cambridge University Press
Pages: - Volume / Issue: 85 (6) Sequence Number: 475850601 Start / End Page: - Identifier: ISSN: 0022-3778
CoNE: https://pure.mpg.de/cone/journals/resource/954925334694