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  Neural-network accelerated coupled core-pedestal simulations with self-consistent transport of impurities and compatible with ITER IMAS

Meneghini, O., Snoep, G., Lyons, B. C., McClenaghan, J., Imai, C. S., Grierson, B., et al. (2021). Neural-network accelerated coupled core-pedestal simulations with self-consistent transport of impurities and compatible with ITER IMAS. Nuclear Fusion, 61: 026006. doi:10.1088/1741-4326/abb918.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0007-B67E-F Version Permalink: https://hdl.handle.net/21.11116/0000-0007-B67F-E
Genre: Journal Article

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meneghini_neural-network.pdf (Supplementary material), 3MB
 
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https://doi.org/10.1088/1741-4326/abb918 (Publisher version)
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 Creators:
Meneghini, O.1, Author
Snoep, G.1, Author
Lyons, B. C.1, Author
McClenaghan, J.1, Author
Imai, C. S.1, Author
Grierson, B.1, Author
Smith, S. P.1, Author
Staebler, G. M.1, Author
Snyder, P. B.1, Author
Candy, J.1, Author
Belli, E.1, Author
Lao, L.1, Author
Park, J. M.1, Author
Citrin, J.1, Author
Cordemiglia, T. L.2, Author           
Tema, A.1, Author
Mordijck, S.1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Tokamak Scenario Development (E1), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856321              

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Language(s): eng - English
 Dates: 20202021
 Publication Status: Issued
 Pages: 14 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1088/1741-4326/abb918
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Title: Nuclear Fusion
Source Genre: Journal
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Publ. Info: Bristol; Vienna : IOP Publishing; IAEA
Pages: - Volume / Issue: 61 Sequence Number: 026006 Start / End Page: - Identifier: ISSN: 0029-5515
CoNE: https://pure.mpg.de/cone/journals/resource/991042749627140