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  Turbulence suppression by energetic particles: a sensitivity-driven dimension-adaptive sparse grid framework for discharge optimization

Farcas, I.-G., Di Siena, A., & Jenko, F. (2021). Turbulence suppression by energetic particles: a sensitivity-driven dimension-adaptive sparse grid framework for discharge optimization. Nuclear Fusion, 61: 056004. doi:10.1088/1741-4326/abecc8.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0008-555B-3 Version Permalink: https://hdl.handle.net/21.11116/0000-0008-555C-2
Genre: Journal Article

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farcas_turbulence.pdf (Supplementary material), 2MB
 
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https://doi.org/10.1088/1741-4326/abecc8 (Publisher version)
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 Creators:
Farcas, I.-G.1, Author
Di Siena, A.2, Author           
Jenko, F.1, 2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Tokamak Theory (TOK), Max Planck Institute for Plasma Physics, Max Planck Society, ou_1856309              

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Language(s): eng - English
 Dates: 2021
 Publication Status: Issued
 Pages: 10 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1088/1741-4326/abecc8
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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: 056004 Start / End Page: - Identifier: ISSN: 0029-5515
CoNE: https://pure.mpg.de/cone/journals/resource/991042749627140