Zobrazeno 1 - 10
of 14
pro vyhledávání: '"tokamak scenario optimization"'
Autor:
Federico Felici, Olivier Sauter, S. Van Mulders, M. Marin, K. L. van de Plassche, Jonathan Citrin, A. Ho
Publikováno v:
Nuclear Fusion, 61, 086019
Nuclear Fusion, 61(8):086019. Institute of Physics
Nuclear Fusion, 61(8):086019. Institute of Physics
This work presents a fast and robust method for optimizing the stationary radial distribution of temperature, density and parallel current density in a tokamak plasma and its application to first-principle-based modeling of the ITER hybrid scenario.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d12aca55aa65b646cabdaf2a72ff581
https://www.differ.nl/bibcite/reference/8661
https://www.differ.nl/bibcite/reference/8661
Akademický článek
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Autor:
van de Plassche, K. L., Citrin, J., Bourdelle, C., Camenen, Y., Casson, F. J., Dagnelie, V. I., Felici, F., Ho, A., Van Mulders, S.
Publikováno v:
Physics of Plasmas; Feb2020, Vol. 27 Issue 2, p1-17, 17p, 3 Diagrams, 13 Charts, 8 Graphs
Autor:
van de Plassche, Karel Lucas, Citrin, Jonathan, Bourdelle, Clarisse, Camenen, Yann, Casson, Francis J., Dagnelie, Victor I., Felici, Federico, Ho, Aaron, Van Mulders, Simon, Contributors, JET
We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model Q
Externí odkaz:
http://arxiv.org/abs/1911.05617
Publikováno v:
Physics of Plasmas; Jun2023, Vol. 30 Issue 6, p1-17, 17p
Autor:
T. Rafiq, C. Wilson, C. Clauser, E. Schuster, J. Weiland, J. Anderson, S.M. Kaye, A. Pankin, B.P. LeBlanc, R.E. Bell
Publikováno v:
Nuclear Fusion, Vol 64, Iss 7, p 076024 (2024)
The objective of this study is twofold: firstly, to demonstrate the consistency between the anomalous transport results produced by updated Multi-Mode Model (MMM) version 9.0.4 and those obtained through gyrokinetic simulations; and secondly, to show
Externí odkaz:
https://doaj.org/article/9eb078cb49884c7d961613dd2a3cb61e
Autor:
F. J. Casson, Victor I. Dagnelie, Jet Contributors, Federico Felici, Yann Camenen, Clarisse Bourdelle, Simon Van Mulders, A. Ho, Jonathan Citrin, Karel Lucas van de Plassche
Publikováno v:
Physics of Plasmas
Physics of Plasmas, 2020
Physics of Plasmas, 27(2):022310. American Institute of Physics
Physics of Plasmas, 27, 022310
Physics of Plasmas, American Institute of Physics, 2020
HAL
Physics of Plasmas, 2020
Physics of Plasmas, 27(2):022310. American Institute of Physics
Physics of Plasmas, 27, 022310
Physics of Plasmas, American Institute of Physics, 2020
HAL
We present an ultrafast neural network (NN) model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 300 million flux calculations of the quasilinear gyrokinetic transport model Q
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d2147ed520eb2a6b5e2929ab39bdaff
https://doi.org/10.1063/1.5134126
https://doi.org/10.1063/1.5134126
We present an ultrafast neural network model, QLKNN, which predicts core tokamak transport heat and particle fluxes. QLKNN is a surrogate model based on a database of 3 × 108 flux calculations of the quasilinear gyrokinetic transport model, QuaLiKiz
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dris___00893::b4a9fb29cc14b35ac2a4c1f3f7e994fd
Autor:
F. Felici, J. Citrin, A.a. Teplukhina, J. Redondo, C. Bourdelle, F. Imbeaux, O. Sauter, Contributors, Jet, Team, The Eurofusion Mst1
Publikováno v:
Nuclear Fusion; Sep2018, Vol. 58 Issue 9, p1-1, 1p
Autor:
Plassche, K.L. Van De, Citrin, J., C. Bourdelle, Camenen, Y., Casson, F.J., V.I. Dagnelie, F. Felici, Ho, A., Mulders, S. Van
This repository contains the source code of the publication "Fast modeling of turbulent transport in fusion plasmas using neural networks" by K.L. van de Plassche et al., submitted to Physics of Plasmas. Currently contains only the pre-print version.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::984baab262cd9fa9572ec5cea20c4884