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Parametric study of hydrogenic inventory in the ITER divertor based on machine learning

A parametric study is performed with the 2D FESTIM code for the ITER monoblock geometry. The influence of the monoblock surface temperature, the incident ion energy and particle flux on the monoblock hydrogen inventory is investigated. The simulated data is analysed with a Gaussian regression proces...

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Detalles Bibliográficos
Autores principales:	Delaporte-Mathurin, Rémi, Hodille, Etienne, Mougenot, Jonathan, De Temmerman, Gregory, Charles, Yann, Grisolia, Christian
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2020
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576168/ https://www.ncbi.nlm.nih.gov/pubmed/33082471 http://dx.doi.org/10.1038/s41598-020-74844-w

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