Disruption prediction with artificial intelligence techniques in tokamak plasmas

Vega, J., Murari, A., Dormido Canto, Sebastián, Rattá, G. A., Gelfusa, M. y JET Contributors . (2022) Disruption prediction with artificial intelligence techniques in tokamak plasmas. Nature Physics

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Título Disruption prediction with artificial intelligence techniques in tokamak plasmas
Autor(es) Vega, J.
Murari, A.
Dormido Canto, Sebastián
Rattá, G. A.
Gelfusa, M.
JET Contributors
Materia(s) Informática
Abstract In nuclear fusion reactors, plasmas are heated to very high temperatures of more than 100 million kelvin and, in so-called tokamaks, they are confined by magnetic fields in the shape of a torus. Light nuclei, such as deuterium and tritium, undergo a fusion reaction that releases energy, making fusion a promising option for a sustainable and clean energy source. Tokamak plasmas, however, are prone to disruptions as a result of a sudden collapse of the system terminating the fusion reactions. As disruptions lead to an abrupt loss of confinement, they can cause irreversible damage to present-day fusion devices and are expected to have a more devastating effect in future devices. Disruptions expected in the next-generation tokamak, ITER, for example, could cause electromagnetic forces larger than the weight of an Airbus A380. Furthermore, the thermal loads in such an event could exceed the melting threshold of the most resistant state-of-the-art materials by more than an order of magnitude. To prevent disruptions or at least mitigate their detrimental effects, empirical models obtained with artificial intelligence methods, of which an overview is given here, are commonly employed to predict their occurrence—and ideally give enough time to introduce counteracting measures.
Editor(es) Springer Nature
Fecha 2022-06-06
Formato application/pdf
Identificador bibliuned:557-Sdormido-0061
DOI - identifier s41567-022-01602-2
ISSN - identifier 1745-2481
Nombre de la revista Nature Physics
Número de Volumen 18
Página inicial 741
Página final 750
Publicado en la Revista Nature Physics
Idioma eng
Versión de la publicación acceptedVersion
Tipo de recurso Article
Derechos de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
Tipo de acceso Acceso abierto
Notas adicionales The registered version of this article, first published in Nature Physics, is available online at the publisher's website: Springer Nature https://doi.org/10.1038/s41567-022-01602-2
Notas adicionales La versión registrada de este artículo, publicado por primera vez en Nature Physics, está disponible en línea en el sitio web del editor: Springer Nature https://doi.org/10.1038/s41567-022-01602-2

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Creado: Mon, 29 Jan 2024, 22:59:11 CET