LAMY, Corisande; DUBROCA, Bruno; NICOLAI, Philippe; TIKHONCHUK, Vladimir; FEUGEAS, Jean-Luc

doi:10.1103/PhysRevE.105.055201

Métadonnées

Afficher la notice complète

Licence d’utilisation du document

LAMY, Corisande

DUBROCA, Bruno

Laboratoire des Composites Thermostructuraux [LCTS]

NICOLAI, Philippe

Langue

Article de revue

Ce document a été publié dans

Physical Review E. 2022-05-06, vol. 105, n° 5

Résumé en anglais

This article presents the use of artificial neural networks (ANN) to predict nonlocal heat flux transport within hydrodynamic simulations. Several cases of laser driven ablation of a plastic target are considered. The database for the ANN training phase is built using the transport module of the hydrodynamic code CHIC. It covers a range of parameters characteristic of laser experiments in the context of high-energy-density physics. Results show that an ANN can efficiently replace a module of nonlocal transport in one- and two-dimensional hydrodynamic simulations, with an error less than 3% in a radius of 0.5μm and an average computation gain of a factor 433 in two dimensions.< Réduire

Métadonnées

Partager cette publication !

Licence d’utilisation du document

Modeling of electron nonlocal transport in plasmas using artificial neural networks

Langue

Ce document a été publié dans

Résumé en anglais

URI

DOI

Unités de recherche