Modeling of electron nonlocal transport in plasmas using artificial neural networks

0561513 - FZÚ 2023 RIV US eng J - Journal Article
Lamy, C. - Dubroca, B. - Nicolai, Ph. - Tikhonchuk, Vladimir - Feugeas, J.-L.
Modeling of electron nonlocal transport in plasmas using artificial neural networks.
Physical Review E. Roč. 105, č. 5 (2022), č. článku 055201. ISSN 2470-0045. E-ISSN 2470-0053
Institutional support: RVO:68378271
Keywords : nonlocal transport * neural networks
OECD category: Fluids and plasma physics (including surface physics)
Impact factor: 2.4, year: 2022
Method of publishing: Limited access
https://doi.org/10.1103/PhysRevE.105.055201

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 0.5 μm and an average computation gain of a factor 433 in two dimensions.
Permanent Link: https://hdl.handle.net/11104/0334103