Title :

Hybrid Kinetic/Fluid numerical method for the Vlasov-BGK equation in the diffusive scaling

Author(s) :

Laidin, Tino [Auteur]
Reliable numerical approximations of dissipative systems [RAPSODI]
Laboratoire Paul Painlevé - UMR 8524 [LPP]

Journal title :

Kinetic and Related Models

Pages :

913-947

Publisher :

AIMS

Publication date :

2023

ISSN :

1937-5093

English keyword(s) :

Kinetic equations
Diffusion scaling
Asymptotic preserving scheme
Micro-macro decomposition
Hybrid solver

HAL domain(s) :

Mathématiques [math]/Analyse numérique [math.NA]

English abstract : [en]

This work presents a hybrid numerical method for linear collisional kinetic equations with diffusive scaling. The aim of the method is to reduce the computational cost of kinetic equations by taking advantage of the lower ...
Show more >This work presents a hybrid numerical method for linear collisional kinetic equations with diffusive scaling. The aim of the method is to reduce the computational cost of kinetic equations by taking advantage of the lower dimensionality of the asymptotic fluid model while reducing the error induced by the latter approach. It relies on two criteria motivated by a perturbative approach to obtain a dynamic domain adaptation. The first criterion quantifies distance between a local equilibrium in velocity and the distribution function of particles. The second one depends only on the macroscopic quantities that are available on the whole computing domain. A key idea is the use of a micro-macro decomposition to deal with interface conditions. The method is significantly more efficient than a standard full kinetic approach. Some properties, such as the conservation of mass, are also investigated and illustrated through various examples.Show less >

Language :

Anglais

Popular science :

Non

ANR Project :

Modèles multi-échelles et simulation numérique hybride de semi-conducteurs
Centre Européen pour les Mathématiques, la Physique et leurs Interactions

Comment :

31 pages, 20 figures, 6 Tables

Collections :

• Laboratoire Paul Painlevé - UMR 8524

Source :

Harvested from HAL