An efficient numerical method for solving the Boltzmann equation in multidimensions - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Journal of Computational Physics Year : 2018

An efficient numerical method for solving the Boltzmann equation in multidimensions

Abstract

In this paper we deal with the extension of the Fast Kinetic Scheme (FKS) [J. Comput. Phys., Vol. 255, 2013, pp 680-698] originally constructed for solving the BGK equation, to the more challenging case of the Boltzmann equation. The scheme combines a robust and fast method for treating the transport part based on an innovative Lagrangian technique supplemented with fast spectral schemes to treat the collisional operator by means of an operator splitting approach. This approach along with several implementation features related to the parallelization of the algorithm permits to construct an efficient simulation tool which is numerically tested against exact and reference solutions on classical problems arising in rarefied gas dynamic. We present results up to the 3D×3D case for unsteady flows for the Variable Hard Sphere model which may serve as benchmark for future comparisons between different numerical methods for solving the multidimensional Boltzmann equation. For this reason, we also provide for each problem studied details on the computational cost and memory consumption as well as comparisons with the BGK model or the limit model of compressible Euler equations.
Fichier principal
Vignette du fichier
Boltzmann.pdf (6.45 Mo) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01357112 , version 1 (29-08-2016)

Licence

Identifiers

Cite

Giacomo Dimarco, Raphaël Loubère, Jacek Narski, Thomas Rey. An efficient numerical method for solving the Boltzmann equation in multidimensions. Journal of Computational Physics, 2018, 353, pp.46-81. ⟨10.1016/j.jcp.2017.10.010⟩. ⟨hal-01357112⟩
1048 View
1497 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More