A low-diffusion self-adaptive flux-vector splitting approach for compressible flows

Abstract : A low-diffusion self-adaptive flux-vector splitting method is presented for the Euler equations. The flux-vector is here split into convective and acoustic parts following the formulation recently proposed by the authors. This procedure is based on the Zha-Bilgen (or previously Baraille et al. for the Euler barotropic system) approach enriched by a dynamic flow-dependent splitting parameter based on the local Mach number. As a consequence, in the present self-adaptive splitting, the convective and acoustic parts decouple in the low-Mach number regime whereas the complete Euler equations are considered for the sonic and highly subsonic regimes. The low diffusive property of the present scheme is obtained by adding anti-diffusion terms to the momentum and the energy components of the pressure flux in the acoustic part of the present splitting. This treatment results from a formal invariance principle preserving the discrete incompressible phase space through the pressure operator. Numerical results for several carefully chosen one- and two-dimensional test problems are finally investigated to demonstrate the accuracy and robustness of the proposed scheme for a wide variety of configurations from subsonic to highly subsonic flows.
Document type :
Preprints, Working Papers, ...
Complete list of metadatas

Cited literature [8 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01945480
Contributor : David Iampietro <>
Submitted on : Tuesday, December 18, 2018 - 4:46:46 PM
Last modification on : Wednesday, July 3, 2019 - 10:48:06 AM
Long-term archiving on : Wednesday, March 20, 2019 - 11:44:05 AM

File

main_fvs.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01945480, version 2

Citation

David Iampietro, Frédéric Daude, Pascal Galon. A low-diffusion self-adaptive flux-vector splitting approach for compressible flows. 2018. ⟨hal-01945480v2⟩

Share

Metrics

Record views

169

Files downloads

227