Sharpening diffuse interfaces with compressible fluids on unstructured meshes

JOURNAL OF COMPUTATIONAL PHYSICS

卷:340

Article

Chiapolino, Alexandre^1,2  Saurel, Richard^1,2,3  Nkonga, Boniface^4,5 

[1] Aix Marseille Univ, CNRS, Cent Marseille, M2P2, Marseille, France

[2] RS2N, Chemin Gaumin, F-83640 St Zacharie, France

[3] Univ Inst France, Nice, France

[4] Univ Cote Azur, LJAD, F-06108 Nice, France

[5] Univ Cote Azur, INRIA, CNRS, UMR 7351,UNS, F-06108 Nice, France

关键词: Multiphase flows;    Interfaces;    Hyperbolic systems;    Unstructured meshes;    Godunov method;    MUSCL;    Flux limiter;   

DOI  :  10.1016/j.jcp.2017.03.042

来源: Elsevier

【 摘 要 】

Diffuse interface methods with compressible fluids, considered through hyperbolic multiphase flow models, have demonstrated their capability to solve a wide range of complex flow situations in severe conditions (both high and low speeds). These formulations can deal with the presence of shock waves, chemical and physical transformations, such as cavitation and detonation. Compared to existing approaches able to consider compressible materials and interfaces, these methods are conservative with respect to mixture mass, momentum, energy and are entropy preserving. Thanks to these properties they are very robust. However, in many situations, typically in low transient conditions, numerical diffusion at material interfaces is excessive. Several approaches have been developed to lower this weakness. In the present contribution, a specific flux limiter is proposed and inserted into conventional MUSCL type schemes, in the frame of the diffuse interface formulation of Saurel et al. (2009). With this limiter, interfaces are captured with 3 +/- 1 mesh points depending on the test problem, showing significant improvement in interface representation compared to conventional limiters, such as for example Superbee. The method works on both structured and unstructured meshes and its implementation in existing codes is simple. Computational examples showing method capabilities and accuracy are presented. (C) 2017 Elsevier Inc. All rights reserved.

【 授权许可】

Free