Geodesic
Parallelization for unstructured adaptive mesh CFD algorithm
Matematičeskoe modelirovanie, Tome 33 (2021) no. 6, pp. 31-44.

Voir la notice de l'article provenant de la source Math-Net.Ru

A parallel CFD-algorithm on adaptive mixed meshes with elements of the tetrahedron, prism, pyramid, and hexahedron type is presented. The algorithm is based on a explicit high-order accurate finite-volume method for Navier-Stokes equations with polynomial reconstruction of variables. The distributed algorithm for heterogeneous supercomputers is developed using the MPI, OpenMP and CUDA software models. Numerical results for supersonic flows and the parameters of the software efficiency are given.
Keywords: computational fluid dynamics, unstructured mixed mesh, adaptive mesh refinement, parallel computing. 
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S. A. Soukov. Parallelization for unstructured adaptive mesh CFD algorithm. Matematičeskoe modelirovanie, Tome 33 (2021) no. 6, pp. 31-44. http://geodesic.mathdoc.fr/item/MM_2021_33_6_a2/

[1] A. L. Afendikov, Y. V. Khankhasaeva, A. E. Lutsky et al, “Numerical Simulation of the Recirculation Flow during the Supersonic Separation of Moving Bodies”, Math. Models Comp. Simul., 2020, no. 12, 282–292 | DOI

[2] A. L. Afendikov, A. A. Davydov, A. E. Lutskii, I. S. Menshov, K. D. Merkulov, A. V. Plenkin, Ya. V. Khankhasaeva, Adaptivnye veivletnye algoritmy dlya resheniya zadach gidro- i gazovoi dinamiki na dekartovykh setkakh, IPM im. M.V. Keldysha, M., 2016, 232 pp.

[3] https://www.ansys.com/products/fluids/ansys-fluent

[4] O. Antepara, O. Lehmkuhl, J. Chiva, R. Borrell, “Parallel adaptive mesh refinement simula-tion of the flow around a square cylinder at Re=22000”, Proc. Eng., 61 (2013), 246–250 | DOI

[5] A. Schwing, I. Nompelis, G. Candler, “Parallelization of unsteady adaptive mesh refinement for unstructured Navier-Stokes solvers”, AIAA AVIATION 2014 — 7th AIAA Theor. Fluid Mechanics Conf., American Institute of Aeronautics and Astronautics Inc., 2014 | DOI

[6] J. Blazek, Computational fluid dynamics: Principles and applications, Elsevier, Amsterdam, 2001 | MR | Zbl

[7] K. Powell, P. Roe, J. Quirk, “Adaptive-Mesh Algorithms for Computational Fluid Dynamics”, Algorithmic Trends in Computational Fluid Dynamics, ICASE/NASA LaRC Series, eds. Hussaini M.Y., Kumar A., Salas M.D., Springer, N.Y., 1993 | MR

[8] E. Sozer, C. Brehm, C. C. Kiris, Gradient calculation methods on arbitrary polyhedral unstructured meshes for cell-centered CFD solvers, AIAA Paper 2014-1440, 2014

[9] T. J. Barth, Numerical Aspects of Computing High-Reynolds Number Flows on Unstructured Meshes, AIAA Paper 91-0721, 1991

[10] S. Kim, D. Caraeni, B. Makarov, AIAA 16th Computational Fluid Dynamics Conf., Technical report (Orlando, Florida American Institute of Aeronautics and Astronautics, June 2003)

[11] E. F. Toro, Riemann solvers and numerical methods for fluid dynamics, Springer-Verlag, Berlin-Heidelberg, 2009 | DOI | MR | Zbl

[12] Y. Wada, M. S. Liou, A flux splitting scheme with high resolution and robustness for discontinuities, AIAA Paper 94-0083

[13] T. Nagata, T. Nonomura, S. Takahashi, Y. Mizuno, K. Fukuda, “Investigation on subsonic to supersonic flow around a sphere at low Reynolds number of between 50 and 300 by direct numerical simulation”, Physics of Fluids, 28 (2016), 056101 | DOI | MR

[14] A. S. Kryuchkova, “Numerical simulation of a hypersonic flow over HB-2 model using UST3D programming code”, J. Phys.: Conf. Ser., 1250 (2019), 012010 | DOI

[15] https://www.kiam.ru/MVS/resourses/k100.html

[16] S. A. Sukov, A. V. Gorobets, P. B. Bogdanov, “Portable Solution for Modeling Compressible Flows on All Existing Hybrid Supercomputers”, Math. Models Comp. Simul., 10:2 (2018), 135–144 | DOI | MR

[17] A. Gorobets, S. Soukov, P. Bogdanov, “Multilevel parallelization for simulating turbulent flows on most kinds of hybrid supercomputers”, Computers and Fluids, 173 (2018), 171–177 | DOI | MR | Zbl