Journal of Scientific Computing

, Volume 72, Issue 2, pp 623–646 | Cite as

A Numerical Scheme for the Compressible Low-Mach Number Regime of Ideal Fluid Dynamics

  • Wasilij Barsukow
  • Philipp V. F. Edelmann
  • Christian Klingenberg
  • Fabian Miczek
  • Friedrich K. Röpke
Article
  • 287 Downloads

Abstract

Based on the Roe solver a new technique that allows to correctly represent low Mach number flows with a discretization of the compressible Euler equations was proposed in Miczek et al. (Astron Astrophys 576:A50, 2015). We analyze properties of this scheme and demonstrate that its limit yields a discretization of the continuous limit system. Furthermore we perform a linear stability analysis for the case of explicit time integration and study the performance of the scheme under implicit time integration via the evolution of its condition number. A numerical implementation demonstrates the capabilities of the scheme on the example of the Gresho vortex which can be accurately followed down to Mach numbers of \({\sim }10^{-10}\).

Keywords

Compressible Euler equations Low Mach number Asymptotic preserving Flux preconditioning 

Mathematics Subject Classification

65M08 76N15 35B40 35Q31 

Notes

Acknowledgements

We thank Philipp Birken for stimulating discussions. WB gratefully acknowledges support from the German National Academic Foundation. The work of FKR and PVFE was supported by the Klaus Tschira Foundation. CK acknowledges support of the DFG priority program SPPEXA. The authors gratefully acknowledge the Gauss Centre for Supercomputing (GCS) for providing computing time through the John von Neumann Institute for Computing (NIC) on the GCS share of the supercomputer JUQUEEN [29] at Jülich Supercomputing Centre (JSC). GCS is the alliance of the three national supercomputing centres HLRS (Universität Stuttgart), JSC (Forschungszentrum Jülich), and LRZ (Bayerische Akademie der Wissenschaften), funded by the German Federal Ministry of Education and Research (BMBF) and the German State Ministries for Research of Baden-Württemberg (MWK), Bayern (StMWFK) and Nordrhein-Westfalen (MIWF).

References

  1. 1.
    Asano, K.: On the incompressible limit of the compressible euler equation. Jpn. J. Appl. Math. 4(3), 455–488 (1987)MathSciNetCrossRefMATHGoogle Scholar
  2. 2.
    Chalons, C., Girardin, M., Kokh, S.: An all-regime Lagrange-Projection like scheme for the gas dynamics equations on unstructured meshes. Commun. Comput. Phys. 20, 188–233 (2016). doi: 10.4208/cicp.260614.061115a MathSciNetCrossRefGoogle Scholar
  3. 3.
    Cordier, F., Degond, P., Kumbaro, A.: An asymptotic-preserving all-speed scheme for the Euler and Navier–Stokes equations. J. Comput. Phys. 231, 5685–5704 (2012). doi: 10.1016/j.jcp.2012.04.025 MathSciNetCrossRefMATHGoogle Scholar
  4. 4.
    Degond, P., Tang, M.: All speed method for the Euler equation in the low mach number limit. Commun. Comput. Phys. 10, 1–31 (2011)MathSciNetCrossRefMATHGoogle Scholar
  5. 5.
    Dellacherie, S.: Checkerboard modes and wave equation. In: Proceedings of ALGORITMY , vol. 2009, pp. 71–80. (2009)Google Scholar
  6. 6.
    Dellacherie, S.: Analysis of Godunov type schemes applied to the compressible Euler system at low mach number. J. Comput. Phys. 229(4), 978–1016 (2010). doi: 10.1016/j.jcp.2009.09.044 MathSciNetCrossRefMATHGoogle Scholar
  7. 7.
    Drikakis, D., Fureby, C., Grinstein, F.F., Youngs, D.: Simulation of transition and turbulence decay in the Taylor–Green vortex. J. Turbul. 8, N20 (2007). doi: 10.1080/14685240701250289 CrossRefMATHGoogle Scholar
  8. 8.
    Ebin, D.G.: The motion of slightly compressible fluids viewed as a motion with strong constraining force. Ann. Math. 105(1), 141–200 (1977)MathSciNetCrossRefMATHGoogle Scholar
  9. 9.
    Eswaran, V., Pope, S.B.: An examination of forcing in direct numerical simulations of turbulence. Comput. Fluids 16, 257–278 (1988)CrossRefMATHGoogle Scholar
  10. 10.
    Gresho, P.M., Chan, S.T.: On the theory of semi-implicit projection methods for viscous incompressible flow and its implementation via a finite element method that also introduces a nearly consistent mass matrix. Part 2: implementation. Int. J. Numer. Methods Fluids 11(5), 621–659 (1990). doi: 10.1002/fld.1650110510 CrossRefMATHGoogle Scholar
  11. 11.
    Guillard, H., Murrone, A.: On the behavior of upwind schemes in the low mach number limit: II Godunov type schemes. Comput. Fluids 33, 655–675 (2004)CrossRefMATHGoogle Scholar
  12. 12.
    Guillard, H., Viozat, C.: On the behaviour of upwind schemes in the low mach number limit. Comput. Fluids 28(1), 63–86 (1999). doi: 10.1016/S0045-7930(98)00017-6 MathSciNetCrossRefMATHGoogle Scholar
  13. 13.
    Haack, J., Jin, S., Liu, J.G.: An all-speed asymptotic-preserving method for the isentropic Euler and Navier–Stokes equations. Commun. Comput. Phys. 12, 955–980 (2012). doi: 10.4208/cicp.250910.131011a MathSciNetCrossRefGoogle Scholar
  14. 14.
    Hammer, N., Jamitzky, F., Satzger, H., Allalen, M., Block, A., Karmakar, A., Brehm, M., Bader, R., Iapichino, L., Ragagnin, A., Karakasis, V., Kranzlmüller, D., Bode, A., Huber, H., Kühn, M., Machado, R., Grünewald, D., Edelmann, P.V.F., Röpke, F.K., Wittmann, M., Zeiser, T., Wellein, G., Mathias, G., Schwörer, M., Lorenzen, K., Federrath, C., Klessen, R., Bamberg, K., Ruhl, H., Schornbaum, F., Bauer, M., Nikhil, A., Qi, J., Klimach, H., Stüben, H., Deshmukh, A., Falkenstein, T., Dolag, K., Petkova, M.: Extreme scale-out supermuc phase 2-lessons learned. In: Joubert, G.R., Leather, H., Parsons, M., Peters, F.J., Sawyer, M. (eds.) Parallel Computing: On the Road to Exascale, Proceedings of the International Conference on Parallel Computing, ParCo 2015, 1–4 September 2015, Edinburgh, Scotland, UK, Advances in Parallel Computing, vol. 27, pp. 827–836. IOS Press (2015). doi: 10.3233/978-1-61499-621-7-827
  15. 15.
    Harten, A., Hyman, J.M.: Self-adjusting grid methods for one-dimensional hyperbolic conservation laws. J. Comput. Phys. 50, 235–269 (1983). doi: 10.1016/0021-9991(83)90066-9 MathSciNetCrossRefMATHGoogle Scholar
  16. 16.
    Isozaki, H.: Wave operators and the incompressible limit of the compressible euler equation. Commun. Math. Phys. 110(3), 519–524 (1987)MathSciNetCrossRefMATHGoogle Scholar
  17. 17.
    Jeong, J., Hussain, F.: On the identification of a vortex. J. Fluid Mech. 285, 69–94 (1995). doi: 10.1017/S0022112095000462 MathSciNetCrossRefMATHGoogle Scholar
  18. 18.
    Klainerman, S., Majda, A.: Singular limits of quasilinear hyperbolic systems with large parameters and the incompressible limit of compressible fluids. Commun. Pure Appl. Math. 34(4), 481–524 (1981)MathSciNetCrossRefMATHGoogle Scholar
  19. 19.
    Klein, R.: Semi-implicit extension of a Godunov-type scheme based on low mach number asymptotics I: one-dimensional flow. J. Comput. Phys. 121, 213–237 (1995). doi: 10.1016/S0021-9991(95)90034-9 MathSciNetCrossRefMATHGoogle Scholar
  20. 20.
    Kreiss, H.O., Lorenz, J., Naughton, M.: Convergence of the solutions of the compressible to the solutions of the incompressible Navier–Stokes equations. Adv. Appl. Math. 12(2), 187–214 (1991)MathSciNetCrossRefMATHGoogle Scholar
  21. 21.
    Métivier, G., Schochet, S.: The incompressible limit of the non-isentropic Euler equations. Arch. Ration. Mech. Anal. 158(1), 61–90 (2001)MathSciNetCrossRefMATHGoogle Scholar
  22. 22.
    Miczek, F., Röpke, F.K., Edelmann, P.V.F.: New numerical solver for flows at various Mach numbers. Astron. Astrophys. 576, A50 (2015). doi: 10.1051/0004-6361/201425059 CrossRefGoogle Scholar
  23. 23.
    Oßwald, K., Siegmund, A., Birken, P., Hannemann, V., Meister, A.: L2Roe: a low dissipation version of roe’s approximate riemann solver for low Mach numbers. Int. J. Numer. Methods Fluids (2015). doi: 10.1002/fld.4175.Fld.4175
  24. 24.
    Pelanti, M., Quartapelle, L., Vigevano, L.: A review of entropy fixes as applied to roe’s linearization. Teaching material of the Aerospace and Aeronautics Department of Politecnico di Milano (2001). http://services.aero.polimi.it/~quartape/bacheca/materiale_didattico/ef_JCP.pdf
  25. 25.
    Rieper, F.: A low-Mach number fix for Roe’s approximate Riemann solver. J. Comput. Phys. 230(13), 5263–5287 (2011)MathSciNetCrossRefMATHGoogle Scholar
  26. 26.
    Roe, P.L.: Approximate Riemann solvers, parameter vectors, and difference schemes. J. Comput. Phys. 43(2), 357–372 (1981). doi: 10.1016/0021-9991(81)90128-5 MathSciNetCrossRefMATHGoogle Scholar
  27. 27.
    Schmidt, W., Hillebrandt, W., Niemeyer, J.C.: Numerical dissipation and the bottleneck effect in simulations of compressible isotropic turbulence. Comput. Fluids 35, 353–371 (2006). doi: 10.1016/j.compfluid.2005.03.002 CrossRefMATHGoogle Scholar
  28. 28.
    Schochet, S.: Fast singular limits of hyperbolic PDEs. J. Differ. Equ. 114(2), 476–512 (1994). doi: 10.1006/jdeq.1994.1157 MathSciNetCrossRefMATHGoogle Scholar
  29. 29.
    Stephan, M., Docter, J.: Juqueen: IBM Blue Gene/Q\(^{\textregistered }\) supercomputer system at the jülich supercomputing centre. J. Large Scale Res. Facil. JLSRF 1, A1 (2015). doi: 10.17815/jlsrf-1-18 CrossRefGoogle Scholar
  30. 30.
    Taylor, G.I., Green, A.E.: Mechanism of the production of small eddies from large ones. R. Soc. Lond. Proc. Ser. A 158, 499–521 (1937). doi: 10.1098/rspa.1937.0036 CrossRefMATHGoogle Scholar
  31. 31.
    Toro, E.F.: Riemann Solvers and Numerical Methods for Fluid Dynamics: a Practical Introduction. Springer, Berlin (2009). http://books.google.de/books?id=SqEjX0um8o0C
  32. 32.
    Turkel, E.: Preconditioning techniques in computational fluid dynamics. Ann. Rev. Fluid Mech. 31, 385–416 (1999). doi: 10.1146/annurev.fluid.31.1.385 MathSciNetCrossRefGoogle Scholar
  33. 33.
    Ukai, S., et al.: The incompressible limit and the initial layer of the compressible Euler equation. J. Math. Kyoto Univ. 26(2), 323–331 (1986)MathSciNetCrossRefMATHGoogle Scholar
  34. 34.
    van Leer, B.: Towards the ultimate conservative difference scheme. V. A second-order sequel to Godunov’s method. J. Comput. Phys. 32, 101–136 (1979). doi: 10.1016/0021-9991(79)90145-1 CrossRefMATHGoogle Scholar
  35. 35.
    Weiss, J.M., Smith, W.A.: Preconditioning applied to variable and constant density flows. AIAA J. 33, 2050–2057 (1995). doi: 10.2514/3.12946 CrossRefMATHGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Wasilij Barsukow
    • 1
  • Philipp V. F. Edelmann
    • 2
  • Christian Klingenberg
    • 1
  • Fabian Miczek
    • 1
  • Friedrich K. Röpke
    • 2
  1. 1.Institute for MathematicsWürzburg UniversityWürzburgGermany
  2. 2.Heidelberg Institute for Theoretical StudiesHeidelbergGermany

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