Skip to main content
Log in

Stabilized methods for high-speed compressible flows: toward hypersonic simulations

  • Original Paper
  • Published:
Computational Mechanics Aims and scope Submit manuscript

Abstract

A stabilized finite element framework for high-speed compressible flows is presented. The Streamline-Upwind/Petrov–Galerkin formulation augmented with discontinuity-capturing (DC) are the main constituents of the framework that enable accurate, efficient, and stable simulations in this flow regime. Full- and reduced-energy formulations are employed for this class of flow problems and their relative accuracy is assessed. In addition, a recently developed DC formulation is presented and is shown to be particularly well suited for hypersonic flows. Several verification and validation cases, ranging from 1D to 3D flows and supersonic to the hypersonic regimes, show the excellent performance of the proposed framework and set the stage for its deployment on more advanced applications.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23

Similar content being viewed by others

References

  1. Ahrabi BR, Mavriplis DJ (2020) An implicit block ilu smoother for preconditioning of Newton–Krylov solvers with application in high-order stabilized finite-element methods. Comput Methods Appl Mech Eng 358:112637

    MathSciNet  MATH  Google Scholar 

  2. Aliabadi SK, Tezduyar TE (1993) Space-time finite element computation of compressible flows involving moving boundaries and interfaces. Comput Methods Appl Mech Eng 107(1–2):209–223

    MATH  Google Scholar 

  3. Almeida RC, Galeão AC (1996) An adaptive Petrov–Galerkin formulation for the compressible Euler and Navier–Stokes equations. Comput Methods Appl Mech Eng 129(1):157–176

    MathSciNet  MATH  Google Scholar 

  4. Arisman CJ, Johansen CT, Bathel BF, Danehy PM (2015) Investigation of gas seeding for planar laser-induced fluorescence in hypersonic boundary layer. AIAA J 53(12):3637–3651

    Google Scholar 

  5. Baba K, Tabata M (1981) On a conservative upwind finite element scheme for the convective diffusion equations. RAIRO Analyse Numerique 15(1):3–25

    MathSciNet  MATH  Google Scholar 

  6. Bazilevs Y, Kamensky D, Moutsanidis G, Shende S (2020) Residual-based shock capturing in solids. Comput Methods Appl Mech Eng 358:112638

    MathSciNet  MATH  Google Scholar 

  7. Bazilevs Y, Takizawa K, Wu MCH, Kuraishi T, Avsar R, Xu Z, Tezduyar TE (2020) Gas turbine computational flow and structure analysis with isogeometric discretization and a complex-geometry mesh generation method. Comput Mech. https://doi.org/10.1007/s00466-020-01919-w

    Article  Google Scholar 

  8. Brooks AN, Hughes TJR (1982) Streamline upwind/Petrov–Galerkin formulations for convection dominated flows with particular emphasis on the incompressible Navier-Stokes equations. Comput Methods Appl Mech Eng 32:199–259

    MathSciNet  MATH  Google Scholar 

  9. Celik IB et al (2008) Procedure for estimation and reporting of uncertainty due to discretization in CFD applications. J Fluids Eng 130(7):07

    Google Scholar 

  10. Carter JE (1972) Numerical solutions of the Navier–Stokes equations for the supersonic laminar flow over a two-dimensional compression corner. Technical report, nasa-tr-r-385, NASA Langley Research Center; Hampton, VA, United States

  11. Catabriga L, Coutinho ALGA, Tezduyar TE (2005) Compressible flow SUPG parameters computed from element matrices. Commun Numer Methods Eng 21:465–476

    MathSciNet  MATH  Google Scholar 

  12. Catabriga L, Coutinho ALGA, Tezduyar TE (2006) Compressible flow SUPG stabilization parameters computed from degree-of-freedom submatrices. Comput Mech 38:334–343

    MATH  Google Scholar 

  13. Chalot F, Hughes TJR (1994) A consistent equilibrium chemistry algorithm for hypersonic flows. Comput Methods Appl Mech Eng 112:25–40

    MATH  Google Scholar 

  14. Chalot F, Hughes TJR, Shakib F (1990) Symmetrization of conservation laws with entropy for high-temperature hypersonic computations. Comput Syst Eng 1(2–4):495–521

    Google Scholar 

  15. Chapman S, Cowling TG (1970) The mathematical theory of nonuniform gases. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  16. Danehy P, Bathel B, Ivey C, Inman J, Jones S (2009) NO PLIF study of hypersonic transition over a discrete hemispherical roughness element. In: 47th AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition

  17. Denman ED, Beavers AN (1976) The matrix sign function and computations in systems. Appl Math Comput 2(1):63–94

    MathSciNet  MATH  Google Scholar 

  18. Dick E (2009) Introduction to finite element methods in computational fluid dynamics. In: Wendt JF (ed) Computational fluid dynamics, chapter 10. Springer, Berlin

    Google Scholar 

  19. Dumbser M, Moschetta JM, Gressier J (2003) A matrix stability analysis of the carbuncle phenomenon. J Comput Phys 197:647–670

    MATH  Google Scholar 

  20. Edquist KT (2006) Computations of Viking Lander capsule hypersonic aerodynamics with comparisons to ground and flight data. In: AIAA atmospheric flight mechanics conference and exhibit

  21. Elling V (2009) The carbuncle phenomenon is incurable. Acta Mathematica Scientia 29(6):1647–1656

    MathSciNet  MATH  Google Scholar 

  22. Flaherty T (1972) Aerodynamics data book, ver-10. TR-3709014, Martin Marietta Corporation, Denver Division

  23. Hauke G (2001) Simple stabilizing matrices for the computation of compressible flows in primitive variables. Comput Methods Appl Mech Eng 190:6881–6893

    MATH  Google Scholar 

  24. Hauke G, Hughes TJR (1994) A unified approach to compressible and incompressible flows. Comput Methods Appl Mech Eng 113:389–395

    MathSciNet  MATH  Google Scholar 

  25. Hauke G, Hughes TJR (1998) A comparative study of different sets of variables for solving compressible and incompressible flows. Comput Methods Appl Mech Eng 153:1–44

    MathSciNet  MATH  Google Scholar 

  26. Hirschfelder JO, Curtiss CF, Bird RB (1954) Molecular theory of gases and liquids. Wiley, Hoboken

    MATH  Google Scholar 

  27. Hollis BR (1996) Real-gas flow properties for NASA Langley research center aerothermodynamic facilities complex wind tunnels. Nasa contractor report 4755, NASA Langley Research Center; Hampton, VA, United States

  28. Hughes TJR, Franca LP, Hulbert GM (1989) A new finite element formulation for computational fluid dynamics: VIII the Galerkin/least-squares method for advective-diffusive equations. Comput Methods Appl Mech Eng 73:173–189

    MathSciNet  MATH  Google Scholar 

  29. Hughes TJR, Franca LP, Mallet M (1986) A new finite element formulation for computational fluid dynamics: I symmetric forms of the compressible Euler and Navier–Stokes equations and the second law of thermodynamics. Comput Methods Appl Mech Eng 54:223–234

    MathSciNet  MATH  Google Scholar 

  30. Hughes TJR, Franca LP, Mallet M (1987) A new finite element formulation for computational fluid dynamics: VI convergence anaysis of the generalized SUPG formulation for linear time-dependent multidimensional advective–diffusive systems. Comput Methods Appl Mech Eng 63:97–112

    MATH  Google Scholar 

  31. Hughes TJR, Mallet M (1986) A new finite element formulation for computational fluid dynamics: III the generalized streamline operator for multidimensional advective–diffusive systems. Comput Methods Appl Mech Eng 58:305–328

    MathSciNet  MATH  Google Scholar 

  32. Hughes TJR, Mallet M (1986) A new finite element formulation for computational fluid dynamics: IV a discontinuity-capturing operator for multidimensional advective–diffusive systems. Comput Methods Appl Mech Eng 58:329–336

    MathSciNet  MATH  Google Scholar 

  33. Hughes TJR, Mallet M, Mizukami A (1986) A new finite element formulation for computational fluid dynamics: II beyond SUPG. Comput Methods Appl Mech Eng 54:341–355

    MathSciNet  MATH  Google Scholar 

  34. Hughes TJR, Tezduyar TE (1984) Finite element methods for first-order hyperbolic systems with particular emphasis on the compressible Euler equations. Comput Methods Appl Mech Eng 45:217–284

    MathSciNet  MATH  Google Scholar 

  35. Ingoldby RN, Michel FC, Flaherty TM, Doryand MG, Preston B, Villyard KW, Steele RD (1976) Entry data analysis for viking landers 1 and 2 final report. NASA CR-159388, Martin Marietta Corporation, Denver Division

  36. Jansen KE, Whiting CH, Hulbert GM (2000) A generalized-\(\alpha \) method for integrating the filtered Navier–Stokes equations with a stabilized finite element method. Comput Methods Appl Mech Eng 190:305–319

    MathSciNet  MATH  Google Scholar 

  37. Johnson C (1987) Numerical solution of partial differential equations by the finite element method. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  38. Johnson C, Navert U, Pitkaranta J (1984) Finite element methods for linear hyperbolic problems. Comput Methods Appl Mech Eng 45:285–312

    MathSciNet  MATH  Google Scholar 

  39. Johnson C, Szepessy A (1987) On the convergence of a finite element method for a nonlinear hyperbolic conservation law. Math Comput 49(180):427–444

    MathSciNet  MATH  Google Scholar 

  40. Johnson C, Szepessy A, Hansbo P (1990) On the convergence of shock-capturing streamline diffusion finite element methods for hyperbolic conservation laws. Math Comput 54(189):107–129

    MathSciNet  MATH  Google Scholar 

  41. Kanai T, Takizawa K, Tezduyar TE, Tanaka T, Hartmann A (2019) Compressible-flow geometric-porosity modeling and spacecraft parachute computation with isogeometric discretization. Comput Mech 63:301–321

    MathSciNet  MATH  Google Scholar 

  42. Kirk BS, Stogner RH, Bauman PT, Oliver TA (2014) Modeling hypersonic entry with the fully-implicit Navier–Stokes (fin-s) stabilized finite element flow solver. Comput Fluids 92:281–292

    MathSciNet  MATH  Google Scholar 

  43. Kozak N, Rajanna MR, Wu MCH, Murugan M, Bravo L, Ghoshal A, Hsu MC, Bazilevs Y (2020) Optimizing gas turbine performance using the surrogate management framework and high-fidelity flow modeling. Energies 13(17):4283

    Google Scholar 

  44. Kuraishi T, Takizawa K, Tezduyar TE (2019) Tire aerodynamics with actual tire geometry, road contact and tire deformation. Comput Mech 63:1165–1185

    MathSciNet  MATH  Google Scholar 

  45. Le Beau GJ, Ray SE, Aliabadi SK, Tezduyar TE (1993) SUPG finite element computation of compressible flows with entropy and conservation variables formulations. Comput Methods Appl Mech Eng 104:397–422

    MATH  Google Scholar 

  46. Le Beau GJ, Tezduyar TE (1991) Finite element computation of compressible flows with the SUPG formulation. Am Soc Mech Eng Fluids Eng Div Pub FED 123:21–27

    Google Scholar 

  47. Lewis JE (1967) Experimental investigation of supersonic laminar, two-dimensional boundary layer separation in a compression corner with and without cooling. Ph.D. thesis, California Institute of Technology

  48. Mazaheri A, Kleb B (2007) Exploring hypersonic, unstructured-grid issues through structured grids. In: 18th AIAA computational fluid dynamics conference

  49. Neufeld PD, Janzen AR, Aziz RA (1972) Empirical equations to calculate 16 of the transport collision integral \(\omega \) for the Lennard–Jones (12–6) potential. J Chem Phys 57(3):1100–1102

    Google Scholar 

  50. Otoguro Y, Takizawa K, Tezduyar TE (2020) Element length calculation in B-spline meshes for complex geometries. Comput Mech 65:1085–1103

    MathSciNet  MATH  Google Scholar 

  51. Otoguro Y, Takizawa K, Tezduyar TE, Nagaoka K, Avsar R, Zhang Y (2019) Space-time VMS flow analysis of a turbocharger turbine with isogeometric discretization: computations with time-dependent and steady-inflow representations of the intake/exhaust cycle. Comput Mech 64:1403–1419

    MathSciNet  MATH  Google Scholar 

  52. Otoguro Y, Takizawa K, Tezduyar TE, Nagaoka K, Mei S (2019) Turbocharger turbine and exhaust manifold flow computation with the space-time variational multiscale method and isogeometric analysis. Comput Fluids 179:764–776

    MathSciNet  MATH  Google Scholar 

  53. Saad Y, Schultz MH (1986) Gmres: A generalized minimal residual algorithm for solving nonsymmetric linear systems. SIAM J Sci Stat Comput 7(3):856–869

    MathSciNet  MATH  Google Scholar 

  54. Shakib F, Hughes TJR, Johan Z (1991) A new finite element formulation for a computational fluid dyamics: X. The compressible Euler and Navier–Stokes equations. Comput Methods Appl Mech Eng 89:141–219

    Google Scholar 

  55. Sod GA (1978) A survey of several finite difference methods for systems of nonlinear hyperbolic conservations laws. J Comput Phys 27:1–31

    MathSciNet  MATH  Google Scholar 

  56. Sturek WB, Ray S, Aliabadi S, Waters C, Tezduyar TE (1997) Parallel finite element computation of missile aerodynamics. Int J Numer Meth Fluids 24:1417–1432

    MATH  Google Scholar 

  57. Szepessy A (1989) Convergence of a shock-capturing streamline diffusion finite element method for a scalar conservation law in two space dimensions. Math Comput 53(188):527–545

    MathSciNet  MATH  Google Scholar 

  58. Tabata M (1977) A finite element approximation corresponding to the upwind finite differencing. Mem Numer Math 4:47–63

    MathSciNet  MATH  Google Scholar 

  59. Tabata M (1978) Uniform convergence of the upwind finite element approximation for semilinear parabolic problems. J Math Kyoto Univ 18(2):327–351

    MathSciNet  MATH  Google Scholar 

  60. Takizawa K, Tezduyar TE, Kanai T (2017) Porosity models and computational methods for compressible-flow aerodynamics of parachutes with geometric porosity. Math Models Methods Appl Sci 27:771–806

    MathSciNet  MATH  Google Scholar 

  61. Takizawa K, Tezduyar TE, Kuraishi T (2015) Multiscale ST methods for thermo-fluid analysis of a ground vehicle and its tires. Math Models Methods Appl Sci 25:2227–2255

    MathSciNet  MATH  Google Scholar 

  62. Takizawa K, Tezduyar TE, McIntyre S, Kostov N, Kolesar R, Habluetzel C (2014) Space-time VMS computation of wind-turbine rotor and tower aerodynamics. Comput Mech 53:1–15

    MATH  Google Scholar 

  63. Takizawa K, Tezduyar TE, Otoguro Y (2018) Stabilization and discontinuity-capturing parameters for space-time flow computations with finite element and isogeometric discretizations. Comput Mech 62:1169–1186

    MathSciNet  MATH  Google Scholar 

  64. Takizawa K, Ueda Y, Tezduyar TE (2019) A node-numbering-invariant directional length scale for simplex elements. Math Models Methods Appl Sci 29:2719–2753

    MathSciNet  Google Scholar 

  65. Tejada-Martínez AE, Akkerman I, Bazilevs Y (2012) Large-eddy simulation of shallow water Langmuir turbulence using isogeometric analysis and the residual-based variational multiscale method. J Appl Mech 79(1):010909

    Google Scholar 

  66. Tezduyar T, Aliabadi S, Behr M, Johnson A, Kalro V, Litke M (1996) Flow simulation and high performance computing. Comput Mech 18:397–412

    MATH  Google Scholar 

  67. Tezduyar T, Aliabadi S, Behr M, Johnson A, Mittal S (1993) Parallel finite-element computation of 3D flows. Computer 26(10):27–36

    MATH  Google Scholar 

  68. Tezduyar TE, Aliabadi SK, Behr M, Mittal S (1994) Massively parallel finite element simulation of compressible and incompressible flows. Comput Methods Appl Mech Eng 119:157–177

    MATH  Google Scholar 

  69. Tezduyar TE (2001) Adaptive determination of the finite element stabilization parameters. In: Proceedings of the ECCOMAS computational fluid dynamics conference 2001

  70. Tezduyar TE (2002) Calculation of the stabilization parameters in SUPG and PSPG formulations. In: Proceedings of the first South-American congress on computational mechanics

  71. Tezduyar TE (2003) Computation of moving boundaries and interfaces and stabilization parameters. Int J Numer Methods Fluids 43:555–575

    MathSciNet  MATH  Google Scholar 

  72. Tezduyar TE (2004) Determination of the stabilization and shock-capturing parameters in SUPG formulation of compressible flows. In: Proceedings of European congress on computational methods in applied sciences and engineering ECCOMAS 2004

  73. Tezduyar TE (2004) Finite element methods for fluid dynamics with moving boundaries and interfaces. In: Stein E, De Borst R, Hughes TJR (eds) Encyclopedia of computational mechanics, volume 3: fluids, chapter 17. Wiley, New York

    Google Scholar 

  74. Tezduyar TE (2005) Calculation of the stabilization parameters in finite element formulations of flow problems. In: Idelsohn SR, Sonzogni V (eds) Applications of computational mechanics in structures and fluids. CIMNE, Barcelona, pp 1–19

    Google Scholar 

  75. Tezduyar TE, Hughes TJR (1982) Development of time-accurate finite element techniques for first-order hyperbolic systems with particular emphasis on the compressible Euler equations. NASA technical report NASA-CR-204772

  76. Tezduyar TE, Hughes TJR (1983) Finite element formulations for convection dominated flows with particular emphasis on the compressible Euler equations. In: 21st aerospace sciences meeting, AIAA paper 83-0125

  77. Tezduyar TE, Osawa Y (2000) Finite element stabilization parameters computed from element matrices and vectors. Comput Methods Appl Mech Eng 190:411–430

    MATH  Google Scholar 

  78. Tezduyar TE, Park YJ (1986) Discontinuity capturing finite element formulations for nonlinear convection–diffusion–reaction equations. Comput Methods Appl Mech Eng 59:307–325

    MATH  Google Scholar 

  79. Tezduyar TE, Senga M (2006) Stabilization and shock-capturing parameters in SUPG formulation of compressible flows. Comput Methods Appl Mech Eng 195:1621–1632

    MathSciNet  MATH  Google Scholar 

  80. Tezduyar TE, Senga M (2007) SUPG finite element computation of inviscid supersonic flows with YZ\(\beta \) shock-capturing. Comput Fluids 36:147–159

    MATH  Google Scholar 

  81. Tezduyar TE, Senga M, Vicker D (2006) Computation of inviscid supersonic flows around cylinders and spheres with the SUPG formulation and YZ\(\beta \) shock-capturing. Comput Mech 38:469–481

    MATH  Google Scholar 

  82. Ueda Y, Otoguro Y, Takizawa K, Tezduyar TE (2020) Element-splitting-invariant local-length-scale calculation in B-spline meshes for complex geometries. Math Models Methods Appl Sci. https://doi.org/10.1142/S0218202520500402

    Article  MathSciNet  MATH  Google Scholar 

  83. Xu F, Bazilevs Y, Hsu MC (2019) Immersogeometric analysis of compressible flows with application to aerodynamic simulation of rotorcraft. Math Models Methods Appl Sci 29(5):905–938

    MathSciNet  MATH  Google Scholar 

  84. Xu F, Moutsanidis G, Kamensky D, Hsu MC, Murugan M, Ghoshal A, Bazilevs Y (2017) Compressible flows on moving domains: stabilized methods, weakly enforced essential boundary conditions, sliding interfaces, and application to gas-turbine modeling. Comput Fluids 158:201–220

    MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

This research was enabled in part by support provided by WestGrid (www.westgrid.ca) and Compute Canada Calcul Canada (www.computecanada.ca). Financial support was provided by the Natural Sciences and Engineering Research Council of Canada (NSERC). Y. Bazilevs was partially supported by the NSF Award No. 1854436.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Artem Korobenko.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix A

Appendix A

The matrices used for Navier–Stokes equations of compressible flows with full energy equation are given by

$$\begin{aligned} \tilde{{\mathbf {A}}}_0 = \begin{bmatrix} \rho \beta _{T} &{}0&{}0 &{}0 &{} -\rho \alpha _{p}\\ \rho \beta _{T} u_1 &{}\rho &{}0 &{}0 &{} -\rho \alpha _{p}u_1\\ \rho \beta _{T} u_2 &{}0&{}\rho &{}0 &{} -\rho \alpha _{p}u_2\\ \rho \beta _{T} u_3 &{}0&{}0 &{}\rho &{} -\rho \alpha _{p}u_3\\ \rho \beta _{T} e_\text {tot} &{}\rho u_1&{}\rho u_2 &{}\rho u_3 &{} \rho \left( -\alpha _{p} e_\text {tot} + c_\text {v} \right) \\ \end{bmatrix}\text {,} \end{aligned}$$
(A.1)

where \(\beta _{T} = 1/p\), \(\alpha _{p} = 1/T\).

Its inverse \(\tilde{{\mathbf {A}}}_0^{-1} = {\mathbf {Y}}_{,\tilde{{\mathbf {U}}}}\) is given by

$$\begin{aligned} \tilde{{\mathbf {A}}}_0^{-1} = \begin{bmatrix} \dfrac{-\alpha _{p}e_\text {tot} +\alpha _{p} \Vert {\mathbf {u}}\Vert ^2+ c_\text {v}}{\rho \beta _{T} c_\text {v}}&{}-\dfrac{\alpha _pu_1}{\rho \beta _{T} c_\text {v}}&{}-\dfrac{\alpha _pu_2}{\rho \beta _{T} c_\text {v}} &{}-\dfrac{\alpha _pu_3}{\rho \beta _{T} c_\text {v}} &{} \dfrac{\alpha _p}{\rho \beta _{T} c_\text {v}}\\ -\dfrac{u_1}{\rho } &{}\dfrac{1}{\rho }&{}0 &{}0 &{} 0\\ -\dfrac{u_2}{\rho } &{}0&{}\dfrac{1}{\rho } &{}0 &{} 0\\ -\dfrac{u_3}{\rho } &{}0&{}0 &{}\dfrac{1}{\rho }&{} 0\\ \dfrac{ \Vert {\mathbf {u}}\Vert ^2 - e_\text {tot}}{\rho c_\text {v}}&{}-\dfrac{u_1}{\rho c_\text {v}}&{}-\dfrac{u_2}{\rho c_\text {v}}&{}-\dfrac{u_3}{\rho c_\text {v}}&{} \dfrac{1}{\rho c_\text {v}}\\ \end{bmatrix}\text {.} \end{aligned}$$
(A.2)

We then give the details of the Euler Jacobian matrices by

$$\begin{aligned} \tilde{{\mathbf {A}}}_1^{\text {adv} \backslash p}&= \begin{bmatrix} \rho \beta _{T} u_1 &{} \rho &{}0 &{}0 &{} -\rho \alpha _{p} u_1\\ \rho \beta _{T} u_1^2 &{}2\rho u_1&{}0 &{}0 &{} -\rho \alpha _{p}u_1^2\\ \rho \beta _{T} u_1 u_2 &{}\rho u_2&{}\rho u_1&{}0 &{} -\rho \alpha _{p} u_1 u_2\\ \rho \beta _{T} u_1 u_3 &{}\rho u_3&{}0 &{}\rho u_1&{} -\rho \alpha _{p} u_1 u_3\\ \left( \rho \beta _{T} e_\text {tot} + 1\right) u_1 &{}\rho \left( e_\text {tot} + u_1^2 \right) + p&{}\rho u_1 u_2 &{}\rho u_1 u_3 &{} \rho \left( -\alpha _{p} e_\text {tot} + c_\text {v} \right) u_1\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.3)
$$\begin{aligned} \tilde{{\mathbf {A}}}_2^{\text {adv} \backslash p}&= \begin{bmatrix} \rho \beta _{T} u_2 &{}0&{} \rho &{}0 &{} -\rho \alpha _{p} u_2\\ \rho \beta _{T} u_1 u_2 &{}\rho u_2&{}\rho u_1 &{}0 &{} -\rho \alpha _{p}u_1 u_2\\ \rho \beta _{T} u_2^2 &{} 0 &{}2\rho u_2&{}0 &{} -\rho \alpha _{p} u_2^2\\ \rho \beta _{T} u_2 u_3 &{}0 &{}\rho u_3&{}\rho u_2&{} -\rho \alpha _{p} u_2 u_3\\ \left( \rho \beta _{T} e_\text {tot} + 1\right) u_2 &{}\rho u_1 u_2 &{}\rho \left( e_\text {tot} + u_2^2 \right) + p&{}\rho u_2 u_3 &{} \rho \left( -\alpha _{p} e_\text {tot} + c_\text {v} \right) u_2\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.4)
$$\begin{aligned} \tilde{{\mathbf {A}}}_3^{\text {adv} \backslash p}&= \begin{bmatrix} \rho \beta _{T} u_3 &{} 0 &{}0 &{} \rho &{} -\rho \alpha _{p} u_3\\ \rho \beta _{T} u_1 u_3 &{}\rho u_3&{}0 &{}\rho u_1&{} -\rho \alpha _{p}u_1 u_3\\ \rho \beta _{T} u_2 u_3 &{} 0 &{}\rho u_3&{}\rho u_2 &{} -\rho \alpha _{p} u_2 u_3\\ \rho \beta _{T} u_3^2 &{}0 &{}0&{}2\rho u_3&{} -\rho \alpha _{p} u_3^2\\ \left( \rho \beta _{T} e_\text {tot} + 1\right) u_3 &{}\rho u_1 u_3 &{}\rho u_2 u_3 &{}\rho \left( e_\text {tot} + u_3^2 \right) + p&{} \rho \left( -\alpha _{p} e_\text {tot} + c_\text {v} \right) u_3\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.5)
$$\begin{aligned} \tilde{{\mathbf {A}}}_1^{p}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 1 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.6)
$$\begin{aligned} \tilde{{\mathbf {A}}}_2^{p}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 1 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.7)
$$\begin{aligned} \tilde{{\mathbf {A}}}_3^{p}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 1 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ \end{bmatrix}\text {.} \end{aligned}$$
(A.8)

Note that \(\tilde{{\mathbf {A}}}_i = \tilde{{\mathbf {A}}}_i^{\text {adv} \backslash p} + \tilde{{\mathbf {A}}}_i^{p} \).

Finally, we give the diffusive matrices by

$$\begin{aligned} \tilde{{\mathbf {K}}}_{11}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 2\mu +\lambda &{} 0&{} 0&{} 0\\ 0 &{} 0&{} \mu &{} 0&{} 0\\ 0 &{} 0&{} 0&{} \mu &{} 0\\ 0 &{} \left( 2\mu +\lambda \right) u_1&{} \mu u_2&{} \mu u_3&{} \kappa \\ \end{bmatrix}\text {,} \end{aligned}$$
(A.9)
$$\begin{aligned} \tilde{{\mathbf {K}}}_{12}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} \lambda &{} 0&{} 0\\ 0 &{} \mu &{}0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} \mu u_2&{} \lambda u_1&{} 0 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.10)
$$\begin{aligned} \tilde{{\mathbf {K}}}_{13}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} \lambda &{} 0\\ 0 &{} 0&{}0&{} 0&{} 0\\ 0 &{} \mu &{} 0&{} 0&{} 0\\ 0 &{} \mu u_3&{}0&{} \lambda u_1 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.11)
$$\begin{aligned} \tilde{{\mathbf {K}}}_{21}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} \mu &{} 0&{} 0\\ 0 &{} \lambda &{}0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} \lambda u_2&{} \mu u_1&{}0 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.12)
$$\begin{aligned} \tilde{{\mathbf {K}}}_{22}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} \mu &{} 0&{} 0&{} 0\\ 0 &{} 0&{} 2\mu +\lambda &{} 0&{} 0\\ 0 &{} 0&{} 0&{} \mu &{} 0\\ 0 &{} \mu u_1&{} \left( 2\mu +\lambda \right) u_2 &{} \mu u_3&{} \kappa \\ \end{bmatrix}\text {,} \end{aligned}$$
(A.13)
$$\begin{aligned} \tilde{{\mathbf {K}}}_{23}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0 &{}0&{} \lambda &{} 0\\ 0 &{} 0&{} \mu &{} 0&{} 0\\ 0 &{} 0&{} \mu u_3&{}\lambda u_2 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.14)
$$\begin{aligned} \tilde{{\mathbf {K}}}_{31}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} \mu &{} 0\\ 0 &{} 0 &{}0&{} 0&{} 0\\ 0 &{} \lambda &{} 0&{} 0&{} 0\\ 0 &{} \lambda u_3&{} 0&{} \mu u_1 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.15)
$$\begin{aligned} \tilde{{\mathbf {K}}}_{32}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0 &{}0&{} \mu &{} 0\\ 0 &{} 0&{} \lambda &{} 0&{} 0\\ 0 &{} 0&{} \lambda u_3&{}\mu u_2 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.16)
$$\begin{aligned} \tilde{{\mathbf {K}}}_{33}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} \mu &{} 0&{} 0&{} 0\\ 0 &{} 0&{}\mu &{} 0&{} 0\\ 0 &{} 0&{} 0&{} 2\mu +\lambda &{} 0\\ 0 &{} \mu u_1&{} \mu u_2&{} \left( 2\mu +\lambda \right) u_3 &{} \kappa \\ \end{bmatrix}\text {.} \end{aligned}$$
(A.17)

For the Navier–Stokes equations with reduced energy formulation, the matrices corresponding to pressure-primitive variables are as follows:

The matrix \({\mathbf {A}}_0 = {\mathbf {U}}_{,{\mathbf {Y}}}\) is given by

$$\begin{aligned} {\mathbf {A}}_0 = \begin{bmatrix} \rho \beta _{T} &{}0&{}0 &{}0 &{} -\rho \alpha _{p}\\ \rho \beta _{T} u_1 &{}\rho &{}0 &{}0 &{} -\rho \alpha _{p}u_1\\ \rho \beta _{T} u_2 &{}0&{}\rho &{}0 &{} -\rho \alpha _{p}u_2\\ \rho \beta _{T} u_3 &{}0&{}0 &{}\rho &{} -\rho \alpha _{p}u_3\\ \rho \beta _{T} e &{}0&{}0&{}0&{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.18)

It’s inverse \({\mathbf {A}}_0^{-1} = {\mathbf {Y}}_{,{\mathbf {U}}}\) is given by

$$\begin{aligned} {\mathbf {A}}_0^{-1} = \begin{bmatrix} 0&{}0&{}0 &{}0&{} \dfrac{\alpha _p}{\rho \beta _{T} c_\text {v}}\\ -\dfrac{u_1}{\rho } &{}\dfrac{1}{\rho }&{}0 &{}0 &{} 0\\ -\dfrac{u_2}{\rho } &{}0&{}\dfrac{1}{\rho } &{}0 &{} 0\\ -\dfrac{u_3}{\rho } &{}0&{}0 &{}\dfrac{1}{\rho }&{} 0\\ -\dfrac{T}{\rho }&{}0&{}0&{}0&{} \dfrac{1}{\rho c_\text {v}}\\ \end{bmatrix}\text {.} \end{aligned}$$
(A.19)

The Euler–Jacobian matrices are given by

$$\begin{aligned} {\mathbf {A}}_1^{\text {adv} \backslash p}&= \begin{bmatrix} \rho \beta _{T} u_1 &{} \rho &{}0 &{}0 &{} -\rho \alpha _{p} u_1\\ \rho \beta _{T} u_1^2 &{}2\rho u_1&{}0 &{}0 &{} -\rho \alpha _{p}u_1^2\\ \rho \beta _{T} u_1 u_2 &{}\rho u_2&{}\rho u_1&{}0 &{} -\rho \alpha _{p} u_1 u_2\\ \rho \beta _{T} u_1 u_3 &{}\rho u_3&{}0 &{}\rho u_1&{} -\rho \alpha _{p} u_1 u_3\\ \rho \beta _{T} e u_1 &{}\rho e &{}0&{}0 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.20)
$$\begin{aligned} {\mathbf {A}}_2^{\text {adv} \backslash p}&= \begin{bmatrix} \rho \beta _{T} u_2 &{}0&{} \rho &{}0 &{} -\rho \alpha _{p} u_2\\ \rho \beta _{T} u_1 u_2 &{}\rho u_2&{}\rho u_1 &{}0 &{} -\rho \alpha _{p}u_1 u_2\\ \rho \beta _{T} u_2^2 &{} 0 &{}2\rho u_2&{}0 &{} -\rho \alpha _{p} u_2^2\\ \rho \beta _{T} u_2 u_3 &{}0 &{}\rho u_3&{}\rho u_2&{} -\rho \alpha _{p} u_2 u_3\\ \rho \beta _{T} e u_2 &{}0 &{}\rho e&{}0&{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.21)
$$\begin{aligned} {\mathbf {A}}_3^{\text {adv} \backslash p}&= \begin{bmatrix} \rho \beta _{T} u_3 &{} 0 &{}0 &{} \rho &{} -\rho \alpha _{p} u_3\\ \rho \beta _{T} u_1 u_3 &{}\rho u_3&{}0 &{}\rho u_1&{} -\rho \alpha _{p}u_1 u_3\\ \rho \beta _{T} u_2 u_3 &{} 0 &{}\rho u_3&{}\rho u_2 &{} -\rho \alpha _{p} u_2 u_3\\ \rho \beta _{T} u_3^2 &{}0 &{}0&{}2\rho u_3&{} -\rho \alpha _{p} u_3^2\\ \rho \beta _{T} e u_3 &{} 0 &{} 0 &{} \rho e &{} 0 \\ \end{bmatrix}\text {,} \end{aligned}$$
(A.22)
$$\begin{aligned} {\mathbf {A}}_1^{p}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 1 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.23)
$$\begin{aligned} {\mathbf {A}}_2^{p}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 1 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.24)
$$\begin{aligned} {\mathbf {A}}_3^{p}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 1 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ \end{bmatrix}\text {.} \end{aligned}$$
(A.25)
$$\begin{aligned} {\mathbf {A}}_1^{\text {sp}}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} p-\tau _{11}&{} -\tau _{12}&{} -\tau _{13}&{} 0\\ \end{bmatrix}\text {.} \end{aligned}$$
(A.26)
$$\begin{aligned} {\mathbf {A}}_2^{\text {sp}}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} -\tau _{21}&{}p -\tau _{22}&{} -\tau _{23}&{} 0\\ \end{bmatrix}\text {.} \end{aligned}$$
(A.27)
$$\begin{aligned} {\mathbf {A}}_3^{\text {sp}}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} -\tau _{31}&{} -\tau _{32}&{}p -\tau _{33}&{} 0\\ \end{bmatrix}\text {.} \end{aligned}$$
(A.28)

The diffusivity matrices are given by

$$\begin{aligned} {\mathbf {K}}_{11}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 2\mu +\lambda &{} 0&{} 0&{} 0\\ 0 &{} 0&{} \mu &{} 0&{} 0\\ 0 &{} 0&{} 0&{} \mu &{} 0\\ 0 &{}0 &{} 0&{} 0&{} \kappa \\ \end{bmatrix}\text {,} \end{aligned}$$
(A.29)
$$\begin{aligned} {\mathbf {K}}_{12}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} \lambda &{} 0&{} 0\\ 0 &{} \mu &{}0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{}0&{}0&{} 0 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.30)
$$\begin{aligned} {\mathbf {K}}_{13}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} \lambda &{} 0\\ 0 &{} 0&{}0&{} 0&{} 0\\ 0 &{} \mu &{} 0&{} 0&{} 0\\ 0 &{}0&{}0&{}0 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.31)
$$\begin{aligned} {\mathbf {K}}_{21}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} \mu &{} 0&{} 0\\ 0 &{} \lambda &{}0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{}0&{}0&{}0 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.32)
$$\begin{aligned} {\mathbf {K}}_{22}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} \mu &{} 0&{} 0&{} 0\\ 0 &{} 0&{} 2\mu +\lambda &{} 0&{} 0\\ 0 &{} 0&{} 0&{} \mu &{} 0\\ 0 &{}0&{}0&{}0&{} \kappa \\ \end{bmatrix}\text {,} \end{aligned}$$
(A.33)
$$\begin{aligned} {\mathbf {K}}_{23}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0 &{}0&{} \lambda &{} 0\\ 0 &{} 0&{} \mu &{} 0&{} 0\\ 0 &{} 0&{} 0&{}0 &{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.34)
$$\begin{aligned} {\mathbf {K}}_{31}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} \mu &{} 0\\ 0 &{} 0 &{}0&{} 0&{} 0\\ 0 &{} \lambda &{} 0&{} 0&{} 0\\ 0 &{} 0&{}0&{}0&{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.35)
$$\begin{aligned} {\mathbf {K}}_{32}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} 0 &{}0&{} \mu &{} 0\\ 0 &{} 0&{} \lambda &{} 0&{} 0\\ 0 &{} 0&{}0&{}0&{}0\\ \end{bmatrix}\text {,} \end{aligned}$$
(A.36)
$$\begin{aligned} {\mathbf {K}}_{33}&= \begin{bmatrix} 0 &{} 0&{} 0&{} 0&{} 0\\ 0 &{} \mu &{} 0&{} 0&{} 0\\ 0 &{} 0&{}\mu &{} 0&{} 0\\ 0 &{} 0&{} 0&{} 2\mu +\lambda &{} 0\\ 0 &{} 0&{}0&{}0 &{} \kappa \\ \end{bmatrix}\text {.} \end{aligned}$$
(A.37)

The matrices for the conservation variables may be obtained from the corresponding matrices for the pressure-primitive variables using the following transformations: \(\hat{{\mathbf {A}}}_i={\mathbf {A}}_i{\mathbf {A}}_0^{-1}\), \(\hat{{\mathbf {A}}}_i^{\text {adv} \backslash p}={\mathbf {A}}_i^{\text {adv} \backslash p}{\mathbf {A}}_0^{-1}\), \(\hat{{\mathbf {A}}}_i^{p}={\mathbf {A}}_i^{p}{\mathbf {A}}_0^{-1}\), \(\hat{{\mathbf {A}}}_i^{\text {sp}}={\mathbf {A}}_i^{\text {sp}}{\mathbf {A}}_0^{-1}\), and \(\hat{{\mathbf {K}}}_{ij}={\mathbf {K}}_{ij}{\mathbf {A}}_0^{-1}\)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Codoni, D., Moutsanidis, G., Hsu, MC. et al. Stabilized methods for high-speed compressible flows: toward hypersonic simulations. Comput Mech 67, 785–809 (2021). https://doi.org/10.1007/s00466-020-01963-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00466-020-01963-6

Keywords

Navigation