×

An adaptive mesh refinement method based on a characteristic-compression embedded shock wave indicator for high-speed flows. (English) Zbl 07899541

Summary: Numerical simulation of high-speed flows often needs a fine grid for capturing detailed structures of shock or contact wave, which makes high-order discontinuous Galerkin methods (DGMs) extremely costly. In this work, a characteristic-compression based adaptive mesh refinement (AMR, h-adaptive) method is proposed for efficiently improving resolution of the high-speed flows. In order to allocate computational resources to needed regions, a characteristic-compression embedded shock wave indicator is developed on incompatible grids and employed as the criterion for AMR. This indicator applies the admissible jumps of eigenvalues to measure the local compression of homogeneous characteristic curves, and theoretically can capture regions of characteristic-compression which contain structures of shock, contact waves and vortices. Numerical results show that the proposed h-adaptive DGM is robust, efficient and high-resolution, it can capture dissipative shock, contact waves of different strengths and vortices with low noise on a rather coarse grid, and can significantly improve resolution of these structures through mild increase of computational resources as compared with the residual-based h-adaptive method.
© 2024 Wiley Periodicals LLC.

MSC:

65Mxx Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems
76Mxx Basic methods in fluid mechanics
65Nxx Numerical methods for partial differential equations, boundary value problems

Software:

Concha
Full Text: DOI

References:

[1] B. R.Ahrabi, W. K.Anderson, I.Newman, and C.James, An adjoint‐based hp‐adaptive stabilized finite‐element method with shock capturing for turbulent flows, Comput. Methods Appl. Mech. Eng.318 (2017), 1030-1065. · Zbl 1439.76042
[2] T. J.Barth and D. C.Jespersen. The design and application of upwind schemes on unstructured meshes, AIAA Aerospace ENCES Meet., 0366. Reno, Nevada, 1989.
[3] R.Becker, K.Gokpi, E.Schall, and D.Trujillo, Fully implicit adaptive method using discontinuous Galerkin finite elements for high speed flows, Int. J. Aerodyn.2 (2012), 222-239.
[4] Z.Cai and R.Li, An h‐adaptive mesh method for Boltzmann‐BGK/hydrodynamics coupling, J. Comput. Phys.229 (2010), 1661-1680. · Zbl 1329.76251
[5] J.Cheng and C.‐W.Shu, Positivity‐preserving lagrangian scheme for multi‐material compressible flow, J. Comput. Phys.257 (2014), 143-168. · Zbl 1349.76439
[6] A.Choudhary and C.Roy. Efficient residual‐based mesh adaptation for 1D and 2D CFD applications, AIAA Aerospace Sci. Meet. Including the New Horizons Forum Aerospace Exp. Texas2013.
[7] B.Cockburn and C.‐W.Shu, TVB Runge‐Kutta local projection discontinuous Galerkin finite element method for conservation laws. II. General framework, Math. Comput.52 (1989), 411-435. · Zbl 0662.65083
[8] B.Cockburn and C.‐W.Shu, The local discontinuous Galerkin method for time‐dependent convection‐diffusion systems, SIAM J. Numer. Anal.35 (1998), 2440-2463. · Zbl 0927.65118
[9] B.Cockburn, S.‐Y.Lin, and C.‐W.Shu, TVB Runge‐Kutta local projection discontinuous Galerkin finite element method for conservation laws III: one dimensional systems, J. Comput. Phys.84 (1988), 90-113. · Zbl 0677.65093
[10] B.Cockburn, S.Hou, and C.‐W.Shu, The Runge‐Kutta local projection discontinuous Galerkin finite element method for conservation laws. IV. The multidimensional case, Math. Comput.54 (1990), 545-581. · Zbl 0695.65066
[11] R.Duvigneau, CAD‐consistent adaptive refinement using a NURBS‐based discontinuous Galerkin method, Int. J. Numer. Methods Fluids92 (2020), 1096-1117.
[12] Y.Feng and T.Liu, A characteristic‐featured shock wave indicator on unstructured grids based on training an artificial neuron, J. Comput. Phys.443 (2021), 110446. · Zbl 07515404
[13] Y.Feng, T.Liu, and K.Wang, A characteristic‐featured shock wave indicator for conservation laws based on training an artificial neuron, J. Sci. Comput.83 (2020), 1-34. · Zbl 1437.65136
[14] K. J.Fidkowski and D. L.Darmofal, Review of output‐based error estimation and mesh adaptation in computational fluid dynamics, Aiaa J.49 (2011), 673-694.
[15] N.Ganesh, N. V.Shende, and N.Balakrishnan, A residual estimator based adaptation strategy for compressible flows, computational, Fluid Dyn2009 (2006), pp. 383-388.
[16] S.Gottlieb, C.‐W.Shu, and E.Tadmor, Strong stability‐preserving high‐order time discretization methods, SIAM Rev.43 (2001), 89-112. · Zbl 0967.65098
[17] W.Hackbusch, Multi‐grid methods and applications, vol. 4, Springer Science & Business Media, Berlin, Germany, 2013.
[18] A.Harten and S.Osher, “Uniformly high‐order accurate nonoscillatory schemes. I,” Upwind and high‐resolution schemes, M. Y.Hussaini (ed.), B.vanLeer (ed.), J.Van Rosendale (ed.) (eds.), Springer, Berlin, Germany, 1997, pp. 187-217. · Zbl 0877.76002
[19] R.Hartmann, Adaptive discontinuous Galerkin methods with shock‐capturing for the compressible Navier‐Stokes equations, Int. J. Numer. Methods Fluids51 (2010), 1131-1156. · Zbl 1106.76041
[20] R.Hartmann and P.Houston, Adaptive discontinuous Galerkin finite element methods for nonlinear hyperbolic conservation Laws, Soc. Ind. Appl. Math.183 (2002a), 508-532. · Zbl 1057.76033
[21] R.Hartmann and P.Houston, Adaptive discontinuous Galerkin finite element methods for the compressible Euler equations, J. Comput. Phys.183 (2002b), 508-532. · Zbl 1057.76033
[22] J. S.Hesthaven and T.Warburton, Nodal discontinuous Galerkin methods: Algorithms, analysis, and applications, Springer Science & Business Media, Berlin, Germany, 2007.
[23] P.Houston and E.Sli, Hp‐adaptive discontinuous Galerkin finite element methods for first‐order hyperbolic problems, SIAM J. Sci. Comput.23 (2001), 1226-1252. · Zbl 1029.65130
[24] A.Jameson, W.Schmidt, and E.Turkel. Numerical solution of the Euler equations by finite volume methods using Runge Kutta time stepping schemes, 14th Fluid Plasma Dyn. Conf. 1981, p. 1259.
[25] D. A.Knoll and D. E.Keyes, Jacobian‐free newton-krylov methods: A survey of approaches and applications, J. Comput. Phys.193 (2004), 357-397. · Zbl 1036.65045
[26] A.Kurganov and E.Tadmor, Solution of two‐dimensional riemann problems for gas dynamics without Riemann problem solvers, Numer. Methods Partial Differ. Equ.18 (2002), 584-608. · Zbl 1058.76046
[27] W.Li and D. J.Mavriplis, Adjoint‐based h‐p adaptive discontinuous Galerkin methods for the compressible Euler equations, J. Comput. Phys.228 (2009), 7643-7661. · Zbl 1391.76367
[28] H.Luo, J. D.Baum, and R.Lhner, A fast, matrix‐free implicit method for compressible flows on unstructured grids, J. Comput. Phys.146 (1998), 73-78.
[29] H.Luo, J. D.Baum, and R.Löhner, A discontinuous Galerkin method based on a Taylor basis for the compressible flows on arbitrary grids, J. Comput. Phys.227 (2008), 8875-8893. · Zbl 1391.76350
[30] P.Mossier, A.Beck, and C.‐D.Munz, A p‐adaptive discontinuous galerkin method with hp‐shock capturing, J. Sci. Comput.91 (2022), 4. · Zbl 07488714
[31] R. C.Moura, A.Silva, E.Bigarella, A. L.Fazenda, and M.Ortega, Lyapunov exponents and adaptive mesh refinement for high‐speed flows using a discontinuous Galerkin scheme, J. Comput. Phys.319 (2016), 9-27. · Zbl 1349.76243
[32] J. T.Oden, T.Strouboulis, and P.Devloo, Adaptive finite element methods for the analysis of inviscid compressible flow: Part I. Fast refinement/unrefinement and moving mesh methods for unstructured meshes, Comput. Methods Appl. Mech. Eng.59 (1986), 327-362. · Zbl 0593.76080
[33] A.Papoutsakis, S. S.Sazhin, S.Begg, I.Danaila, and F.Luddens, An efficient adaptive mesh refinement (AMR) algorithm for the discontinuous Galerkin method: applications for the computation of compressible two‐phase flows, J. Comput. Phys.363 (2018), 399-427. · Zbl 1392.76029
[34] E.Schall and N.Chauchat, Implicit method and slope limiter in AHMR procedure for high order discontinuous Galerkin methods for compressible flows, Commun. Nonlinear Sci. Numer. Simul.72 (2019), 371-391. · Zbl 1464.65126
[35] C. W.Schulz‐Rinne, Classification of the riemann problem for two‐dimensional gas dynamics, SIAM J. Math. Anal.24 (1993), 76-88. · Zbl 0811.35082
[36] C.‐W.Shu, “Essentially non‐oscillatory and weighted essentially non‐oscillatory schemes for hyperbolic conservation laws,” Advanced numerical approximation of nonlinear hyperbolic equations, A.Quarteroni (ed.) (ed.), Springer, Berlin, Germany, 1998, pp. 325-432. · Zbl 0927.65111
[37] E.Tadmor, Entropy stability theory for difference approximations of nonlinear conservation laws and related time‐dependent problems, Acta Numer.12 (2003), 451-512. · Zbl 1046.65078
[38] E. F.Toro, Riemann solvers and numerical methods for fluid dynamics: A practical introduction, Springer Science & Business Media, 2013.
[39] J. J.Van der Vegt and H.Van der Ven, Space‐time discontinuous Galerkin finite element method with dynamic grid motion for inviscid compressible flows: I. General formulation, J. Comput. Phys.182 (2002), 546-585. · Zbl 1057.76553
[40] B.Van Leer, Towards the ultimate conservative difference scheme. V. A second‐order sequel to Godunov’s method, J. Comput. Phys.32 (1979), 101-136. · Zbl 1364.65223
[41] J.Videla, C.Anitescu, T.Khajah, S. P.Bordas, and E.Atroshchenko, h‐and p‐adaptivity driven by recovery and residual‐based error estimators for pht‐splines applied to time‐harmonic acoustics, Comput. Math. Appl.77 (2019), 2369-2395. · Zbl 1442.65409
[42] Z.Wang, Adaptive high‐order methods in computational fluid dynamics, World Scientific, Singapore, 2011. · Zbl 1234.76007
[43] Z. J.Wang, K.Fidkowski, R.Abgrall, F.Bassi, D.Caraeni, A.Cary, H.Deconinck, R.Hartmann, K.Hillewaert, and H. T.Huynh, High‐order CFD methods: Current status and perspective, Int. J. Numer. Methods Fluids72 (2013), 811-845. · Zbl 1455.76007
[44] O. C.Zienkiewicz and J. Z.Zhu, A simple error estimator and adaptive procedure for practical engineerng analysis, Int. J. Numer. Methods Eng.24 (1987), 337-357. · Zbl 0602.73063
[45] O. C.Zienkiewicz and J. Z.Zhu, Recovery procedures in error estimation and adaptivity Part i: adaptivity in linear problems, Comput. Methods Appl. Mech. Eng.176 (1999), 111-125. · Zbl 0955.74069
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.