×

Development of a balanced adaptive time-stepping strategy based on an implicit JFNK-DG compressible flow solver. (English) Zbl 1499.76086

Summary: A balanced adaptive time-stepping strategy is implemented in an implicit discontinuous Galerkin solver to guarantee the temporal accuracy of unsteady simulations. A proper relation between the spatial, temporal and iterative errors generated within one time step is constructed. With an estimate of temporal and spatial error using an embedded Runge-Kutta scheme and a higher order spatial discretization, an adaptive time-stepping strategy is proposed based on the idea that the time step should be the maximum without obviously influencing the total error of the discretization. The designed adaptive time-stepping strategy is then tested in various types of problems including isentropic vortex convection, steady-state flow past a flat plate, Taylor-Green vortex and turbulent flow over a circular cylinder at \(Re = 3\,900\). The results indicate that the adaptive time-stepping strategy can maintain that the discretization error is dominated by the spatial error and relatively high efficiency is obtained for unsteady and steady, well-resolved and under-resolved simulations.

MSC:

76N06 Compressible Navier-Stokes equations
65M60 Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs
65L06 Multistep, Runge-Kutta and extrapolation methods for ordinary differential equations
76M10 Finite element methods applied to problems in fluid mechanics

Software:

Nektar++

References:

[1] Arévalo, C.; Söderlind, G.; Hadjimichael, Y.; Fekete, I., Local error estimation and step size control in adaptive linear multistep methods, Numer. Algor., 86, 537-556 (2021) · Zbl 1458.65080 · doi:10.1007/s11075-020-00900-1
[2] Bassi, F.; Botti, L.; Colombo, A.; Crivellini, A.; Ghidoni, A.; Massa, F., On the development of an implicit high-order discontinuous Galerkin method for DNS and implicit LES of turbulent flows, Eur. J. Mech. B/Fluids, 55, 367-379 (2016) · Zbl 1408.76360 · doi:10.1016/j.euromechflu.2015.08.010
[3] Bijl, H.; Carpenter, MH; Vatsa, VN; Kennedy, CA, Implicit time integration schemes for the unsteady compressible Navier-Stokes equations: laminar flow, J. Comput. Phys., 179, 1, 313-329 (2002) · Zbl 1060.76079 · doi:10.1006/jcph.2002.7059
[4] Birken, P.; Gassner, G.; Haas, M.; Munz, C-D, Preconditioning for modal discontinuous Galerkin methods for unsteady 3D Navier-Stokes equations, J. Comput. Phys., 240, 20-35 (2013) · Zbl 1426.76520 · doi:10.1016/j.jcp.2013.01.004
[5] Blom, DS; Birken, P.; Bijl, H.; Kessels, F.; Meister, A.; van Zuijlen, AH, A comparison of Rosenbrock and ESDIRK methods combined with iterative solvers for unsteady compressible flows, Adv. Comput. Math., 42, 6, 1401-1426 (2016) · Zbl 1388.76166 · doi:10.1007/s10444-016-9468-x
[6] Bücker, HM; Pollul, B.; Rasch, A., On CFL evolution strategies for implicit upwind methods in linearized Euler equations, Int. J. Numer. Methods Fluids, 59, 1, 1-18 (2009) · Zbl 1149.76031 · doi:10.1002/fld.1798
[7] De Wiart, CC; Hillewaert, K.; Duponcheel, M.; Winckelmans, G., Assessment of a discontinuous Galerkin method for the simulation of vortical flows at high Reynolds number, Int. J. Numer. Methods Fluids, 74, 7, 469-493 (2014) · Zbl 1455.65163 · doi:10.1002/fld.3859
[8] Eisenstat, SC; Walker, HE, Choosing the forcing terms in an inexact newton method, SIAM J. Sci. Comput., 17, 1, 16-32 (1996) · Zbl 0845.65021 · doi:10.1137/0917003
[9] Grinstein, FF; Margolin, LG; Rider, WJ, Implicit Large Eddy Simulation: Computing Turbulent Fluid Dynamics (2007), Cambridge: Cambridge University Press, Cambridge · Zbl 1135.76001 · doi:10.1017/CBO9780511618604
[10] Hartmann, R.; Houston, P., An optimal order interior penalty discontinuous Galerkin discretization of the compressible Navier-Stokes equations, J. Comput. Phys., 227, 22, 9670-9685 (2008) · Zbl 1359.76220 · doi:10.1016/j.jcp.2008.07.015
[11] Holst, KR; Glasby, RS; Bond, RB, On the effect of temporal error in high-order simulations of unsteady flows, J. Comput. Phys., 402, 108989 (2020) · Zbl 1453.76071 · doi:10.1016/j.jcp.2019.108989
[12] Kalkote, N.; Assam, A.; Eswaran, V., Acceleration of later convergence in a density-based solver using adaptive time stepping, AIAA J., 57, 1, 352-364 (2019) · doi:10.2514/1.J057014
[13] Karniadakis, G.; Sherwin, S., Spectral/hp Element Methods for Computational Fluid Dynamics (2013), Oxford: Oxford Science Publications, Oxford · Zbl 1256.76003
[14] Kelley, CT, Numerical methods for nonlinear equations, Acta Numerica, 27, 207-287 (2018) · Zbl 1429.65108 · doi:10.1017/S0962492917000113
[15] Kennedy, C.A., Carpenter, M.H.: Diagonally implicit Runge-Kutta methods for ordinary differential equations. A review. NASA report TM-2016-219173 (2016)
[16] Knoll, DA; Keyes, DE, Jacobian-free Newton-Krylov methods: a survey of approaches and applications, J. Comput. Phys., 193, 2, 357-397 (2004) · Zbl 1036.65045 · doi:10.1016/j.jcp.2003.08.010
[17] Kværnø, A., Singly diagonally implicit Runge-Kutta methods with an explicit first stage, BIT Numer. Math., 44, 3, 489-502 (2004) · Zbl 1066.65077 · doi:10.1023/B:BITN.0000046811.70614.38
[18] Lian, C.; Xia, G.; Merkle, CL, Solution-limited time stepping to enhance reliability in CFD applications, J. Comput. Phys., 228, 4836-4857 (2009) · Zbl 1368.76042 · doi:10.1016/j.jcp.2009.03.040
[19] Meisrimel, P.; Birken, P., Goal oriented time adaptivity using local error estimates, Algorithms, 13, 5, 113 (2020) · doi:10.3390/a13050113
[20] Mengaldo, G.: Discontinuous Spectral/\(hp\) Element Methods: Development, Analysis and Applications to Compressible Flows. PhD thesis, Imperial College London, UK (2015)
[21] Noventa, G.; Massa, F.; Bassi, F.; Colombo, A.; Franchina, N.; Ghidoni, A., A high-order discontinuous Galerkin solver for unsteady incompressible turbulent flows, Comput. Fluids, 139, 248-260 (2016) · Zbl 1390.76344 · doi:10.1016/j.compfluid.2016.03.007
[22] Noventa, G.; Massa, F.; Rebay, S.; Bassi, F.; Ghidoni, A., Robustness and efficiency of an implicit time-adaptive discontinuous Galerkin solver for unsteady flows, Comput. Fluids, 204, 104529 (2020) · Zbl 1519.76155 · doi:10.1016/j.compfluid.2020.104529
[23] Parnaudeau, P.; Carlier, J.; Heitz, D.; Lamballais, E., Experimental and numerical studies of the flow over a circular cylinder at Reynolds number 3900, Fluids, 20, 8, 085101 (2008) · Zbl 1182.76591 · doi:10.1063/1.2957018
[24] Söderlind, G., Automatic control and adaptive time-stepping, Numer. Algorithms, 31, 1, 281-310 (2002) · Zbl 1012.65080 · doi:10.1023/A:1021160023092
[25] Söderlind, G.; Wang, L., Adaptive time-stepping and computational stability, J. Comput. Appl. Math., 185, 2, 225-243 (2006) · Zbl 1077.65086 · doi:10.1016/j.cam.2005.03.008
[26] Toro, EF, Riemann Solvers and Numerical Methods for Fluid Dynamics (2009), Berlin: Springer, Berlin · Zbl 1227.76006 · doi:10.1007/b79761
[27] Vandenhoeck, R.; Lani, A., Implicit high-order flux reconstruction solver for high-speed compressible flows, Comput. Phys. Commun., 242, 1-24 (2019) · Zbl 07674796 · doi:10.1016/j.cpc.2019.04.015
[28] Vanderstraeten, D.; Toro, EF, An expert system to control the CFL number of implicit upwind methods, Godunov Methods: Theory and Applications, 977-984 (2001), Boston: Springer, Boston · Zbl 1064.76602 · doi:10.1007/978-1-4615-0663-8_91
[29] Yan, Z-G; Pan, Y.; Castiglioni, G.; Hillewaert, K.; Peiró, J.; Moxey, D.; Sherwin, SJ, Nektar++: design and implementation of an implicit, spectral/hp element, compressible flow solver using a Jacobian-free Newton Krylov approach, Math. Appl, 81, 351-372 (2020) · Zbl 1456.76087
[30] Yildirim, A.; Kenway, GKW; Mader, CA; Martins, JRRA, A Jacobian-free approximate Newton-Krylov startup strategy for RANS simulations, J. Comput. Phys, 397, 108741 (2019) · Zbl 1453.76117 · doi:10.1016/j.jcp.2019.06.018
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.