ORIGINAL PAPER

How to Design a Generic Accuracy-Enhancing Filter for Discontinuous Galerkin Methods

Expand
  • School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China

Received date: 2020-08-30

  Revised date: 2021-04-26

  Online published: 2022-07-04

Supported by

The authors would like to thank the reviewers for their helpful comments and suggestions in the revision of this manuscript.

Abstract

Higher order accuracy is one of the well-known beneficial properties of the discontinuous Galerkin (DG) method. Furthermore, many studies have demonstrated the superconvergence property of the semi-discrete DG method. One can take advantage of this superconvergence property by post-processing techniques to enhance the accuracy of the DG solution. The smoothness-increasing accuracy-conserving (SIAC) filter is a popular post-processing technique introduced by Cockburn et al. (Math. Comput. 72(242): 577–606, 2003). It can raise the convergence rate of the DG solution (with a polynomial of degree k) from order $ k+1 $ to order $2k+1$ in the $ L^2 $ norm. This paper first investigates general basis functions used to construct the SIAC filter for superconvergence extraction. The generic basis function framework relaxes the SIAC filter structure and provides flexibility for more intricate features, such as extra smoothness. Second, we study the distribution of the basis functions and propose a new SIAC filter called compact SIAC filter that significantly reduces the support size of the original SIAC filter while preserving (or even improving) its ability to enhance the accuracy of the DG solution. We prove the superconvergence error estimate of the new SIAC filters. Numerical results are presented to confirm the theoretical results and demonstrate the performance of the new SIAC filters.

Cite this article

Xiaozhou Li . How to Design a Generic Accuracy-Enhancing Filter for Discontinuous Galerkin Methods[J]. Communications on Applied Mathematics and Computation, 2022 , 4(3) : 759 -782 . DOI: 10.1007/s42967-021-00144-3

References

[1] Asthana, K., López-Morales, M.R., Jameson, A.: Non-linear stabilization of high-order flux reconstruction schemes via Fourier-spectral filtering. J. Comput. Phys. 303, 269–294 (2015)
[2] Bohm, M., Schermeng, S., Winters, A.R., Gassner, G.J., Jacobs, G.B.: Multi-element SIAC filter for shock capturing applied to high-order discontinuous Galerkin spectral element methods. J. Sci. Comput. 81(2), 820–844 (2019)
[3] Bramble, J.H., Schatz, A.H.: Higher order local accuracy by averaging in the finite element method. Math. Comput. 31(137), 94–111 (1977)
[4] Cockburn, B., Hou, S., Shu, C.-W.: The Runge-Kutta local projection discontinuous Galerkin finite element method for conservation laws. IV. The multidimensional case. Math. Comput. 54(190), 545–581 (1990)
[5] Cockburn, B., Lin, S.Y., Shu, C.-W.: TVB Runge-Kutta local projection discontinuous Galerkin finite element method for conservation laws. III. One-dimensional systems. J. Comput. Phys. 84(1), 90–113 (1989)
[6] Cockburn, B., Luskin, M., Shu, C.-W., Süli, E.: Enhanced accuracy by post-processing for finite element methods for hyperbolic equations. Math. Comput. 72(242), 577–606 (2003)
[7] Cockburn, B., Shu, C.-W.: TVB Runge-Kutta local projection discontinuous Galerkin finite element method for conservation laws. II. General framework. Math. Comput. 52(186), 411–435 (1989)
[8] Cockburn, B., Shu, C.-W.: The Runge-Kutta local projection \begin{document}$ P^1 $\end{document}-discontinuous-Galerkin finite element method for scalar conservation laws. RAIRO Modél. Math. Anal. Numér. 25(3), 337–361 (1991)
[9] Curtis, S., Kirby, R.M., Ryan, J.K., Shu, C.-W.: Postprocessing for the discontinuous Galerkin method over nonuniform meshes. SIAM J. Sci. Comput. 30(1), 272–289 (2007)
[10] Docampo-Sánchez, J., Jacobs, G.B., Li, X., Ryan, J.K.: Enhancing accuracy with a convolution filter: what works and why!. Comput. Fluids 213, 104727 (2020)
[11] Docampo-Sánchez, J., Ryan, J.K., Mirzargar, M., Kirby, R.M.: Multi-dimensional filtering: reducing the dimension through rotation. SIAM J. Sci. Comput. 39(5), A2179–A2200 (2017)
[12] Edoh, A.K., Mundis, N.L., Merkle, C.L., Karagozian, A.R., Sankaran, V.: Comparison of artificial-dissipation and solution-filtering stabilization schemes for time-accurate simulations. J. Comput. Phys. 375, 1424–1450 (2018)
[13] Jallepalli, A., Docampo-Sanchez, J., Ryan, J.K., Haimes, R., Kirby, R.M.: On the treatment of field quantities and elemental continuity in fem solutions. IEEE Trans. Vis. Comput. Graph. 24(1), 903–912 (2018)
[14] Jallepalli, A., Haimes, R., Kirby, R.M.: Adaptive characteristic length for L-SIAC filtering of FEM data. J. Sci. Comput. 79(1), 542–563 (2019)
[15] Ji, L., Ryan, J.K.: Smoothness-increasing accuracy-conserving (SIAC) filters in Fourier space. In: Spectral and High Order Methods for Partial Differential Equations—ICOSAHOM 2014, Lecture Notes in Computational Science and Engineering, vol. 106, pp. 415–423. Springer, Cham (2015)
[16] King, J., Mirzaee, H., Ryan, J.K., Kirby, R.M.: Smoothness-increasing accuracy-conserving (SIAC) filtering for discontinuous Galerkin solutions: improved errors versus higher-order accuracy. J. Sci. Comput. 53(1), 129–149 (2012)
[17] Li, X., Ryan, J.K.: SIAC filtering for nonlinear hyperbolic equations. In: Interdisciplinary Topics in Applied Mathematics. Modeling and Computational Science, pp. 285–291. Springer International Publishing, Cham (2015)
[18] Li, X., Ryan, J.K., Kirby, R.M., Vuik, C.: Smoothness-increasing accuracy-conserving (SIAC) filters for derivative approximations of discontinuous Galerkin (DG) solutions over nonuniform meshes and near boundaries. J. Comput. Appl. Math. 294, 275–296 (2016)
[19] Li, X., Ryan, J.K., Kirby, R.M., Vuik, K.: Smoothness-increasing accuracy-conserving (SIAC) filtering for discontinuous Galerkin solutions over nonuniform meshes: superconvergence and optimal accuracy. J. Sci. Comput. 81(3), 1150–1180 (2019)
[20] Mirzaee, H., Ryan, J.K., Kirby, R.M.: Quantification of errors introduced in the numerical approximation and implementation of smoothness-increasing accuracy conserving (SIAC) filtering of discontinuous Galerkin (DG) fields. J. Sci. Comput. 45(1/2/3), 447–470 (2010)
[21] Mirzaee, H., Ryan, J.K., Kirby, R.M.: Efficient implementation of smoothness-increasing accuracy-conserving (SIAC) filters for discontinuous Galerkin solutions. J. Sci. Comput. 52(1), 85–112 (2012)
[22] Mirzargar, M., Jallepalli, A., Ryan, J.K., Kirby, R.M.: Hexagonal smoothness-increasing accuracy-conserving filtering. J. Sci. Comput. 73(2/3), 1072–1093 (2017)
[23] Reed, W., Hill, T.: Triangular mesh methods for the neutron transport equation. Los Alamos Report LA-UR-73-479. Los Alamos Scientific Laboratory, Los Alamos, NM (1973)
[24] Ryan, J.K., Cockburn, B.: Local derivative post-processing for the discontinuous Galerkin method. J. Comput. Phys. 228(23), 8642–8664 (2009)
[25] Ryan, J.K., Docampo-Sanchez, J.: One-dimensional line SIAC filtering for multi-dimensions: applications to streamline visualization. In: van Brummelen, H., Corsini, A., Perotto, S., Rozza, G. (eds) Numerical Methods for Flows: FEF 2017 Selected Contributions, pp. 145–154. Springer International Publishing, Cham (2020)
[26] Ryan, J.K., Li, X., Kirby, R.M., Vuik, K.: One-sided position-dependent smoothness-increasing accuracy-conserving (SIAC) filtering over uniform and non-uniform meshes. J. Sci. Comput. 64(3), 773–817 (2015)
[27] Ryan, J.K., Shu, C.-W., Atkins, H.: Extension of a postprocessing technique for the discontinuous Galerkin method for hyperbolic equations with application to an aeroacoustic problem. SIAM J. Sci. Comput. 26(3), 821–843 (2005)
[28] Van Slingerland, P., Ryan, J.K., Vuik, C.: Position-dependent smoothness-increasing accuracy-conserving (SIAC) filtering for improving discontinuous Galerkin solutions. SIAM J. Sci. Comput. 33(2), 802–825 (2011)
[29] Steffen, M., Curtis, S., Kirby, R.M., Ryan, J.K.: Investigation of smoothness-increasing accuracy-conserving filters for improving streamline integration through discontinuous fields. Vis. Comput. Graph. IEEE Trans. 14(3), 680–692 (2008)
[30] Vandeven, H.: Family of spectral filters for discontinuous problems. J. Sci. Comput. 6(2), 159–192 (1991)
[31] Walfisch, D., Ryan, J.K., Kirby, R.M., Haimes, R.: One-sided smoothness-increasing accuracy-conserving filtering for enhanced streamline integration through discontinuous fields. J. Sci. Comput. 38(2), 164–184 (2009)
[32] Wissink, B.W., Jacobs, G.B., Ryan, J.K., Don, W.S., van der Weide, E.T.A.: Shock regularization with smoothness-increasing accuracy-conserving Dirac-delta polynomial kernels. J. Sci. Comput. 77(1), 579–596 (2018)
[33] Zhang, Z., Naga, A.: A new finite element gradient recovery method: superconvergence property. SIAM J. Sci. Comput. 26(4), 1192–1213 (2005)
[34] Zhang, Z., Zhu, J.: Analysis of the superconvergent patch recovery technique and a posteriori error estimator in the finite element method. I. Comput. Methods Appl. Mech. Eng. 123(1/2/3/4), 173–187 (1995)
[35] Zhang, Z., Zhu, J.Z.: Analysis of the superconvergent patch recovery technique and a posteriori error estimator in the finite element method. II. Comput. Methods Appl. Mech. Eng. 163(1/2/3/4), 159–170 (1998)
Options
Outlines

/