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A Systematic Study on Weak Galerkin Finite Element Methods for Second Order Elliptic Problems

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Abstract

This article provides a systematic study for the weak Galerkin (WG) finite element method for second order elliptic problems by exploring polynomial approximations with various degrees for each local element. A typical local WG element is of the form \(P_k(T)\times P_j(\partial T)\Vert P_\ell (T)^2\), where \(k\ge 1\) is the degree of polynomials in the interior of the element T, \(j\ge 0\) is the degree of polynomials on the boundary of T, and \(\ell \ge 0\) is the degree of polynomials employed in the computation of weak gradients or weak first order partial derivatives. A general framework of stability and error estimate is developed for the corresponding numerical solutions. Numerical results are presented to confirm the theoretical results. The work reveals some previously undiscovered strengths of the WG method for second order elliptic problems, and the results are expected to be generalizable to other type of partial differential equations.

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References

  1. Arnold, D.N., Brezzi, F., Cockburn, B., Marini, L.D.: Discontinuous Galerkin methods for elliptic problems. Discontinuous Galerkin methods (Newport, RI, 1999), 89–101. Lecture notes in computational science and engineering. Springer, Berlin (2000)

    MATH  Google Scholar 

  2. Arnold, D.N., Brezzi, F., Cockburn, B., Marini, L.D.: Unified analysis of discontinuous Galerkin methods for elliptic problems. SIAM J. Numer. Anal. 39, 1749–1779 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  3. Beirão da Veiga, L., Brezzi, F., Cangiani, A., Manzini, G., Marini, L.D., Russo, A.: Basic principles of virtual element methods. Math. Models Methods Appl. Sci. 23, 199–214 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  4. Beirão da Veiga, L., Manzini, G.: A virtual element method with arbitrary regularity. IMA J. Numer. Anal. 34, 759–781 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  5. Brezzi, F., Marini, L.D.: Virtual element methods for plate bending problems. Comput. Methods Appl. Mech. Eng. 253, 455–462 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  6. Chen, L., Wang, J., Ye, X.: A posteriori error estimates for weak Galerkin finite element methods for second order elliptic problems. J. Sci. Comput. 59, 496–511 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  7. Ciarlet, P.G.: The Finite Element Method for Elliptic Problems. North-Holland, Amsterdam (1978)

    MATH  Google Scholar 

  8. Cockburn, B., Gopalakrishnan, J., Lazarov, R.: Unified hybridization of discontinuous Galerkin, mixed, and continuous Galerkin methods for second order elliptic problems. SIAM J. Numer. Anal. 47, 1319–1365 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  9. Di Pietro, D.A., Ern, A.: A hybrid high-order locking-free method for linear elasticity on general meshes. Comput. Methods Appl. Mech. Eng. 283, 1–21 (2015)

    Article  MathSciNet  Google Scholar 

  10. Gao, F., Mu, L.: On \(L^2\) error estimate for weak Galerkin finite element methods for parabolic problems. J. Comput. Math. 32, 195–204 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  11. Huang, W., Wang, Y.: Discrete maximum principle for the weak Galerkin method for anisotropic diffusion problems. Commun. Comput. Phys. 18, 65–90 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  12. Karakashian, O.A., Pascal, F.: A posterior error estimates for a discontinuous Galerkin approximation of second-order elliptic problems. SIAM J. Numer. Anal. 41, 2374–2399 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  13. Lehrenfeld, C.: Hybrid Discontinuous Galerkin methods for solving incompressible flow problems, Diploma Thesis, MathCCES/IGPM, RWTH Aachen. (2010)

  14. Li, B., Xie, X.: A two-level algorithm for the weak Galerkin discretization of diffusion problems. J. Comput. Appl. Math. 287, 179–195 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  15. Li, J., Wang, X., Zhang, K.: Multi-level Monte Carlo weak Galerkin method for elliptic equations with stochastic jump coefficients. Appl. Math. Comput. 275, 181–194 (2016)

    Article  MathSciNet  Google Scholar 

  16. Li, Q., Wang, J.: Weak Galerkin finite element methods for parabolic equations. Numer. Methods Partial Differ. Equ. 29, 2004–2024 (2013)

    MathSciNet  MATH  Google Scholar 

  17. Mu, L., Wang, J., Wang, Y., Ye, X.: A computational study of the weak Galerkin method for second-order elliptic equations. Numer. Algorithms 63, 753–777 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  18. Mu, L., Wang, J., Ye, X.: A stable numerical algorithm for the Brinkman equations by weak Galerkin finite element methods. J. Comput. Phys. 273, 327–342 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  19. Mu, L., Wang, J., Ye, X.: A new weak Galerkin finite element method for the Helmholtz equation. IMA J. Numer. Anal. 35, 1228–1255 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  20. Mu, L., Wang, J., Ye, X.: Weak Galerkin finite element methods on polytopal meshes. Int. J. Numer. Anal. Model. 12, 31–53 (2015)

    MathSciNet  MATH  Google Scholar 

  21. Mu, L., Wang, J., Ye, X.: A weak Galerkin finite element method with polynomial reduction. J. Comput. Appl. Math. 285, 45–58 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  22. Mu, L., Wang, J., Ye, X., Zhang, S.: A \(C^0\)-weak Galerkin finite element method for the biharmonic equation. J. Sci. Comput. 59, 473–495 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  23. Mu, L., Wang, J., Ye, X., Zhang, S.: A weak Galerkin finite element method for the Maxwell equations. J. Sci. Comput. 65, 363–386 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  24. Mu, L., Wang, J., Ye, X., Zhao, S.: A numerical study on the weak Galerkin method for the Helmholtz equation. Commun. Comput. Phys. 15, 1461–1479 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  25. Wang, C., Wang, J.: An efficient numerical scheme for the biharmonic equation by weak Galerkin finite element methods on polygonal or polyhedral meshes. Comput. Math. Appl. 68, 2314–2330 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  26. Wang, C., Wang, J.: A primal-dual weak Galerkin finite element method for second order elliptic equations in non-divergence form. Math. Comp. (2017). doi:10.1090/mcom/3220

  27. Wang, J., Ye, X.: A weak Galerkin finite element method for second-order elliptic problems. J. Comput. Appl. Math. 241, 103–115 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  28. Wang, J., Ye, X.: A weak Galerkin mixed finite element method for second order elliptic problems. Math. Comp. 83, 2101–2126 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  29. Wang, J., Ye, X.: A weak Galerkin finite element method for the Stokes equations. Adv. Comput. Math. 42, 155–174 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  30. Wang, R., Wang, X., Zhai, Q., Zhang, R.: A weak Galerkin finite element scheme for solving the stationary Stokes equations. J. Comput. Appl. Math. 302, 171–185 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  31. Wang, X., Zhai, Q., Zhang, R.: The weak Galerkin method for solving the incompressible Brinkman flow. J. Comput. Appl. Math. 307, 13–24 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  32. Zhai, Q., Zhang, R., Mu, L.: A new weak Galerkin finite element scheme for the Brinkman model. Commun. Comput. Phys. 19, 1409–1434 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  33. Zhang, R., Zhai, Q.: A weak Galerkin finite element scheme for the biharmonic equations by using polynomials of reduced order. J. Sci. Comput. 64, 559–585 (2015)

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Ran Zhang.

Additional information

J. Wang: The research of Wang was supported by the NSF IR/D program, while working at National Science Foundation. However, any opinion, finding, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

R. Zhang: The research of this author was supported in part by China Natural National Science Foundation (U1530116, 91630201, 11471141, J1310022), and by the Program for Cheung Kong Scholars of Ministry of Education of China, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130012, P.R. China.

Appendix

Appendix

In this section we present some detailed computational data for a set of selected values of \(k,\ j\), and \(\ell \). These data shall be in support of the order of convergence reported in Sect. 5. The numerical results are organized as follows. Tables 9, 10, 11, 12, 13, and 14 illustrate the table index number for the set value of \((k,j,\ell )\), and the rest of the tables show the corresponding numerical results. For example, Table 9 points to the table index number when the stabilizer \(j_\partial (v) = Q_b^m(v_0-v_b)\) was employed in the numerical scheme. This table has a fixed value of \(k=2\) while j and \(\ell \) are varying. The entry of the table at \((k,j,\ell )=(2,1,2)\) has value (Table 17) so that the computational results for \((k,j,\ell )=(2,1,2)\) should be found in Table 17.

1.1 Index Tables

The index tables are given in Tables 9, 10, 11, 12, 13, and 14. Please be reminded that the values in those tables refer to the table number where the computational results are reported.

Table 9 Table index for \(j_\partial (v) = Q_b^m(v_0-v_b)\) with \(k=2\)
Table 10 Table index for \(j_\partial (v) = Q_b^m(v_0-v_b)\) with \(k=3\)
Table 11 Table index for \(j_\partial (v) = Q_b^m(v_0-v_b)\) with \(k=4\)
Table 12 Table index for \(j_\partial (v) = v_0-v_b\) with \(k=2\)
Table 13 Table Index for \(j_\partial (v) = v_0-v_b\) with \(k=3\)
Table 14 Table index for \(j_\partial (v) = v_0-v_b\) with \(k=4\)

1.2 Tables for Computational Results

All the detailed computational results are presented in Tables 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, and 42. No interpretation of the data is necessary as they are virtually self-explanatory. Interested readers are invited to draw their own conclusions from reading these numerical results.

Table 15 Convergence orders for \(k=2\), \(j=0\), \(\ell =1\)
Table 16 Convergence orders for \(k=2\), \(j=1\), \(\ell =1\)
Table 17 Convergence orders for \(k=2\), \(j=1\), \(\ell =2\)
Table 18 Convergence orders for \(k=2\), \(j=2\), \(\ell =2\)
Table 19 Convergence orders for \(k=2\), \(j=3\), \(\ell =3\)
Table 20 Convergence orders for \(k=2\), \(j=4\), \(\ell =4\)
Table 21 Convergence orders for \(k=3\), \(j=1\), \(\ell =2\)
Table 22 Convergence orders for \(k=3\), \(j=2\), \(\ell =2\)
Table 23 Convergence orders for \(k=3\), \(j=2\), \(\ell =3\)
Table 24 Convergence orders for \(k=3\), \(j=3\), \(\ell =3\)
Table 25 Convergence orders for \(k=3\), \(j=4\), \(\ell =4\)
Table 26 Convergence orders for \(k=4\), \(j=1\), \(\ell =3\)
Table 27 Convergence orders for \(k=4\), \(j=2\), \(\ell =3\)
Table 28 Convergence orders for \(k=4\), \(j=3\), \(\ell =3\)
Table 29 Convergence orders for \(k=4\), \(j=3\), \(\ell =4\)
Table 30 Convergence orders for \(k=4\), \(j=4\), \(\ell =4\)
Table 31 Convergence orders for \(k=2\), \(j=1\), \(\ell =1\)
Table 32 Convergence orders for \(k=2\), \(j=2\), \(\ell =2\)
Table 33 Convergence orders for \(k=2\), \(j=3\), \(\ell =3\)
Table 34 Convergence orders for \(k=2\), \(j=4\), \(\ell =4\)
Table 35 Convergence orders for \(k=3\), \(j=1\), \(\ell =1\)
Table 36 Convergence orders for \(k=3\), \(j=2\), \(\ell =2\)
Table 37 Convergence orders for \(k=3\), \(j=3\), \(\ell =3\)
Table 38 Convergence orders for \(k=3\), \(j=4\), \(\ell =4\)
Table 39 Convergence orders for \(k=4\), \(j=1\), \(\ell =2\)
Table 40 Convergence orders for \(k=4\), \(j=2\), \(\ell =2\)
Table 41 Convergence orders for \(k=4\), \(j=3\), \(\ell =3\)
Table 42 Convergence orders for \(k=4\), \(j=4\), \(\ell =4\)

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Wang, J., Wang, R., Zhai, Q. et al. A Systematic Study on Weak Galerkin Finite Element Methods for Second Order Elliptic Problems. J Sci Comput 74, 1369–1396 (2018). https://doi.org/10.1007/s10915-017-0496-6

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