Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter July 28, 2017

A Two-Level Sparse Grid Collocation Method for Semilinear Stochastic Elliptic Equation

  • Luoping Chen , Yanping Chen EMAIL logo and Xiong Liu

Abstract

In this work, we investigate a novel two-level discretization method for the elliptic equations with random input data. Motivated by the two-grid method for deterministic nonlinear partial differential equations introduced by Xu [36], our two-level discretization method uses a two-grid finite element method in the physical space and a two-scale stochastic collocation method with sparse grid in the random domain. Specifically, we solve a semilinear equations on a coarse mesh 𝒯H(D) with small scale of sparse collocation points η(L,N) and solve a linearized equations on a fine mesh 𝒯h(D) using large scale of sparse collocation points η(,N) (where η(L,N),η(,N) are the numbers of sparse grid with respect to different levels L, in N dimensions). Moreover, an error correction on the coarse mesh with large scale of collocation points is used in the method. Theoretical results show that when hH3,η(,N)(η(L,N))3, the novel two-level discretization method achieves the same convergence accuracy in norm ρ2(Γ)2(D) (ρ2(Γ) is the weighted 2 space with ρ a probability density function) as that for the original semilinear problem directly by sparse grid stochastic collocation method with 𝒯h(D) and large scale collocation points η(,N) in random spaces.

MSC 2010: 65M10; 78A48

Funding statement: Luoping Chen is supported by the National Natural Science Foundation of China (No. 11501473) and the Fundamental Research Funds for the Central Universities of China (No. 2682016CX108). Yanping Chen is supported National Natural Science Foundation of China (No. 11671157 and No. 91430104). Xiong Liu is supported by Lingnan Normal University general project (No. 2014YL1408).

References

[1] G. Adomian, Nonlinear Stochastic Systems: Theory and Application to Physics, Springer, Netherlands, 1989. 10.1007/978-94-009-2569-4Search in Google Scholar

[2] A. Ammi and M. Marion, Nonlinear Galerkin methods and mixed finite elements: Two-grid algorithms for the Navier–Stokes equations, Numer. Math. 68 (1994), no. 2, 189–213. 10.1007/s002110050056Search in Google Scholar

[3] I. Babuška, F. Nobile and R. Tempone, A stochastic collocation method for elliptic partial differential equations with random input data, SIAM Rev. 52 (2010), no. 2, 317–355. 10.1137/100786356Search in Google Scholar

[4] I. Babuška, R. Tempone and G. Zouraris, Galerkin finite element approximations of stochastic elliptic partial differential equations, SIAM J. Numer. Anal. 42 (2004), no. 2, 800–825. 10.1137/S0036142902418680Search in Google Scholar

[5] V. Barthelmann, E. Novak and K. Ritter, High dimensional polynomial interpolation on sparse grids, Adv. Comput. Math. 12 (2000), no. 4, 273–288. 10.1023/A:1018977404843Search in Google Scholar

[6] N. Bellomo and R. Riganti, Nonlinear Stochastic Systems in Physics and Mechanics, World Scientific, Singapore, 1987. 10.1142/0387Search in Google Scholar

[7] R. Caflisch, Monte Carlo and quasi-Monte Carlo methods, Acta Numer. 7 (1998), 1–49. 10.1017/S0962492900002804Search in Google Scholar

[8] Y. Chen, Y. Huang and D. Yu, A two-grid method for expanded mixed finite-element solution of semilinear reaction–diffusion equations, Int. J. Numer. Meth. Eng. 57 (2003), no. 2, 193–209. 10.1002/nme.668Search in Google Scholar

[9] Y. Chen, H. Liu and S. Liu, Analysis of two-grid methods for reaction-diffusion equations by expanded mixed finite element methods, Int. J. Numer. Meth. Eng. 69 (2007), no. 2, 408–422. 10.1002/nme.1775Search in Google Scholar

[10] C. Chien and B. Jeng, A two-grid discretization scheme for semilinear elliptic eigenvalue problems, SIAM J. Sci. Comput. 27 (2006), no. 4, 1287–1304. 10.1137/030602447Search in Google Scholar

[11] C. Dawson and M. Wheeler, Two-grid methods for mixed finite element approximations of nonlinear parabolic equations, Contemp. Math. 180 (1994), 191–191. 10.1090/conm/180/01971Search in Google Scholar

[12] C. Dawson, M. Wheeler and C. Woodward, A two-grid finite difference scheme for nonlinear parabolic equations, SIAM J. Numer. Anal. 35 (1998), no. 2, 435–452. 10.1137/S0036142995293493Search in Google Scholar

[13] T. Gerstner and M. Griebel, Numerical integration using sparse grids, Numer. Algorithms 18 (1998), no. 3, 209. 10.1023/A:1019129717644Search in Google Scholar

[14] R. Ghanem and P. Spanos, Stochastic Finite Elements: A Spectral Approach, Springer, New York, 1991. 10.1007/978-1-4612-3094-6Search in Google Scholar

[15] V. Girault and J. Lions, Two-grid finite-element schemes for the steady Navier–Stokes problem in polyhedra, Port. Math. 58 (2001), no. 1, 25–58. Search in Google Scholar

[16] S. Hosder, R. Walters and R. Perez, A non-intrusive polynomial chaos method for uncertainty propagation in CFD simulations, Proceedings of the 44th AIAA Aerospace Sciences Meeting and Exibit (Reno 2006), AIAA, Reston (2006), 1–19. 10.2514/6.2006-891Search in Google Scholar

[17] A. Klimke, Sparse grid interpolation toolbox – User’s guide, IANS Report 2007/017, University of Stuttgart, 2007. Search in Google Scholar

[18] O. Knio, H. Najm and R. Ghanem, A stochastic projection method for fluid flow: I. Basic formulation, J. Comput. Phys. 173 (2001), no. 2, 481–511. 10.1006/jcph.2001.6889Search in Google Scholar

[19] W. Layton and W. Lenferink, Two-level Picard and modified Picard methods for the Navier–Stokes equations, Appl. Math. Comput. 69 (1995), no. 2, 263–274. 10.1016/0096-3003(94)00134-PSearch in Google Scholar

[20] W. Layton, A. Meir and P. Schmidt, A two-level discretization method for the stationary MHD equations, Electron. Trans. Numer. Anal. 6 (1997), 198–210. Search in Google Scholar

[21] W. Layton and L. Tobiska, A two-level method with backtracking for the Navier–Stokes equations, SIAM J. Numer. Anal. 35 (1998), no. 5, 2035–2054. 10.1137/S003614299630230XSearch in Google Scholar

[22] O. Le Maître, M. Reagan, H. Najm, R. Ghanem and O. Knio, A stochastic projection method for fluid flow: II. Random process, J. Comput. Phys. 181 (2002), no. 1, 9–44. 10.1006/jcph.2002.7104Search in Google Scholar

[23] X. Ma and N. Zabaras, An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations, J. Comput. Phys. 228 (2009), no. 8, 3084–3113. 10.1016/j.jcp.2009.01.006Search in Google Scholar

[24] X. Ma and N. Zabaras, A stochastic mixed finite element heterogeneous multiscale method for flow in porous media, J. Comput. Phys. 230 (2011), no. 12, 4696–4722. 10.1016/j.jcp.2011.03.001Search in Google Scholar

[25] H. Matthies and A. Keese, Galerkin methods for linear and nonlinear elliptic stochastic partial differential equations, Comput. Methods Appl. Math. 194 (2005), no. 12, 1295–1331. 10.1016/j.cma.2004.05.027Search in Google Scholar

[26] H. Najm, Uncertainty quantification and polynomial chaos techniques in computational fluid dynamics, Annu. Rev. Fluid Mech. 41 (2009), 35–52. 10.1146/annurev.fluid.010908.165248Search in Google Scholar

[27] F. Nobile, R. Tempone and C. G. Webster, A sparse grid stochastic collocation method for partial differential equations with random input data, SIAM J. Numer. Anal 46 (2008), no. 5, 2309–2345. 10.1137/060663660Search in Google Scholar

[28] B. Øksendal, Stochastic Differential Equations: An Introduction with Applications, Springer, New York, 2003. 10.1007/978-3-642-14394-6Search in Google Scholar

[29] M. Shinozuka and Y. Wen, Monte Carlo solution of nonlinear vibrations, AIAA J. 10 (1972), no. 1, 37–40. 10.2514/6.1971-213Search in Google Scholar

[30] S. A. Smoljak, Quadrature and interpolation formulae on tensor products of certain function classes, Dokl. Akad. Nauk 4 (1963), no. 5, 240–243. Search in Google Scholar

[31] T. Utnes, Two-grid finite element formulations of the incompressible Navier–Stokes equations, Commun. Numer. Meth. Eng. 13 (1997), no. 8, 675–684. 10.1002/(SICI)1099-0887(199708)13:8<675::AID-CNM98>3.0.CO;2-NSearch in Google Scholar

[32] D. Xiu and J. Hesthaven, High-order collocation methods for differential equations with random inputs, SIAM J. Sci. Comput. 27 (2005), no. 3, 1118–1139. 10.1137/040615201Search in Google Scholar

[33] D. Xiu and G. Karniadakis, The Wiener–Askey polynomial chaos for stochastic differential equations, SIAM J. Sci. Comput. 24 (2002), no. 2, 619–644. 10.21236/ADA460654Search in Google Scholar

[34] D. Xiu and G. Karniadakis, Modeling uncertainty in flow simulations via generalized polynomial chaos, J. Comput. Phys. 187 (2003), no. 1, 137–167. 10.21236/ADA461813Search in Google Scholar

[35] D. Xiu, D. Lucor, C. Su and G. Karniadakis, Stochastic modeling of flow-structure interactions using generalized polynomial chaos, ASME J. Fluid Engrg. 124 (2002), no. 1, 51–69. 10.21236/ADA461832Search in Google Scholar

[36] J. Xu, A novel two-grid method for semilinear elliptic equations, SIAM J. Sci. Comput. 15 (1994), no. 1, 231–237. 10.1137/0915016Search in Google Scholar

[37] J. Xu, Two-grid discretization techniques for linear and nonlinear PDEs, SIAM J. Numer. Anal. 33 (1996), no. 5, 1759–1777. 10.1137/S0036142992232949Search in Google Scholar

[38] J. Xu and A. Zhou, A two-grid discretization scheme for eigenvalue problems, Math. Comp. 70 (2001), no. 233, 17–25. 10.1090/S0025-5718-99-01180-1Search in Google Scholar

[39] W. Yao and T. Lu, Numerical comparison of three stochastic methods for nonlinear PN junction problems, Front. Math. China 9 (2014), no. 3, 659–698. 10.1007/s11464-013-0327-5Search in Google Scholar

[40] Q. Zhang, Z. Li and Z. Zhang, A sparse grid stochastic collocation method for elliptic interface problems with random input, J. Sci. Comput. 67 (2016), no. 1, 262–280. 10.1007/s10915-015-0080-xSearch in Google Scholar

Received: 2017-4-19
Revised: 2017-5-22
Accepted: 2017-6-7
Published Online: 2017-7-28
Published in Print: 2018-4-1

© 2018 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 21.5.2024 from https://www.degruyter.com/document/doi/10.1515/cmam-2017-0025/html
Scroll to top button