Superconvergence Analysis of $C^m$ Finite Element Methods for Fourth-Order Elliptic Equations I: One Dimensional Case
Year: 2023
Author: Waixiang Cao, Lueling Jia, Zhimin Zhang
Communications in Computational Physics, Vol. 33 (2023), Iss. 5 : pp. 1466–1508
Abstract
In this paper, we study three families of $C^m (m=0,1,2)$ finite element methods for one dimensional fourth-order equations. They include $C^0$ and $C^1$ Galerkin methods and a $C^2-C^0$ Petrov-Galerkin method. Existence, uniqueness and optimal error estimates of the numerical solution are established. A unified approach is proposed to study the superconvergence property of these methods. We prove that, for $k$th-order elements, the $C^0$ and $C^1$ finite element solutions and their derivative are superconvergent with rate $h^{2k−2} (k≥3)$ at all mesh nodes; while the solution of the $C^2-C^0$ Petrov-Galerkin method and its first- and second-order derivatives are superconvergent with rate $h^{2k−4} (k≥5)$ at all mesh nodes. Furthermore, interior superconvergence points for the $l$-${\rm th} (0≤l≤m+1)$ derivate approximations are also discovered, which are identified as roots of special Jacobi polynomials, Lobatto points, and Gauss points. As a by-product, we prove that the $C^m$ finite element solution is superconvergent towards a particular Jacobi projection of the exact solution in the $H^l (0≤ l ≤ m+1)$ norms. All theoretical findings are confirmed by numerical experiments.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/cicp.OA-2022-0311
Communications in Computational Physics, Vol. 33 (2023), Iss. 5 : pp. 1466–1508
Published online: 2023-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 43
Keywords: $C^m$ finite element methods superconvergence fourth-order elliptic equations.
Author Details
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Superconvergence Analysis of a Robust Orthogonal Gauss Collocation Method for 2D Fourth-Order Subdiffusion Equations
Yang, Xuehua
Zhang, Zhimin
Journal of Scientific Computing, Vol. 100 (2024), Iss. 3
https://doi.org/10.1007/s10915-024-02616-z [Citations: 3]