Abstract
In this article, we study superconvergence of the finite element approximation to the solution of a general secondorder elliptic boundary value problem in three dimensions over a fully uniform mesh of piecewise tensorproduct linear triangular prism elements. First, we give the superclose property of the gradient between the finite element solution and the interpolant Πu. Second, we introduce a superconvergence recovery scheme for the gradient of the finite element solution. Finally, superconvergence of the recovered gradient is derived.
Keywords:
superconvergence patch recovery; superclose property; triangular prism element1 Introduction
Superconvergence of the gradient for the finite element approximation is a phenomenon whereby the convergent order of the derivatives of the finite element solutions exceeds the optimal global rate. Up to now, superconvergence is still an active research topic (see [16]). Recently, we studied the superconvergence patch recovery (SPR) technique introduced by Zienkiewicz and Zhu [79] for the linear tetrahedral element and proved pointwise superconvergent property of the recovered gradient by SPR. For the linear tetrahedral element, Chen and Wang [10] also discussed superconvergent properties of the gradients by SPR and obtained superconvergence results of the recovered gradients in the average sense of the norm. In addition, Chen [11] and Goodsell [12] derived superconvergence estimates of the recovered gradient by the projection technique and the average technique, respectively. This article will use the SPR technique to obtain a superconvergence estimate for the gradient of the tensorproduct linear triangular prism element. In this article, we shall use the letter C to denote a generic constant which may not be the same in each occurrence and also use the standard notations for the Sobolev spaces and their norms.
2 General elliptic boundary value problem and finite element discretization
We consider the model problem
Here is a rectangular block with boundary ∂Ω consisting of faces parallel to the x, y, and zaxes. We also assume that the given functions , , and . In addition, we write , , and , which are usual partial derivatives.
To discretize the problem, one proceeds as follows. The domain Ω is firstly partitioned into subcubes of side h, and each of these is then subdivided into two triangular prisms. We denote by these uniform partitions as above. Thus . Obviously, we can write (see Figure 1), where D and L represent a triangle parallel to the xyplane and a onedimensional interval parallel to the zaxes, respectively.
Figure 1. Triangular prisms partition. This figure gives how to partition the domain Ω. The domain Ω is firstly partitioned into subcubes of side h, and each of these is then subdivided into two triangular prisms.
We introduce a tensorproduct linear polynomial space denoted by , that is,
where , stands for the linear polynomial space with respect to , and is the linear polynomial space with respect to z. The indexing set ℐ satisfies . Let be the linear interpolation operator with respect to , and let be the linear interpolation operator with respect to . Thus we may define the tensorproduct linear interpolation operator by . Obviously, . In addition, the weak form of problem (2.1) is
where
and
Define the tensorproduct linear triangular prism finite element space by
Thus, the finite element method of problem (2.2) is to find such that
Moreover, from the definitions of and , we may define a global tensorproduct linear interpolation operator . Here . As for this interpolation operator, the following Lemma 2.1 holds (see [13]).
Lemma 2.1For Πuand, the tensorproduct linear interpolant and the tensorproduct linear triangular prism finite element approximation tou, respectively, we have the supercloseness estimate
3 Gradient recovery and superconvergence
For , we consider a SPR scheme of ∇v. We denote by the SPRrecovery operator for ∇v and begin by defining the point values of at the element nodes. After the recovered values at all nodes are obtained, we construct a tensorproduct linear interpolation by using these values, namely SPRrecovery gradient . Obviously, .
Let us first assume that N is an interior node of the partition , and denote by ω the element patch around N containing 12 triangular prisms. Under the local coordinate system centered N, we let be the barycenter of a triangular prism , . Obviously, . SPR uses the discrete leastsquares fitting to seek linear vector function such that
where . We define . If N is a boundary node, we calculate by linear extrapolation from the values of already obtained at two neighboring interior nodes, and (with diagonal directions being used for edge nodes and corner nodes) (see Figure 2). Namely,
Figure 2. N, a boundary node. and are interior nodes. We can calculate by linear extrapolation from the values of already obtained at two neighboring interior nodes, and .
Lemma 3.1Letωbe the element patch around an interior nodeN, and. Forthe interpolant tou, we have
Proof Choose and set in (3.1) to obtain . Therefore,
That is,
Further,
where , and the highorder term satisfies .
In (3.4), we write . For every , it is not difficult to verify . Thus, by the BrambleHilbert lemma [14], we have . Therefore,
Combining (3.3) and (3.5), we obtain the result (3.2). □
Lemma 3.2Forthe tensorproduct linear interpolant tou, the solution of (2.2), andthe SPR recovery operator, we have the superconvergent estimate
Proof Denote by an affine transformation. Obviously, there exists an element , using the triangle inequality and the Sobolev embedding theorem [15], and (3.3), such that
where is a small patch of elements surrounding the triangular prism, . Due to the fact that for quadratic over ,
so, from the BrambleHilbert lemma [14],
which completes the proof of the result (3.6). Finally, we give the main result in this article. □
Theorem 3.1Forthe tensorproduct linear triangular prism finite element approximation tou, the solution of (2.2), andthe SPR recovery operator, we have the superconvergence estimate
Proof Using the triangle inequality, we have
which combined with (2.3) and (3.6) completes the proof of the result (3.7). □
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
The first author gave the idea of this article and the methods of proving the main results. He also proved Lemmas 3.1 and 3.2. The second author provided the proof of Theorem 3.1 and the correction of the English language.
Acknowledgements
This work is supported by the National Natural Science Foundation of China Grant 11161039, the Zhejiang Provincial Natural Science Foundation of China Grant LY13A010007, and the Natural Science Foundation of Ningbo City Grant 2013A610104.
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