Numerical Experiments Using MATLAB: Superconvergence of Nonconforming Finite Element Approximation for Second-Order Elliptic Problems ()
1. Introduction
The conforming finite element method (CFEM) requires a strong continuity; hence it is
not easy to construct such finite elements for the complex partial differential equations. The nonconforming finite element method (NCFEM) is more appealing computationally due to better stability and flexibility properties compared to CFEM [1] [2] [3] . The superconvergence in the finite element method is a phenomenon in which the finite element approximation converges to the exact solution at a rate higher than the optimal order error estimate. Wang proposed and analyzed superconvergence of the conforming finite element method by L2-projections. The main idea behind the L2-projections is to project the finite element solution to another finite element space with a coarse mesh and a higher order of polynomials.
The objective of this paper is to establish a general superconvergence result for the nonconforming finite element approximations for second-order elliptic problems by L2-projection methods by applying the idea presented in Wang [4] .
This paper is organized as follows. In Section 2, we present a review for the non- conforming finite element method for the second-order elliptic problem. In Section 3, we develop a general theory of superconvergence by following the idea presented in Wang [4] . In Section 4, we perform numerical experiments to support the theoretical results. Numerical experiements of superconvergence of NCFEM are performed in MATLAB and its codes are posted at https://github.com/annaleeharris/Superconvergence-NCFEM for anyone to use and to study.
2. NCFEM for the Second-Order Elliptic Problem
Consider the second-order elliptic problem with the Dirichlet boundary condition which seeks
satisfying
(1)
where
is the Laplacian operator,
is a bounded, connected, and open subset of
,
is a Lipschitz continuous boundary, and a given function f is the external force.
A variational formulation of (1) seeks
such that

where

Let
be a quasi-uniform, i.e., it is regular and satisfies the inverse assumption [5] , triangulation of
with
. Let
be the space of poly- nomials of degree at most k with
on K. Let
denote the union of the boun- daries of all elements
and let
be the collection of all interior edges. Assume that the polynomial space in the construction of
contains
. Define the finite element space
associated with
as
![]()
The finite element space
is assumed to satisfy the following approximation pro- perty for any
[6] :
(2)
The nonconforming finite element approximation problem (2) seeks
such that
(3)
where
![]()
A well known error estimate for the finite element approximation solution
is the following [7] :
(4)
where C is a constant independent of the mesh size h.
To apply the superconvergence of finite element approximation, we assume that domain
is so regular that it ensures a
, regularity for the solution of (2). In other words, for any
the problem (2) has a unique solution
satisfying the following a priori estimate
(5)
where C is a constant independent of data f.
3. Superconvergence of NCFEM
Let
be another finite element partition with coarse mesh size
where
. Assume that
and h have the following relation:
(6)
Let
be any finite element space consisting of piecewise polynomial of degree r associated with the partition
. Define
to be the L2-projection from
onto the finite element space
. The finite element space
is defined as follows:
![]()
The following lemma will provide an error estimate for
.
Lemma 1 Assume that the second-order elliptic problem (2) holds (5) with
and
. Then there exists a constant C independent of h and
such that
(7)
where
and
.
Proof. Using the definition of
and
, we have
![]()
and
![]()
Then
(8)
Consider the following problem:
(9)
Multiplying the second-order elliptic Equation (1) by v and integrating it over
give
(10)
where n is the unit outward normal.
Subtract (3) from the above Equation (10) gives
(11)
Multiplying (9) by
, integrating it over
, adding and subtracting
, and using the result (11) we have
![]()
The line integrals of the above equations are approximated in [6] as follows:
(12)
(13)
Using the Cauchy-Schwartz inequality, the approximation property (2), and line integral approximations (12) and (13) we have
![]()
Substituting
as
by the
regularity, applying the inverse in- equality to the term
and using the definition of
we have
![]()
Combining the above equation with the Equation (8) we have
(14)
which completes the proof of the lemma.
The following theorem provides an error estimate for
.
Theorem 1 Assume that (5) holds true with
and
. If
is the finite element approximation of the exact solution
of (2), then there exists a constant C independent of h and
such that
(15)
Proof. Since we assume the exact solution u is sufficiently smooth and by the de- finitions of
and
, we have
(16)
Using the triangle inequality and combining (16) and Lemma 1 we obtain
![]()
which completes the error estimate of
.
Similarly, we estimate
.
Using the inverse inequality and the definitions of
and
we have
(17)
Using the triangle inequality and combining (17) and Lemma 1 we have
![]()
Hence the theorem has been proved.
The optimal
is selected using Theorem 1 for the error estimates:
![]()
(18)
4. Numerical Experiments of Superconvergence of NCFEM by L2-Projection Methods
In this section, we present numerical experiments for second-order elliptic problems to support our theoretical results. Assume that the exact solution of the second-order elliptic problem has the
regularity for some
and for simplicity, assume
and
which gives
using the
formula (18).
From the theoretical result (15) we have the following optimal error estimates:
(19)
and
(20)
From the results (19) and (20), theoretically, in L2 norm the L2-projection to the existing numerical approximation does not improve the convergence rate but in
norm the L2-projection to the existing numerical solution provides some superconver- gence.
The finite element partition
is constructed by dividing the domain into an
rectangular mesh then dividing the rectangular mesh with the positive slope to form two triangles. The coarse finite element partition
is also constructed by dividing the domain into an
rectangular mesh then dividing the rectangular mesh with the positive slope to form two triangles. The finite element space
con- sists of the space of the linear polynomials
associated with the partition
and the dual finite element space
consists of the space of the quadratic polynomials
associated with the partition
. The finite element spaces
and
are defined as follows:
![]()
and
![]()
The numerical approximation is refined as
where
. The length of
and each
element contains
elements.
Using the
Equation (18) and our choice of
and
we have
![]()
Using the difference in mesh size and a higher degree of polynomials we shall produce some superconvergence of NCFEM for the second-order elliptic problems.
Example 1. Let the domain
and the exact solution is assumed to be as follows:
![]()
From Table 1 we observe that the L2-projection to the existing numerical approxi- mation
reduced the error estimates in L2 norm and in
norm. In L2 norm the convergence rate of
is similar to the convergence rate of
which is the same as the theoretical result (19). The convergence rate of
is about 33% faster than the convergence rate of
in
norm (see Figure 2). The surface plots of
in coarse meshes and
in fine meshes are shown in Figure 1. The numerical example 1 clearly supports the theoretical result and confirms the super- convergence of NCFEM for the second-order elliptic problem.
Example 2. Let the domain
and let the analytical solution be given as
![]()
From Table 2, we can see that the numerical example 2 supports the theoretical result (15). See Figure 3, when
and
, we can project 32 fine triangle elements onto one coarse triangle element. Thus, as n increases, we can project
more fine triangle elements to one coarse triangle element in which the process of refining elements produces better error estimates. The L2-projection to the existing numerical approximation
produced some superconvergence in
norm and did not affect the convergence rate in L2 norm (see Figure 4). The numerical example 2 also
![]()
Table 1. Numerical error approximation results using NCFEM in Example 1,
.
![]()
Figure 2. Error convergence rates using NCFEM in Example 1,
. (L): L2 norm error; (R):
norm error.
![]()
Table 2. Numerical error approximation results using NCFEM in Example 2, ![]()
supports the theoretical result and confirms the superconvergence of NCFEM for the second-order elliptic problem.
5. Conclusion
The L2-projection to the existing numerical approximation
produced some super- convergence in
norm, convergence rate
, but did not affect the convergence
![]()
Figure 4. Error convergence rates using NCFEM in Example 2,
(L): L2 norm error; (R):
norm error.
rate in L2 norm. With the numerical experiments we can conclusively support the theoretical result and confirm the superconvergence of NCFEM for second-order elliptic problems by L2-projection method.
Acknowledgements
We thank the Editor and the peer-reviewers for their comments. Research of Anna Harris is funded by the National Science Foundation Historical Black Colleges and Universities Undergraduate Program Research Initiative Award grant (#1505119). This support is greatly appreciated.