Abstract
Expanded mixed finite element method is introduced to approximate the two-dimensional Sobolev equation. This formulation expands the standard mixed formulation in the sense that three unknown variables are explicitly treated. Existence and uniqueness of the numerical solution are demonstrated. Optimal order error estimates for both the scalar and two vector functions are established.
1. Introduction
In this paper, we consider the following Sobolev equation: in a bounded domain with Lipschitz continuous boundary . Equation (1) has a wide range of applications in many mathematical and physical problems [1, 2], for example, the percolation theory when the fluid flows through the cracks, the transfer problem of the moisture in the soil, and the heat conduction problem in different materials. So there exists great and actual significance to research Sobolev equation. Up till now, there are some different schemes studied to solve this kind of equation (see [1–4] for instance).
The mixed finite element method, which is a finite element method [5] with constrained conditions, plays an important role in the research of the numerical solution for partial differential equations. Its general theory was proposed by Babuska [6] and Brezzi [7]. Falk and Osborn [8] improved their theory and expanded the adaptability of the mixed finite element method. The mixed finite element method (see [9, 10] for instance) is wildly used for the modeling of fluid flow and transport, as it provides accurate and locally mass conservative velocities.
The main motivation of the expanded mixed finite element method [11–15] is to introduce three (or more) auxiliary variables for practical problems, while the traditional finite element method and mixed finite element method can only approximate one and two variables, respectively. The expanded mixed finite element method also has some other advantages except introducing more variables. It can treat individual boundary conditions. Also, this method is suitable for differential equation with small coefficient (close to zero) which does not need to be inverted. Consequently, this method works for the problems with small diffusion or low permeability terms in fluid problems. Using this method, we can get optimal order error estimates for certain nonlinear problems, while standard mixed formulation sometimes gives only suboptimal error estimates.
The object of this paper is to present the expanded mixed finite element method for the Sobolev equation. We conduct theoretical analysis to study the existence and uniqueness and obtain optimal order error estimates. The rest of this paper is organized as follows. In Section 2, the mixed weak formulation and its mixed element approximation are considered. In Section 3, we prove the existence and uniqueness of approximation form. In Section 4, some lemmas are given. In Section 5, optimal order semidiscrete error estimates are established.
Throughout the paper, we will use , with or without subscript, to denote a generic positive constant which does not depend on the discretization parameter . Vectors will be expressed in boldface. At the same time, we show a useful -Cauchy inequality
2. Mixed Weak Form and Mixed Element Approximation
For and any nonnegative integer, let denote the Sobolev spaces [16] endowed with the norm (the subscript will always be omitted).
Let with the norm . The notation will mean or . We denote by the inner product in either or ; that is, The notation denotes the -inner product on the boundary of
To formulate the weak form, let ; we introduce two vector variables Letting , we rewrite (1) as the following system: Let be the unit exterior normal vector to the boundary of . Then (8) is formulated in the following expanded mixed weak form: find , such that where
Let be a quasiregular polygonalization of (by triangles or rectangles), with being the maximum diameter of the elements of the polygonalization. Let be a conforming mixed element space with index and discretization parameter . is an approximation to . There are many conforming (or compatible) mixed element function spaces such as Raviart-Thomas elements [17], BDFM elements [18, 19]. Some RT type mixed elements are listed in Table 1. Here, is the polynomial up to order in two-dimensional domain used in triangle, while is the polynomial up to in each dimension used in rectangle.
Replacing the three variables by their approximation, we get the expanded mixed finite element approximation problem: find , such that where
The error analysis next makes use of three projection operators. The first operator is the Raviart-Thomas projection (or Brezzi-Douglas-Marini projection) ; satisfies The following approximation properties are well known. The other two operators are the standard -projection [5] and onto and , respectively, They have the approximation properties The two projections and preserve the commuting property
3. Existence and Uniqueness of Approximation Form
In this section, we consider the existence and uniqueness of the solution of (11).
Lemma 1. Equation (11) has a unique solution.
Proof. In fact, this equation is linear; it suffices to show that the associated homogeneous system has only the trivial solution. In the first equation of (19), if we take and , respectively, then we have that By (20), it is easy to see that Choosing , , and in (19), we get In the third equation of (19), letting and , respectively, then Using the -Cauchy inequality to (22), we have Note that (21), we deserve From (27), we know Using Gronwall’s inequality to (28), we can prove . Further, from (26) and (23), we know that , . The proof is completed.
4. Some Lemmas
In the study of parabolic equations, we usually introduce a mixed elliptic projection associated with our equations. Define a map: find , such that Similarly to Lemma 1, we can prove that system (29) has a unique solution.
Now we give some error estimates of . Define System (29) can be rewritten as follows: Now we consider the estimates of and .
Lemma 2. Let be the solution of system (31). If , , and are sufficiently smooth, then there exist positive constants such that where for , and for .
Proof. Let be the solution of the following problem: Then we know For , from the second equation of (31), we have that It is easy to see that Now, we estimate , We turn to consider , where is the piecewise constant interpolation of function . Using the previous estimates, we obtain So we deserve Applying Gronwall’s inequality to (40), we have Noting the estimates of , , and , the proof is completed.
Define
Lemma 3. Let and be the solution of (19) and (29), respectively. If , , and are sufficiently smooth, then there exist positive constants such that(I)if , then (II)if , then (III)if , then
Proof. For , the proof proceeds in three steps as follows.
(I) In the first equation of (29), taking , we know
which implies that
Choosing , note that and , we get
Combing (15) with (56), we can prove (43).
(II) In (29), letting , together with (43), we obtain
Hence
In the third equation of (29), choosing , we get
So we know
Note that (44) and (45), we obtain
which implies that
Now we estimate ,
It is easy to see that
By the properties of projection , we get
which proves (49) and (53).
Now we estimate ,
where
From (66) and (67), we know
By Lemma 2, if , we have that
If , we have that
Using the estimate of , we obtain
If , we get
If , we get
(III) By Lemma 2, we have that
If , we know
If , we know
The proof is completed.
Remark 4. The estimate results of (46)–(53) are optimal. If , the estimate results of (43)–(45) are superconvergent.
5. Main Result
In this section, we consider error estimates for the continuous-in-time mixed finite element approximation. Define
Theorem 5. Let and be the solution of (9) and (11), respectively. If , , and are sufficiently smooth, then there exist positive constants such that(I)if , then (II)if and , then
Proof. From (9) and (19), we have the following error equation: In (85), choosing , , and , we have In the second equation of (85), letting , we know Further, using -inequality to (86), we get Hence, Using Gronwall’s inequality to (89), we obtain Further, we know Noting the first equation of (78), we get So we have that Together with the results of Lemmas 2 and 3, the proof is completed.
Remark 6. The estimate results of (78)–(84) are optimal.
Acknowledgments
This work is supported by the National Natural Science Foundation of China (nos. 11171190, 11101246, and 11101247) and the Natural Science Foundation of Shandong Province (ZR2011AQ020). The authors thank the anonymous referees for their constructive comments and suggestions, which led to improvements in the presentation.