In this paper, we propose a BDDC preconditioner for the mortar-type rotated finite element method for second order elliptic partial differential equations with piecewise but discontinuous coefficients. We construct an auxiliary discrete space and build our algorithm on an equivalent auxiliary problem, and we present the BDDC preconditioner based on this constructed discrete space. Meanwhile, in the framework of the standard additive Schwarz methods, we describe this method by a complete variational form. We show that our method has a quasi-optimal convergence behavior, i.e., the condition number of the preconditioned problem is independent of the jumps of the coefficients, and depends only logarithmically on the ratio between the subdomain size and the mesh size. Numerical experiments are presented to confirm our theoretical analysis.
MSC: 65N55, 65N30.
Keywords:domain decomposition; BDDC algorithm; mortar; rotated element; preconditioner
The method of balancing domain decomposition by constraints (BDDC) was first introduced by Dohrmann in . Mandel and Dohrmann restated the method in an abstract manner, and provided its convergence theory in . The BDDC method is closely related to the dual-primal FETI (FETI-DP) method , which is one of dual iterative substructuring methods. Each BDDC and FETI-DP method is defined in terms of a set of primal continuity. The primal continuity is enforced across the interface between the subdomains and provides a coarse space component of the preconditioner. In , Mandel, Dohrmann, and Tezaur analyzed the relation between the two methods and established the corresponding theory.
In the last decades, the two methods have been widely analyzed and successfully been extended to many different types of partial differential equations. In , the two algorithms for elliptic problems were rederived and a brief proof of the main result was given. A BDDC algorithm for mortar finite element was developed in , meanwhile, the author also extended the FETI-DP algorithm to elasticity problems and Stokes problems in [6,7], respectively. These algorithms are based on locally conforming finite element methods, and the coarse space components of the algorithms are related to the cross-points (i.e., corners), which are often noteworthy points in domain decomposition methods (DDMs). Since the cross-points are related to more than two subregions, thus it is not convenient to design the domain decomposition algorithm.
The BDDC method derives from the Neumann-Neumann domain decomposition method (see ). The difference is that the BDDC method applies an additive rather than a multiplicative coarse grid correction, and substructure spaces have some constraints which result in non-singular subproblems. Thus we need not modify the bilinear forms on subdomains, and we can solve each subproblem and coarse problem in parallel.
The rotated element is an important nonconforming element. It was introduced by Rannacher and Turek in  for stokes equations originally, and it is the simplest example of a divergence-stable nonconforming element on quadrilaterals. Since its degree of freedom is integral average on element edge which is not related to the corners, and each degree of freedom on subdomain interfaces is only included in two neighboring subdomains, so it is easy to design the BDDC algorithm.
The mortar technique was introduced in . This method is nonconforming domain decomposition methods with nonoverlapping subdomains. The meshes on different subdomains need not align across subdomain interfaces, and the matching of discretizations on adjacent subdomains is only enforced weakly. This offers the advantages of freely choosing highly varying mesh sizes on different subdomains and is very promising to approximate the problems with abruptly changing diffusion coefficients or local anisotropic.
In this paper, we study the BDDC algorithm for the mortar-type rotated element for the second order elliptic problem with discontinuous coefficients, where the discontinuities lie only along the subdomain interfaces. Following the technique in , we construct an auxiliary discrete space and build our BDDC algorithm on an equivalent auxiliary problem. This approach overcomes the difficulty caused by the mortar condition and simplifies the implementation of the BDDC preconditioning iteration. Furthermore, since the rotated element is not related to the subdomain’s vertices, we can complete our theoretical analysis conveniently. It is proved that the condition number of the preconditioned operator is independent of the jumps of the coefficients and only depends logarithmically on the ratio between the subdomain size and mesh size. Numerical experiments are presented to confirm our theoretical analysis.
The rest of this paper is organized as follows: in Section 2, we introduce the model problem and the auxiliary problem. Section 3 gives the BDDC algorithm and proposes the BDDC preconditioner. Several technical tools are presented and analyzed in Section 4. In Section 5, we give the proof of the main result. Last section provides numerical experiments. For convenience, the symbols ⪯, ⪰ and ≍ are used, and , , and mean that , , and for some constants , , , and that are independent of discontinuous coefficients and mesh size.
For simplicity, we only consider the geometrically conforming case, i.e., the intersection between the closure of two different subdomains is empty, or a vertex, or an edge. The subdomains together form a coarse partition , we denote the diameter of each by . Let be a quasi-uniform partition with the mesh size , made up of shape regular rectangles in . The resulted partition can be nonmatched across adjacent subdomain interfaces. We denote the sets of edges of the triangulation in and by , respectively, and let , be the sets of vertices of the triangulation that are in , respectively.
We denote the common open edge of and , and let . Each can be regarded as two sides corresponding to the two subdomains and . We define one of the sides of as mortar denoted by and the other one as nonmortar denoted by , here m represents the indexing of (see Figure 1). We assume that: (1) the mortar for is chosen by the condition ; (2) there is at least one subdomain which has two mortar sides associated with each cross point; (3) , i.e., is bounded. The first condition used in choosing mortar sides is essential (see the numerical tests in ). The last condition is technical but not essential for the convergence analysis. Along each , there are two independent and different 1-D meshes which are denoted by and . For each nonmortar side , we denote by an auxiliary test space whose functions are piecewise constant on . We denote by the -orthogonal projection from the space to the space.
Figure 1. Nonmatching grid.
here is the restriction of to the mortar side , and is the restriction of to the nonmortar side . The condition in (2.2) for each interface is called mortar condition. The mortar-type rotated element approximation of problem (2.1) is: find such that
It can easily be shown that is positive definite on , which yields the existence and uniqueness of the discrete solution. The error estimate between the discrete and the continuous solution is discussed in .
Since the mortar condition depends on both the degrees of freedom on the interfaces and the ones near the interfaces, it is difficult to construct a preconditioner directly for (2.3). To overcome this difficulty, we introduce a new discrete space and an auxiliary problem which is equivalent to problem (2.3).
Lemma 2.1 ()
3 BDDC algorithm
In this section, we introduce our BDDC preconditioner for problem (2.7) and describe the BDDC algorithm.
As we know, the technical aspect in DDMs is that the preconditioner includes a coarse problem which can enhance the convergence. In view of the characteristic of the space , we select the standard coarse space which is the rotated finite element space associated with the coarse partition , and it satisfies primal constraints on subdomain interfaces.
In what follows, we describe our BDDC preconditioning algorithm, we apply the basic framework of additive Schwarz method (or parallel subspace correction method ). From the decomposition (3.1), we only need to choose appropriate subspace solvers.
Remark 3.1 The bilinear form on the coarse space can be different from that on substructure space, here we only use the exact solvers. On each subdomain, we avoid the possible singularity of local subproblem and we need not modify the bilinear forms.
Now we define our BDDC preconditioner as
We have the following main result.
4 Technical tools
In this section we state and prove a few technical lemmas necessary for the proof of Theorem 3.1. Our theoretical analysis is based on the substructuring theory of conforming elements.
Lemma 4.1 ()
Remark 4.1 The above lemma is related to vertex-edge-face arguments in substructuring methods, in view of the characteristic for the rotated element, here the results only concern the inequalities for faces.
Let be the conforming element space of bilinear continuous functions on the partition which is constructed by joining the midpoints of the edges of elements of . We now introduce a local equivalence map as follows (cf.).
For the operators and , we have the following results (see ):
Proof By (4.1), Lemma 4.1, the inverse trace theorem, the trace theorem, and the Poincaré inequality, we obtain
5 Proof of Theorem 3.1
In the proof of Theorem 3.1 we use the abstract framework of ASM methods (see ), we need to prove three assumptions. Assumption II follows from the standard coloring argument, we only need to prove Assumption I and Assumption III.
First we show the following stability of the decomposition.
Lemma 5.1 (Assumption I)
Now we prove the stability of decomposition (5.2). Let . Using Lemma 3.5 in , Poincaré-Friedrichs’ inequality and scaling argument, we derive
From (5.3) and the discrete equivalent norm, we have
Meanwhile, from the fact that the harmonic function has minimal energy norm and (5.4)-(5.5), we deduce
So (5.4)-(5.6) lead to (5.2). □
Next we state the local stability as follows.
Lemma 5.2 (Assumption III)
Note that the support of is on , and using Lemma 3.4 in  we have
From (5.10)-(5.12), we complete the proof of (5.8).
Using similar techniques to those in (5.8), and summing over all subdomains, we can complete the proof of (5.9). □
6 Numerical results
In this section, we show numerical results of our method using the model problem
where . The domain is composed of sub-squares, their mesh sizes are H, and the sub-squares are divided into smaller ones with mesh sizes in mortar subdomains; and in nonmortar subdomains. The coefficient ρ is either 1 or ().
We use the preconditioned conjugate gradient (PCG) method with zero initial guess for the discrete system of equations. The stopping criterion for the PCG method is when the 2-norm of the residual is reduced by the factor of 10−6 of the initial guess. An estimate for the condition number of the corresponding system is computed by using the Lanczos algorithm.
In Table 1, we show the number of iterations and the condition numbers with different ratio . In Figure 2, we plot the condition number as the function for 16 domains. From the results in Table 1 and Figure 2, we see that the convergence of our method is quasi-optimal since the number of iterations is independent of the jumps of the coefficients, and almost independent of the mesh size.
The authors declare that they have no competing interests.
All results belong to YJ and JC. All authors read and approved the final manuscript.
The work was supported by the National Natural Science Foundation of China (Grant Nos. 11371199 and 11301275), Jiangsu Provincial 2011 Program (Collaborative Innovation Center of Climate Change), the Program of Natural Science Research of Jiangsu Higher Education Institutions of China (Grant No. 12KJB110013), the Doctoral fund of Ministry of Education of China (Grant No. 20123207120001), and Jiangsu Key Lab for NSLSCS (Grant No. 201306). Moreover the authors are grateful to anonymous referees for their constructive comments and suggestions.
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