An Immersed Weak Galerkin Method for Elliptic Interface Problems on Polygonal Meshes
Abstract.
In this paper we present an immersed weak Galerkin method for solving second-order elliptic interface problems on polygonal meshes, where the meshes do not need to be aligned with the interface. The discrete space consists of constants on each edge and broken linear polynomials satisfying the interface conditions in each element. For triangular meshes, such broken linear plynomials coincide with the basis functions in immersed finite element methods [26]. We establish some approximation properties of the broken linear polynomials and the discrete weak gradient of a certain projection of the solution on polygonal meshes. We then prove an optimal error estimate of our scheme in the discrete -seminorm under some assumptions on the exact solution. Numerical experiments are provided to confirm our theoretical analysis.
Key words and phrases:
immersed weak Galerkin method, elliptic interface problem, unfitted mesh, polygonal mesh2010 Mathematics Subject Classification:
65N12, 65N15, 65N30, 35J151. Introduction
There are a wide range of physical and engineering problems that are governed by partial differential equations having an interface. For example, a second-order elliptic partial differential equation with a discontinuous coefficient is often used as a model problem in material sciences and porous media involving multiple materials or media. To solve such a problem, one can use some classical numerical schemes with interface-fitted meshes, such as finite element methods (FEMs), discontinuous Galerkin (DG) methods, etc. However, it is difficult and takes a lot of time to generate such fitted meshes when the domain boundary and the interface are geometrically complicated. Even worse, when the interface is moving, one needs to generate a new fitted mesh as time evolves.
To overcome such difficulties, researchers developed and studied some numerical methods using unfitted/structured meshes, such as cut finite element methods (CutFEMs) [19, 12, 20, 3], extended finite element methods (XFEMs) [5, 6, 23, 28, 34], immersed finite element methods (IFEMs) [29, 30, 26, 22, 24], to name just a few. In particular, the IFEMs use basis functions that are modified so that they satisfy the interface conditions. The authors in [29, 30] studied IFEMs using uniform triangular or rectangular grids. In [24, 31], the performance of the IFEMs was improved by adding penalty terms that are commonly used in DG methods. Linear and bilinear nonconforming IFEMs were studied in [26, 32]. The IFEM was also successfully applied to other interface problems: interface elasticity problems [25], elliptic eigenvalue inteface problems [27], Stokes interface problems [1], etc.
On the other hand, several numerical methods using general polygonal or polyhedral meshes have been developed, such as hybrid high-order (HHO) methods [17, 18, 16], virtual element methods (VEMs) [4, 2, 10], weak Galerkin (WG) methods (or weak Galerkin finite element methods) [39, 40, 35], etc. Here we explain the WG methods in some detail. In WG methods, the discrete space consists of polynomials on an element interior and polynomials on its edges, and the differential operators are replaced by the so-called weak differential operators. Compared to the classical FEMs, the WG methods have several advantages. For example, WG methods can handle the general polygonal and polyhedral meshes while the FEMs cannot. In addition, the WG methods can be generalized to higher orders directly. Due to such advantages, the WG methods were successfully applied to various problems: Darcy problems [40], Stokes equations [41], elasticity problems [44], Maxwell equations [36], etc. For more thorough survey, we refer to [39, 35, 43, 33, 42, 21] and references therein.
In [37], an immersed WG method was proposed for the elliptic interface problems for triangular meshes. However, their method cannot be generalized to the polygonal meshes since it is impossible to define the Lagrange-type immersed finite element interpolation on polygonal elements. Besides, the discrete bilinear form formulated in their method is different from the usual WG method; they use the usual gradient and DG-type consistency terms.
In this paper, we develop a new immersed WG method for the elliptic interface problems. Our method uses general polygonal meshes which allow the interface cut through the interior. We generalize the discrete weak gradient to the case when the coefficient is discontinuous, and use it to define the bilinear form. Our weak gradient coincides with the usual one [35] when the coefficient is constant. However, they are different from each other when the coefficient is non-constant.
The rest of the paper is organized as follows. In the next section, we describe the model problem and summarize some preliminaries. In Section 3, we propose our immersed WG method for the model problem, and prove that the discrete problem is well-posed. In Section 4, we prove some technical inequalities and approximation properties of broken linear polynomials on polygonal elements. In Section 5, we derive an optimal error estimate in the discrete -seminorm under some regularity assumptions on the exact solution. Finally, in Section 6, we present some numerical experiments that confirm our theoretical analysis.
2. Preliminaries
We follow the usual notation of Sobolev spaces, inner product, seminorms, and norms (see, for example, [15]). Let be a bounded domain in or . For , we denote by and the usual norm and seminorm of the Sobolev space , respectively. We also denote by the usual inner product in . We define as the dual space of equipped with the norm given by
where is the duality pairing. For a nonnegative integer , we denote by the space of all polynomials of degree on .
2.1. Model problem
Let be a convex polygonal domain in , which is separated into two disjoint subdomains and by an interface as in Figure 1. Here we assume that is a regular -curve that is not self-intersecting. For any domain and any function , we define its jump across the portion of the interface as
We consider the following elliptic interface problem: Given , find such that
(2.1) |
with the jump conditions on the interface
(2.2) |
where is a positive and piecewise -function on bounded below and above by two positive constants and with . That is,
for some functions such that , . A weak formulation of the model problem (2.1)-(2.2) is written as follows: Find such that
(2.3) |
For any domain , let us introduce the space
equipped with the following norm and seminorm:
We also define
Then we have the following regularity theorem for the solution of the variational problem (2.3); see [8, 13].
Theorem 2.1.
Suppose that . Then the variational problem (2.3) has a unique solution satisfying
(2.4) |
for some generic positive constant .
2.2. Mesh assumptions
Let be a family of decompositions (meshes) of into polygonal elements with maximum diameter . Let be the set of all edges in . Let and denote the set of all interior and boundary edges in , respectively. For each , let be the set of all edges of . For each , we denote by the area of , by the diameter of , and by its exterior unit normal vector along the boundary . For each , we denote by the length of . For , we define by a unit normal vector of with orientation fixed once and for all. For , we define by a unit normal vector on in the outward direction with respect to .
We call an element an interface element if the interface passes through the interior of ; otherwise we call a noninterface element. We denote by the collection of all interface elements in , and by the collection of all non-interface elements in . For an interface element , we denote by the line segment connecting the intersections of and the edges of . This line segment divides into two parts and with (see, for example, Figure 2). For any function , we define its jump across as
Assumption 2.2.
There exists independent of such that
-
(i)
the decomposition consists of a finite number of nonoverlapping polygonal elements;
-
(ii)
for any the diameter of any edge of is larger than ;
-
(iii)
every element of is star-shaped with respect to a ball with center and radius ;
-
(iv)
if is an edge of then ;
-
(v)
the interface meets the edges of an interface element at no more than two points;
-
(vi)
the interface meets each edge in at most once, except possibly it passes through two vertices.
Remark 2.3.
The assumptions (v) and (vi) are resonable if is sufficiently small. Note also that the assumptions (i)-(iv) imply that the following properties [10]:
-
•
Every has at most edges and vertices, where is independent of .
-
•
Each element can be decomposed as triangles, obtained by connecting the vertices of to , such that the minimum angle of the triangles is controlled by .
Throughout this paper, will denote a generic positive constant independent of , not necessarily the same in each occurrence.
3. Immersed Weak Galerkin Method
In this section, we describe an immersed WG method for the problem (2.3).
3.1. Broken polynomial space
Let be an interface element. We define the piecewise constant function on the element as follows:
where and denotes the barycenter of for . We also let be the piecewise constant function such that on each . The broken polynomial space of degree is defined by
It is easy to see that (see, for example, [26, Theorem 2.2]), and the following piecewise polynomials form a basis of :
where is the midpoint of the line segment , is a unit vector normal to pointing from to , and . Note that, since , the space is well-defined, and the vector-valued functions and form a basis of .
For convenience, we set for any non-interface element . Let
3.2. Weak Galerkin finite element space
We define the weak Galerkin finite element space associated to and its subspace as follows:
Here we note that, for any , its second component is a single-valued function on each edge . Thus, the space has degrees of freedom on the interior of each element and degree of freedom on each edge .
For each element , let be the -projection from onto . Similarly, for each edge , let the -projection from onto . We then define a projection operator by
(3.1) |
3.3. Discrete problem and well-posedness
For each , we define a discrete weak gradient of as a vector-valued function satisfying and
(3.2) |
for each element .
We next introduce two bilinear forms on as follows:
for any and , where is an arbitrary positive constant. The stabilization of is defined by
We are now ready to formulate the immersed WG method for solving (2.3) as follows: Find such that
(3.3) |
We next analyze the well-posedness of the discrete problem (3.3). Define the energy-norm by
Clearly is a seminorm on . Moreover, is a norm on , as shown in the following lemma.
Lemma 3.1.
is a norm on .
Proof.
It suffices to show that for any . Suppose that satisfies . Since
and since for any , we obtain and on each edge . Then
for any . This shows that on each . Note that, for each , implies for any . Since on each , we obtain that is constant on each . Since on each and on , we conclude that . ∎
The well-posedness of the discrete problem (3.3) directly follows from the lemma.
Corollary 3.2.
The discrete problem (3.3) is well-posed.
Proof.
From Lemma 3.1, the bilinear form on is coercive and continuous with respect to the norm on . The conclusion follows from the Lax-Milgram Lemma. ∎
4. Some Estimates on Interface Elements
In this section, we present some inequalities for the function spaces on the interface elements, which are needed for the error analysis of the immersed WG method.
4.1. Geometric assumptions on interface elements
Let be an interface element. Recall that denotes the line segment connecting two intersection points of and the edges of . Although the analysis works for -interface, we assume for the simplicity of presentation, that on each mesh element , the portion is a line segment so that and for . In addition, we assume that aligns with the -axis and the origin of the -plane is contained in , so that
(4.1) |
(see Figure 3). Since , we have . Since and on for , we have
(4.2) |
where . Let be the unit vector normal to pointing from to , and let .
Remark 4.1.
We briefly discuss the case when the interface is not piecewise linear, that is, . Without loss of generality we assume that aligns with the -axis and is contained in the box , where and are intervals with length not greater than . Since is a regular -curve, there exists a parametrization of the curve for some , when is sufficiently small. Then the unit normal vector along pointing from to is
Let us extend the vector-valued function to the box by setting . Then, since is , we have
(4.3) |
where is the unit normal vector along pointing from to . In addition, one can obtain a similar result for the tangential vector of . Next, according to Lemma 2 in [7],
(4.4) |
where is a subset of given by
see Figure 2. Note also that the first estimate in (4.2) is modified as follows:
(4.5) |
Using the estimates (4.3)-(4.5) and the standard trace inequality, all the results below can be derived with only minor modification. We leave the detailed analysis for a future investigation.
Lemma 4.2.
If is sufficiently small, then either or contains a ball with radius .
Proof.
Recall that is star-shaped with respect to a ball centered at with radius . First, assume that . Consider the ball centered at with radius . Then .
One can show that, by the same argument, for the case the set contains the ball centered at with radius , and for the case the set contains the ball centered at with radius . ∎
4.2. Some inequalities for the broken polynomial space
Recall that, on each element , the standard trace inequality holds:
(4.6) |
The following lemma provides a trace inequality for the space .
Lemma 4.3.
Let be an interface element. Then there exists a positive constant depending only on and such that for any and any edge of ,
(4.7) |
Proof.
Note that we have the following inverse inequality holds (see, for example, (2.6) of [10]):
(4.8) |
where is a ball in with radius and is a positive constant depending only on . The following lemma shows that the inverse inequality also holds for the space .
Lemma 4.4.
Let be an interface element. There exists a positive constant depending only on and such that
4.3. Approximation properties of the broken polynomial space
In this subsection, we derive some approximation properties of the broken linear polynomial space .
It is well-known that, on each non-interface element , for any there exists such that
(4.12) |
where is a positive constant depending only on [11, Lemma 4.3.8].
Theorem 4.5.
Let . Then there exists such that
where is a positive constant depending only on and .
Proof.
Let be an interface element. Then we have
(4.13) |
on . We note that and . Thus, from (4.12), there exist such that
Note that
(4.14) |
Thus
(4.15) |
Let
Then . By (4.13), (4.15), and (4.2),
(4.16) | |||||
Since , there exists such that and . Then (4.16) and Poincaré-Friedrichs inequality (cf. [9]) imply that
This completes the proof of the theorem. ∎
As a corollary, we obtain the estimate for the -projection onto the space as follows.
Corollary 4.6.
There exists a positive constant , depending only on and , such that
Proof.
Let be an interface element. By Theorem 4.5, there exists such that
(4.17) |
where is a positive constant depending only on and . Since for any and for any , we obtain
By Lemma 4.4,
This completes the proof. ∎
The following lemma gives the -norm estimate of on each mesh edge (see Proposition 5.2 in [24]).
Lemma 4.7.
There exists a positive constant independent of such that
Proof.
Let be an interface element. Let , and let . As in (4.13), we have
(4.18) |
on . Since , we have and . Note also that and are constants on . Then, by (4.2),
(4.19) | |||||
By the trace inequality (4.6) and (4.14),
(4.20) | |||||
(4.21) | |||||
By the trace inequality (4.6), Corollary 4.6, and (4.2),
(4.22) | |||||
(4.23) | |||||
Now the conclusion follows from the inequalities (4.19)-(4.23). ∎
The following lemma gives the -norm estimate of on each element in .
Lemma 4.8.
There exists a positive constant independent of such that
Proof.
Let be an interface element. By the definition of the discrete weak gradient (3.2), we have
Let satisfy . By the trace inequality (4.6), Lemma 4.3, Poincaré-Friedrichs inequality, and Corollary 4.6, we obtain
and this completes the proof. ∎
5. Error Analysis
In this section, we present the error estimate in the discrete -seminorm for the scheme (3.3).
5.1. Discrete -seminorm
We introduce a discrete -seminorm as follows: For ,
The following lemma shows that two seminorms and on are equivalent.
Lemma 5.1.
There exist two positive constants and independent of such that
Proof.
The proof is similar to the proof of Lemma 5.3 in [35]. Let . By the definition of the discrete weak gradient (3.2), we have
(5.1) |
Let satisfy on each . Then, by Lemma 4.3,
Thus we have . Since , we have
On the other hand, let satisfy on each . Then, by (5.1) and Lemma 4.3 we have
Thus . Since , we obtain
Hence we have proved the lemma. ∎
5.2. Error equation
The error equation presented in the following lemma will be used to derive the error estimate.
Proof.
Note that, for any ,
Since for each interior edge and for each boundary edge , we obtain
Using the above equation we obtain
This completes the proof of the lemma. ∎
The following lemma can be found in [14].
Lemma 5.3.
Let and let . Then there exists a positive constant independent of such that
where .
5.3. Error estimate
Now we prove the error estimates in the energy norm and the discrete -seminorm.
Theorem 5.4.
Proof.
Let . From the error equation (5.2), we have
(5.3) | |||||
By the trace inequality (4.6), Poincaré-Friedrichs inequality, and Corollary 4.6,
(5.4) | |||||
From (4.2), Lemma 4.8, and Lemma 5.1,
(5.5) | |||||
Since on each , using Lemma 4.3, Lemma 4.7, and Lemma 4.8, we have
(5.6) | |||||
Let and . Since , by Lemma 5.3 and the trace theorem, we have
Thus we obtain from Remark 2.3 that
(5.7) | |||||
Now combining the inequalities (5.3)-(5.7) we have
This concludes the proof of the theorem. ∎
Using Lemma 5.1 and Theorem 5.4, we immediately obtain the following discrete -seminorm error estimate.
6. Numerical Examples
In this section, we report several numerical results. We solve the problem (2.1)-(2.2) with partitioned into two different families of meshes as follows:
-
(i)
M1: uniform square meshes with ,
-
(ii)
M2: unstructured polygonal meshes with .
Some examples of the meshes are shown in Figure 4. The unstructured polygonal meshes are generated from PolyMesher [38]. Let be the exact solution and let be the solution of our immersed WG method. We compute errors in the discrete -seminorm and -norm, which are given by
respectively. For the examples below, the discrete -seminorm error converges with order , which agrees with our theoretical result. Moreover, the results show the error in discrete -norm, which is optimal.




Example 6.1 (Circular interface).
Example 6.2 (Sharp edge).
Example 6.3 (Variable coefficient).
In this example, we take the level set of with and as an interface, that is, we set
The exact solution is chosen as , where
The results are reported in Table 6.
M1 | M2 | |||||||
---|---|---|---|---|---|---|---|---|
Order | Order | Order | Order | |||||
5.4587e-02 | 3.3027e-03 | 5.5979e-02 | 3.3820e-03 | |||||
2.6417e-02 | 1.0471 | 8.7554e-04 | 1.9154 | 2.7216e-02 | 1.0404 | 8.8878e-04 | 1.9280 | |
1.3137e-02 | 1.0079 | 2.2319e-04 | 1.9719 | 1.3755e-02 | 0.9845 | 2.2742e-04 | 1.9665 | |
6.5602e-03 | 1.0018 | 5.6112e-05 | 1.9919 | 6.9372e-03 | 0.9876 | 5.6936e-05 | 1.9979 | |
3.2792e-03 | 1.0004 | 1.4049e-05 | 1.9979 | 3.4921e-03 | 0.9903 | 1.4224e-05 | 2.0011 | |
1.6395e-03 | 1.0001 | 3.5135e-06 | 1.9995 | 1.7500e-03 | 0.9967 | 3.5427e-06 | 2.0054 |
M1 | M2 | |||||||
---|---|---|---|---|---|---|---|---|
Order | Order | Order | Order | |||||
5.8617e-02 | 3.4872e-03 | 6.0526e-02 | 3.6934e-03 | |||||
2.8290e-02 | 1.0510 | 9.3409e-04 | 1.9004 | 2.9512e-02 | 1.0362 | 9.7713e-04 | 1.9183 | |
1.4189e-02 | 0.9955 | 2.4360e-04 | 1.9391 | 1.5092e-02 | 0.9676 | 2.4927e-04 | 1.9708 | |
7.1176e-03 | 0.9953 | 6.2122e-05 | 1.9713 | 7.7258e-03 | 0.9660 | 6.2438e-05 | 1.9972 | |
3.5635e-03 | 0.9981 | 1.5643e-05 | 1.9896 | 3.9414e-03 | 0.9710 | 1.5536e-05 | 2.0068 | |
1.7825e-03 | 0.9994 | 3.9192e-06 | 1.9969 | 1.9947e-03 | 0.9825 | 3.8632e-06 | 2.0078 |
M1 | M2 | |||||||
---|---|---|---|---|---|---|---|---|
Order | Order | Order | Order | |||||
5.5356e-02 | 3.2533e-03 | 5.8561e-02 | 3.3911e-03 | |||||
2.6461e-02 | 1.0649 | 8.7488e-04 | 1.8947 | 2.7524e-02 | 1.0893 | 8.8967e-04 | 1.9304 | |
1.3148e-02 | 1.0090 | 2.2320e-04 | 1.9707 | 1.3777e-02 | 0.9984 | 2.2758e-04 | 1.9669 | |
6.5645e-03 | 1.0021 | 5.6113e-05 | 1.9919 | 6.9396e-03 | 0.9893 | 5.6970e-05 | 1.9981 | |
3.2800e-03 | 1.0010 | 1.4049e-05 | 1.9978 | 3.4929e-03 | 0.9904 | 1.4231e-05 | 2.0011 | |
1.6398e-03 | 1.0002 | 3.5137e-06 | 1.9994 | 1.7504e-03 | 0.9968 | 3.5445e-06 | 2.0054 |
M1 | M2 | |||||||
---|---|---|---|---|---|---|---|---|
Order | Order | Order | Order | |||||
1.6219e-01 | 3.4747e-03 | 7.4038e-02 | 3.7966e-03 | |||||
2.9224e-02 | 2.4725 | 8.7313e-04 | 1.9926 | 3.1237e-02 | 1.2450 | 9.9624e-04 | 1.9301 | |
1.4104e-02 | 1.0511 | 2.2151e-04 | 1.9788 | 1.5075e-02 | 1.0512 | 2.5707e-04 | 1.9543 | |
7.0375e-03 | 1.0029 | 5.6761e-05 | 1.9644 | 7.5627e-03 | 0.9951 | 6.4711e-05 | 1.9901 | |
3.5397e-03 | 0.9914 | 1.4787e-05 | 1.9406 | 3.7960e-03 | 0.9944 | 1.6118e-05 | 2.0053 | |
1.7847e-03 | 0.9879 | 3.8351e-06 | 1.9470 | 1.9126e-03 | 0.9890 | 3.9855e-06 | 2.0159 |
M1 | M2 | |||||||
---|---|---|---|---|---|---|---|---|
Order | Order | Order | Order | |||||
6.0360e-01 | 3.0913e-02 | 5.6648e-01 | 3.2621e-02 | |||||
3.0771e-01 | 0.9720 | 7.1992e-03 | 2.1023 | 2.8813e-01 | 0.9753 | 8.0180e-03 | 2.0245 | |
1.6788e-01 | 0.8742 | 1.7187e-03 | 2.0665 | 1.6058e-01 | 0.8434 | 1.9645e-03 | 2.0291 | |
8.3267e-02 | 1.0116 | 4.2052e-04 | 2.0310 | 7.6565e-02 | 1.0686 | 4.7390e-04 | 2.0515 | |
3.9446e-02 | 1.0779 | 1.0327e-04 | 2.0258 | 3.5919e-02 | 1.0919 | 1.0916e-04 | 2.1181 | |
1.9396e-02 | 1.0241 | 2.5529e-05 | 2.0162 | 1.7581e-02 | 1.0308 | 2.6011e-05 | 2.0693 |
M1 | M2 | |||||||
---|---|---|---|---|---|---|---|---|
Order | Order | Order | Order | |||||
1.0067e+01 | 5.8821e-01 | 9.7421e+00 | 6.1556e-01 | |||||
5.0872e+00 | 0.9847 | 1.4782e-01 | 1.9925 | 4.8530e+00 | 1.0054 | 1.5612e-01 | 1.9793 | |
2.5514e+00 | 0.9956 | 3.7083e-02 | 1.9950 | 2.4251e+00 | 1.0009 | 3.9536e-02 | 1.9814 | |
1.2772e+00 | 0.9983 | 9.2748e-03 | 1.9994 | 1.2119e+00 | 1.0008 | 9.9313e-03 | 1.9931 | |
6.3883e-01 | 0.9995 | 2.3199e-03 | 1.9992 | 6.0612e-01 | 0.9995 | 2.4873e-03 | 1.9974 | |
3.1948e-01 | 0.9997 | 5.8000e-04 | 2.0000 | 3.0290e-01 | 1.0007 | 6.2143e-04 | 2.0009 |
7. Conclusion
We introduce an immersed WG method for the elliptic interface problems on general unfitted polygonal meshes. The discrete space consists of constant functions on the mesh edges and piecewise linear functions in the mesh elements, satisfying the interface conditions. We prove an optimal-order convergence in the discrete -seminorm under some assumptions on the exact solution.
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