Local convergence of the boundary element method on polyhedral domains
Markus Faustmann, Jens Markus Melenk

TL;DR
This paper analyzes the local convergence properties of the lowest order boundary element method on polyhedral domains, providing local a priori estimates and convergence rates based on solution regularity.
Contribution
It offers new local a priori estimates and convergence rate analysis for boundary element methods on polyhedral domains, considering solution regularity.
Findings
Established local $L^2$ estimates for Symm's integral equation.
Derived local $H^1$ estimates for hypersingular integral equations.
Identified the influence of solution regularity on convergence rates.
Abstract
The local behavior of the lowest order boundary element method on quasi-uniform meshes for Symm's integral equation and the stabilized hyper-singular integral equation on polygonal/polyhedral Lipschitz domains is analyzed. We prove local a priori estimates in for Symm's integral equation and in for the hypersingular equation. The local rate of convergence is limited by the local regularity of the sought solution and the sum of the global regularity and additional regularity provided by the shift theorem for a dual problem.
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Abstract
The local behavior of the lowest order boundary element method on quasi-uniform meshes for Symm’s integral equation and the stabilized hyper-singular integral equation on polygonal/polyhedral Lipschitz domains is analyzed. We prove local a priori estimates in for Symm’s integral equation and in for the hypersingular equation. The local rate of convergence is limited by the local regularity of the sought solution and the sum of the global regularity and additional regularity provided by the shift theorem for a dual problem.
Local convergence of the boundary element method on polyhedral domains
**Markus Faustmann, Jens Markus Melenk
**Institute for Analysis and Scientific Computing
Vienna University of Technology
Wiedner Hauptstr. 8-10, 1040 Wien, Austria
[email protected], [email protected]
1 Introduction
The boundary element method (BEM) for the discretization of boundary integral equation is an established numerical method for solving partial differential equations on (un)bounded domains. As an energy projection method, the Galerkin BEM is, like the finite element method (FEM), (quasi-)optimal in some global norm. However, often the quantity of interest is not the error on the whole domain, but rather a local error on part of the computational domain.
For the FEM, the analysis of local errors goes back at least to [NS74]; advanced versions can be found in [Wah91, DGS11]. For Poisson’s problem, the local error estimates typically have the form
[TABLE]
where is the exact solution, the finite element approximation from a space of piecewise polynomials, and are open subsets of with . Thus, the local error in the energy norm is bounded by the local best approximation on a larger domain and the error in the weaker -norm. The local best approximation allows convergence rates up to the local regularity; the -error is typically controlled with a duality argument and limited by the regularity of the dual problem as well as the global regularity of the solution. Therefore, if the solution is smoother locally, we can expect better rates of convergence for the local error.
Significantly fewer works study the local behavior of the BEM. The case of smooth two dimensional curves is treated in [Sar87, Tra95], and in [ST96] three dimensional screen problems are studied. [RW85, RW88] provide estimates in the -norm on smooth domains. However, for the case of piecewise smooth geometries such as polygonal and polyhedral domains, sharp local error estimates that exploit the maximal (local) regularity of the solution are not available. Moreover, the analyses of [Sar87, Tra95, ST96] are tailored to the energy norm and do not provide optimal local estimates in stronger norms.
In this article, we obtain sharp local error estimates for lowest order discretizations on quasi-uniform meshes for Symm’s integral equation in the -norm and for the (stabilized) hyper-singular integral equation in the -seminorm on polygonal/polyhedral domains. Structurally, the local estimates are similar to (1.1): The local error is bounded by a local best approximation error and a global error in a weaker norm. More precisely, our local convergence rates depend only on the local regularity and the sum of the global regularity and the additional regularity of the dual problem on polygonal/polyhedral domains. Numerical examples show the sharpness of our analysis. As discussed in Remark 2.4 below, our results improve [Sar87, Tra95, ST96] as estimates in (for Symm’s equation) and (for the hyper-singular equation) are obtained there from local energy norm estimates with the aid of inverse estimates, thereby leading to a loss of . In contrast, we avoid using an inverse inequality to go from the energy norm to a stronger norm.
The paper is structured as follows. We start with some notations and then present the main results for both Symm’s integral equation and the hyper-singular integral equation in Section 2. In Section 3 we are concerned with the proofs of these results. First, some technical preliminaries that exploit the additional regularity on piecewise smooth geometries to prove some improved a priori estimates for solutions of Poisson’s equation as well as for the boundary integral operators are presented. Then, we prove the main results, first for Symm’s equation, then for the stabilized hyper-singular equation. In principle, the proofs take ideas from [Wah91], but due to the non-locality of the BEM solutions, important modifications are needed. However, similarly to [Wah91] a key step is to apply interior regularity estimates, provided recently by [FMP16, FMP15], and to use some additional smoothness of localized boundary integral operators (commutators). Finally, Section 4 provides numerical examples that underline the sharpness of our theoretical local a priori estimates.
1.1 Notation on norms
For open sets , we define the integer order Sobolev spaces , , in the standard way [McL00, p. 73ff]. The fractional Sobolev space , , are defined by the Slobodeckii norm as described in [McL00, p. 73ff]. The spaces , , consist of those function whose zero extension to is in . The spaces , , are taken to be the dual space of . We will make use of the fact that for bounded Lipschitz domains
[TABLE]
For Lipschitz domains with boundary we define Sobolev spaces with as described in [McL00, p. 96ff] using local charts. For , we define the spaces in a non-standard way: consists of those functions that have a lifting to , and we define the norm by
[TABLE]
Correspondingly, there is a lifting operator
[TABLE]
with the lifting property , which is by definition of the norm (1.3) bounded. The spaces , , are the duals of . Their norm is defined as
[TABLE]
Remark 1.1** (equivalent norm definitions)**
- (i)
For an equivalent definition of the norm in (1.3) would be to replace with , i.e.,
[TABLE]
This follows from the existence of the universal extension operator described in **[Ste70, Chap. VI.3]**, which asserts that is also a bounded linear operator for any . 2. (ii)
The trace operator is a continuous operator for (cf. **[McL00, Thm. 3.38]**, **[SS11, Thm. 2.6.8]**). **[SS11, Thm. 2.6.11]** (cf. also **[McL00, Thm. 3.37]**) assert the existence of a continuous lifting in the range as well so that (1.3) is an equivalent norm for as well. 3. (iii)
For polygonal (in 2D) and polyhedral (in 3D) Lipschitz domains the spaces in the range can be characterized alternatively as follows: Let , , be the affine pieces of , which may be identified with an interval (for the 2D case) or a polygon (for the 3D case). Then
[TABLE]
The equivalence (1.5) gives rise to yet another norm equivalence for the space , namely, .
*The condition is a compatibility condition. More generally, for similar, more complicated compatibility conditions can be formulated to describe the space in terms of piecewise Sobolev spaces.
Finally, we will need local norms on the boundary. For an open subset and , we define local negative norms by
[TABLE]
In the following, we write for the interior trace operator, i.e., the trace operator from the inside of the domain and for the exterior trace operator. For the jump of the trace of a function we use the notation . In order to shorten notation, we write for the trace, if the interior and exterior trace are equal, i.e., .
We denote the interior and exterior conormal derivative by , , with the interior and exterior normal vectors . The jump of the normal derivative across the boundary is defined by , and we write for the normal derivative if .
2 Main Results
We study bounded Lipschitz domains , with polygonal/polyhedral boundary .
2.1 Symm’s integral equation
The elliptic shift theorem for the Dirichlet problem is valid in a range that is larger than for general Lipschitz domains. We characterize this extended range by a parameter that will pervade most of the estimates of the present work. It is defined by the following assumption:
Assumption 1
, is a bounded Lipschitz domain whose boundary consists of finitely many affine pieces (i.e., is the intersection of finitely many half-spaces). is such that the open ball of radius that is centered at the origin contains . The parameter is such that for every there is such that the a priori bound
[TABLE]
holds, where denotes the solution of
[TABLE]
The norms , are understood as the sum of the norm on and , i.e.,
[TABLE]
Remark 2.1
The condition on the parameter in Assumption 1 can be described in terms of two Dirichlet problems, one posed on and one posed on . For each of these two domains, a shift theorem is valid, and is determined by the more stringent of the two conditions. It is worth stressing that the type of boundary condition on is not essential in view of the smoothness of and .
In the case the parameter is determined by the extremal angles of the polygon . Specifically, let , , be the interior angles of the polygon . Then, Assumption 1 is valid for any that satisfies
[TABLE]
*(Note that for all so that the right inequality is indeed strict.) *
We consider Symm’s integral equation in its weak form: Given find such that
[TABLE]
Here, the single-layer operator is given by
[TABLE]
where, with the surface measure of the Euclidean sphere in , we set
[TABLE]
The single layer operator is a bounded linear operator in for , [SS11, Thm. 3.1.16]. It is elliptic for with the usual proviso for that , which we can assume by scaling.
Let be a quasiuniform, regular and -shape regular triangulation of the boundary . By we denote the space of piecewise constants on the mesh . The Galerkin formulation of (2.3) reads: Find such that
[TABLE]
The following theorem is one of the main results of this paper. It estimates the Galerkin error in the -norm on a subdomain by the local best approximation error in on a slightly larger subdomain and the global error in a weaker norm.
Theorem 2.2
Let Assumption 1 hold and let be a quasiuniform, -shape regular triangulation. Let and satisfy the Galerkin orthogonality condition
[TABLE]
Let , be open subsets of with and . Let be sufficiently small such that at least with a fixed constant depending only on . Assume that . Then, we have
[TABLE]
The constant depends only on and the -shape regularity of .
If we additionally assume higher local regularity as well as some (low) global regularity of the solution , this local estimate implies that the local error converges faster than the global error, which is stated in the following corollary.
Corollary 2.3
Let the assumptions of Theorem 2.2 be fulfilled. Let be a subset with and . Additionally, assume with , . Then, we have
[TABLE]
with a constant depending only on , and the -shape regularity of .
In the results of [NS74, Wah91] singularities far from the domain of interest have a weaker influence on the local convergence for the FEM. Corollary 2.3 shows that this is similar in the BEM. Singularities either of the solution (represented by ) or the geometry (represented by ) are somewhat smoothed on distant parts of the boundary, but still persist even far away.
Remark 2.4
*In comparison to [ST96], Corollary 2.3 gives a better result for the rate of convergence of the local error in the case where the convergence is limited by the global error in the weaker norm. More precisely, for the case , [ST96] obtains the local rate of , which coincides with our local rate. However, if , we obtain a rate of in the -norm, whereas the rate in [ST96] remains at . *
Remark 2.5
Even for smooth functions , the solution of (2.3) is, in general, not better than with . Recall from Remark 2.1 that is determined by the mapping properties for both the interior and the exterior Dirichlet problem. A special situation therefore arises if Symm’s integral equation is obtained from reformulating an interior (or exterior) Dirichlet problem. To be specific, consider again the case of a polygon with interior angles , . We rewrite the boundary value problem in with as the integral equation
[TABLE]
*for the unknown function with the double layer operator defined by . Then, for any with . *
2.2 The hyper-singular integral equation
For the Neumann problem, we assume an extended shift theorem as well.
Assumption 2
, is a bounded Lipschitz domain whose boundary consists of finitely many affine pieces (i.e., is the intersection of finitely many half-spaces). is such that the open ball of radius that is centered at the origin contains . The parameter , where is the parameter from Assumption 1, is such that for every there is such that for all and with the a priori bound
[TABLE]
holds, where denotes the solution of
[TABLE]
The condition on the parameter again can be described in terms of two problems, a pure Neumann problem posed in , for which we need a compatibility condition, and a mixed Dirichlet-Neumann problem posed on , which is uniquely solvable without the need to impose a solvability condition for .
The parameter again depends only on the geometry and the corners/edges that induce singularities. In fact, on polygonal domains, i.e., , , see, e.g., [Dau88].
Studying the inhomogeneous Neumann boundary value problem , , leads to the boundary integral equation of finding such that with satisfying the compatibility condition and the hyper-singular integral operator defined by
[TABLE]
We additionally assume that is connected, so that the hyper-singular integral operator has a kernel of dimension one consisting of the constant functions. Therefore, the boundary integral equation is not uniquely solvable. Employing the constraint leads to the stabilized variational formulation
[TABLE]
which has a unique solution , see, e.g., [Ste08].
For the Galerkin discretization we employ lowest order test and trial functions in , which leads to the discrete variational problem of finding such that
[TABLE]
The following theorem presents a result analogous to Theorem 2.2 for the hyper-singular integral equation. The local error in the -seminorm is estimated by the local best approximation error and the global error in a weak norm.
Theorem 2.6
Let Assumption 2 hold and let be a quasiuniform, -shape regular triangulation. Let and satisfy the Galerkin orthogonality condition
[TABLE]
Let , be open subsets of with and . Let be sufficiently small such that at least with a fixed constant depending only on . Assume that . Then, we have
[TABLE]
The constant depends only on and the -shape regularity of .
Again, assuming additional regularity, the local estimate of Theorem 2.6 leads to a faster rate of local convergence of the BEM for the stabilized hyper-singular integral equation.
Corollary 2.7
Let the assumptions of Theorem 2.6 be fulfilled. Let be a subset with , . Additionally, assume with , . Then, we have
[TABLE]
with a constant depending only on , and the -shape regularity of .
3 Proof of main results
This section is dedicated to the proofs of Theorem 2.2, Corollary 2.3 for Symm’s integral equation and Theorem 2.6 and Corollary 2.7 for the hyper-singular integral equation.
We start with some technical results that are direct consequences of the assumed shift theorems from Assumption 1 for the Dirichlet problem and Assumption 2 for the Neumann problem.
3.1 Technical preliminaries
The shift theorem of Assumption 1 implies the following shift theorem for Dirichlet problems:
Lemma 3.1
Let the shift theorem from Assumption 1 hold and let be the solution of the inhomogeneous Dirichlet problem in , on for some .
- (i)
There is a constant depending only on and such that
[TABLE] 2. (ii)
Let and be nested subdomains with . Let be a cut-off function satisfying on , , and for . Assume . Then
[TABLE]
Here, the constant additionally depends on .
Proof: Proof of (i): Let solve in , on for . Then, in view of (1.2),
[TABLE]
Integration by parts on and leads to
[TABLE]
We split the polygonal boundary into its (smooth) faces and prolong each face to the hyperplane , which decomposes into two half spaces . Let be the characteristic function for . Since the normal vector on a face does not change, we may use the trace estimate (note: ) facewise, to estimate
[TABLE]
As the boundary is smooth, standard elliptic regularity yields . This leads to
[TABLE]
where the last inequality follows from Assumption 1.
Proof of (ii): With the bounded lifting operator from (1.4), the function satisfies
[TABLE]
With the shift theorem from Assumption 1 we get
[TABLE]
which proves the second statement.
The following lemma collects mapping properties of the single-layer operator that exploits the present setting of piecewise smooth geometries:
Lemma 3.2
Define the single layer potential by
[TABLE]
- (i)
The single layer potential is a bounded linear operator from to for . 2. (ii)
The single-layer operator is a bounded linear operator from to for . 3. (iii)
The adjoint double-layer operator is a bounded linear operator from to for .
Proof: Proof of (i): The case is shown in [SS11, Thm. 3.1.16], and for we refer to [Ver84]. For the case , we exploit that is piecewise smooth. We split the polygonal boundary into its (smooth) faces . Let be the characteristic function for . Then, for , we have . We prolong each face to the hyperplane , which decomposes into two half spaces . Due to , we have . Since the half spaces are smooth, we may use the mapping properties of on smooth geometries, see, e.g., [McL00, Thm. 6.13] to estimate
[TABLE]
Proof of (ii): The case is taken from [SS11, Thm. 3.1.16]. For the result follows from part (i) and the definition of the norm given in (1.3).
Proof of (iii): The case is taken from [SS11, Thm. 3.1.16]. With the case follows from part (i) and a facewise trace estimate (3.3) since
[TABLE]
which finishes the proof.
In addition to the single layer operator , we will need to understand localized versions of these operators, i.e., the properties of commutators. For a smooth cut-off function we define the commutators
[TABLE]
Since the singularity of the Green’s function at is smoothed by , we expect that the commutators , have better mapping properties than the single-layer operator, which is stated in the following lemma.
Lemma 3.3
Let be fixed.
- (i)
The commutator is a skew-symmetric and continuous mapping for all . 2. (ii)
The commutator is a symmetric and continuous mapping .
In both cases, the continuity constant depends only on , , and the constants appearing in Assumption 1.
Proof: Proof of (i): Since is symmetric, we have
[TABLE]
i.e., the skew-symmetry of the commutator . A similar computation proves the symmetry of the commutator .
Let , , and with the single-layer potential . Since the volume potential is harmonic and in view of the jump relations , satisfied by , c.f. [SS11, Thm. 3.3.1], we have
[TABLE]
We may write with the Newton potential
[TABLE]
since and have the same decay for . The mapping properties of the Newton potential (see, e.g., [SS11, Thm. 3.1.2]), as well as the mapping properties of of Lemma 3.2, (i) provide
[TABLE]
The definition of and the definition of the norm from (1.3) prove the mapping properties of for . The skew-symmetry of directly leads to the mapping properties for the case .
Using different mapping properties of the Newton potential (see, e.g., [SS11, Thm. 3.1.2]), we may also estimate in the same way
[TABLE]
Proof of (ii): Let . Since
[TABLE]
the function solves
[TABLE]
Again, the function and the Newton potential have the same decay for , and the mapping properties of the Newton potential as well as the previous estimate (3.9) for provide
[TABLE]
We apply Lemma 3.1 to . Since we have that is smooth on , and we can estimate this term by an arbitrary negative norm of on to obtain
[TABLE]
The additional mapping properties of of Lemma 3.2, (ii) and the symmetry of imply
[TABLE]
Inserting this in (3.10) leads to
[TABLE]
which, together with the definition of the -norm from (1.3), proves the lemma.
The shift theorem for the Neumann problem from Assumption 2 implies the following shift theorem.
Lemma 3.4
Let the shift theorem from Assumption 2 hold, and let be the solution of the inhomogeneous problems
[TABLE]
where with , and .
- (i)
There is a constant depending only on and such that
[TABLE] 2. (ii)
Let . Let be nested subdomains with and be a cut-off function satisfying on , , and for . Assume . Then
[TABLE]
Here, the constant depends on , and .
Proof: Proof of (i): Let solve
[TABLE]
for and . Then, with we have
[TABLE]
Integration by parts on and leads to
[TABLE]
The definition of the norm (1.3) implies
[TABLE]
and the same estimate holds for . Since is smooth, we may estimate
[TABLE]
This leads to
[TABLE]
where the last inequality follows from Assumption 2.
Proof of (ii): Since on , the function satisfies
[TABLE]
With the shift theorem from Assumption 2 we get with the trace inequality that
[TABLE]
which proves the second statement.
The following lemma collects mapping properties of the double-layer operator and the hyper-singular operator that exploit the present setting of piecewise smooth geometries:
Lemma 3.5
Define the double layer potential by
[TABLE]
- (i)
The double layer potential is a bounded linear operator from to for . 2. (ii)
The double layer operator is a bounded linear operator from to for . 3. (iii)
The hyper singular operator is a bounded linear operator from to for .
Proof: Proof of (i): With the mapping properties of the single layer potential from Lemma 3.2, the mapping properties of the solution operator of the Dirichlet problem from Assumption 1 (), and the assumption , the mapping properties of follow from Green’s formula by expressing in terms of , , and the Newton potential . For details, we refer to [SS11, Thm. 3.1.16], where the case is shown.
Proof of (ii): The case is taken from [SS11, Thm. 3.1.16]. For the result follows from part (i), the definition of the norm given in (1.3), and .
Proof of (iii): The case is taken from [SS11, Thm. 3.1.16]. Since , we get with a facewise trace estimate as in the proof of Lemma 3.1, estimate (3.3), that
[TABLE]
which finishes the proof for the case . With the symmetry of , the case follows.
For a smooth function , we define the commutators
[TABLE]
By the mapping properties of , both operators map . However, is in fact an operator of order [math] and is an operator of positive order:
Lemma 3.6
Fix .
- (i)
Let . Then, the commutator can be extended in a unique way to a bounded linear operator that satisfies the bound
[TABLE]
The constant depends only on and the choice of . Furthermore, the operator is skew-symmetric (with respect to the extended -inner product). 2. (ii)
The commutator is a symmetric and continuous mapping . The continuity constant depends only on , , and the constants appearing in Assumption 2.
Proof: Proof of (i): 1. step: We show (3.16) for the range . For , consider the potential with the single layer potential and the double layer potential from (3.13).
Using the jump conditions , for and additionally the jump relations , satisfied by from [SS11, Thm. 3.3.1], we observe that the function solves
[TABLE]
The decay of - the dominant part is the single-layer potential - and the Newton potential for are the same, which allows us to write . With the mapping properties of the Newton potential and the standard mapping properties of from [SS11, Thm. 3.1.16] it follows that
[TABLE]
The trace estimate applied facewise as in the proof of Lemma 3.1, estimate (3.3), and (3.17) lead to
[TABLE]
Furthermore, using Lemma 3.2, (i) we arrive at
[TABLE]
Next, we identify . With , , , we compute
[TABLE]
Recalling the mapping property and the relation we get with the aid of (3.18), (3.19)
[TABLE]
2. step: Since is dense in , , the operator can be extended (in a unique way) to a bounded linear operator .
3. step: The operator is skew-symmetric: The operator maps and is symmetric. The skew-symmetry of then follows from a direct calculation.
4. step: The skew-symmetry of allows us to extend (in a unique way) the operator as an operator for by the following argument: For , we compute
[TABLE]
Since for , we see that, on the right-hand side of (3.21) extends to a bounded linear functional on . Hence, for .
5. step: We have for . An interpolation argument allows us to extend the boundedness to the remaining case .
Proof of (ii): Since
[TABLE]
the function . solves
[TABLE]
Again, the decay of and the Newton potential applied to the right-hand side of the equation are the same, and the mapping properties of the Newton potential provide
[TABLE]
We apply Lemma 3.4 to . Since we have that is smooth on , and we can estimate this term by an arbitrary negative norm of on to obtain
[TABLE]
The mean value can be estimated with , the observation , and integration by parts by
[TABLE]
where the last step follows since is a bounded operator mapping from Lemma 3.2. The additional mapping properties of of Lemma 3.5, (iii) and inserting this in (3.22) leads together with a facewise trace estimate to
[TABLE]
Now, the computation
[TABLE]
the mapping properties of and the commutator of (as normal trace of the commutator from Lemma 3.3, c.f. (3.8)) prove the lemma.
3.2 Symm’s integral equation (proof of Theorem 2.2)
The main tools in our proofs are the Galerkin orthogonality
[TABLE]
and a Caccioppoli-type estimate for discrete harmonic functions that satisfy the orthogonality
[TABLE]
More precisely, the space of discrete harmonic functions on an open set is defined as
[TABLE]
Proposition 3.7
[FMP16, Lemma 3.9]** For discrete harmonic functions , the interior regularity estimate
[TABLE]
holds, where and are nested boxes and satisfies . The hidden constant depends only on , and the -shape regularity of .
As a consequence of this interior regularity estimate and Lemma 3.1, we get an estimate for the jump of the normal derivative of a discrete harmonic potential.
Lemma 3.8
Let Assumption 1 hold and be nested boxes with and be sufficiently small so that the assumption of Proposition 3.7 holds. Let with and assume . Let and be an arbitrary cut-off function satisfying on . Then,
[TABLE]
The constant depends only on , the -shape regularity of , , and the constants appearing in Assumption 1.
**Proof: **We split the function , where the near field and the far field solve the Dirichlet problems
[TABLE]
We first consider - the case is treated analogously.
Let be another cut-off function satisfying on and . The multiplicative trace inequality, see, e.g., [Mel05, Thm. A.2], implies for any that
[TABLE]
Since , we use the interior regularity estimate (3.24) for the first term on the right-hand side of (3.28), and the second term of (3.28) can be estimated using (3.2) of Lemma 3.1. In total, we get for that
[TABLE]
Let be the nodal interpolation operator. The mapping properties of from Lemma 3.2, (ii), the commutator from (3.5) as well as an inverse inequality, see, e.g., [GHS05, Thm. 3.2], lead to
[TABLE]
With the classical a priori estimate for the inhomogeneous Dirichlet problem in the -norm, the commutator , and Lemma 3.3, we estimate
[TABLE]
We apply (3.1), (since on only the boundary terms for appear) together with Young’s inequality applied with , to obtain
[TABLE]
Similarly, we get for the second term in (3.29)
[TABLE]
Inserting everything in (3.29) and using gives
[TABLE]
Applying the same argument for the exterior Dirichlet boundary value problem leads to an estimate for the jump of the normal derivative
[TABLE]
It remains to estimate the far field , which can be treated similarly to the near field using a trace estimate and Lemma 3.1. Applying Lemma 3.1 with a cut-off function satisfying on and the boundary term in (3.2) disappears since , which simplifies the arguments:
[TABLE]
which proves the lemma.
We use the Galerkin projection , which is, for any , defined by
[TABLE]
We denote by the -orthogonal projection given by
[TABLE]
This operator has the following super-approximation property, [NS74]: For any discrete function and a cut-off function we have (with implied constants depending on )
[TABLE]
The following lemma provides an estimate for the local Galerkin error and includes the key steps to the proof of Theorem 2.2.
Lemma 3.9
Let the assumptions of Theorem 2.2 hold. Let be an open subset of with and . Let be sufficiently small such that at least . Assume that . Then, we have
[TABLE]
The constant depends only on and the -shape regularity of .
**Proof: **We define , open subsets , and volume boxes , where . Throughout the proof, we use multiple cut-off functions , . These smooth functions should satisfy on , and . We write
[TABLE]
With the Galerkin projection from (3.33), we obtain
[TABLE]
With an inverse inequality and the -orthogonal projection , which satisfies the super-approximation property (3.34) for , we get
[TABLE]
where the last estimate follows from Céa’s lemma and super-approximation. The same argument leads to
[TABLE]
In fact, this argument shows -stability of :
[TABLE]
The bounds (3.37), (3.38) together imply
[TABLE]
For the first term on the right-hand side of (3.36), we want to use Lemma 3.8. Since for any discrete function , we need to construct a discrete function satisfying the orthogonality condition (3.24). Using the Galerkin orthogonality with test functions with support and noting that on , we obtain with the commutator defined in (3.5)
[TABLE]
Thus, defining
[TABLE]
we get on the volume box a discrete harmonic function
[TABLE]
The correction can be estimated using the -stability (3.39) of the Galerkin projection, the mapping properties of , , and the commutator from Lemma 3.3 by
[TABLE]
We write
[TABLE]
For the second term in (3.44) we use
[TABLE]
We treat the first term in (3.44) as follows: We apply Lemma 3.8 with the boxes and - since we assumed , the condition can be fulfilled - to the discrete harmonic function and the cut-off function . The jump condition leads to
[TABLE]
The definition of , the bound (3.43), and the -stability of the Galerkin projection lead to
[TABLE]
With the -stability (3.39) of the Galerkin projection and (3.43) we get
[TABLE]
We use the orthogonality of on expressed in (3.24) and the -orthogonal projection to estimate
[TABLE]
Inserting (3.47)–(3.2) in (3.46) and using , we arrive at
[TABLE]
Combining (3.36), (3.44) with (3.40), (3.45), (3.50), and finally (3.35), we get
[TABLE]
Since we only used the Galerkin orthogonality as a property of the error , we may write for arbitrary and we have proven the inequality claimed in Lemma 3.9.
In order to prove Theorem 2.2, we need a lemma:
Lemma 3.10
For every there is a bounded linear operator with the following properties:
- (i)
(stability): For every there is (depending only on , , ) such that for all . 2. (ii)
(locality): for the restriction depends only on with . 3. (iii)
(approximation): For every there is (depending only on , , ) such that for all .
**Proof: **Operators with such properties are obtained by the usual mollification procedure (on a length scale for domains in ). This technique can be generalized to the present setting of surfaces with the aid of localization and charts.
Now, we can prove our main result, a local estimate for the Galerkin-boundary element error for Symm’s integral equation in the -norm.
**Proof of Theorem 2.2: ** Starting with Lemma 3.9, it remains to estimate the two terms and , where .
We start with the latter. Let be a cut-off-function with on , and . Let be another cut-off function with on and , where . Select with a constant such that the operator of Lemma 3.10 has the support property . We will employ the operator with the -orthogonal projection . It is easy to see that we may assume that
[TABLE]
Concerning the approximation properties, we have
[TABLE]
With the definition of the commutators , , the Galerkin orthogonality satisfied by , and the fact that is an isomorphism, we get
[TABLE]
The first term on the right-hand side of (3.2) can be treated in the same way as the term from the right-hand side of Lemma 3.9.
We set . The assumption allows us to define nested domains , such that , . Since the term again contains a local -norm, we may use Lemma 3.9 and (3.2) again on the larger set to estimate
[TABLE]
Inserting this into the initial estimate of Lemma 3.9 (using ) leads to
[TABLE]
Now, the -term on the right-hand side is multiplied by , i.e., the square of the initial factor. Iterating this argument -times, provides the factor , and by choice of , we have . Together with an inverse estimate we obtain
[TABLE]
which proves the theorem.
**Proof of Corollary 2.3: ** The assumption leads to
[TABLE]
where the second estimate is the standard global error estimate for the BEM, see [SS11].
It remains to estimate , which is treated with a duality argument: We note that Assumption 1 and the jump relations imply the following shift theorem for : If and solves , then and . Hence
[TABLE]
Therefore, the term of slowest convergence has an order of , which proves the Corollary.
Remark 3.11
The term of slowest convergence in the case of high local regularity is the global error in the negative -norm, which is treated with a duality argument that uses the maximum amount of additional regularity on the polygonal/polyhedral domain. Therefore, further improvements of the convergence rate cannot be achieved with our method of proof. In fact, the numerical examples in the next section confirm this observation, i.e., that the best possible convergence is .
*The trivial estimate immediately implies that the local convergence in the energy norm is at least of order as well. Again, analyzing the proof of Lemma 3.9, we observe that an improvement is impossible, since the limiting term is once more in the negative -norm. *
Remark 3.12
Remark 3.11 states that the local rate of convergence is limited by the shift theorem of Assumption 1. If the geometry is smooth, then elliptic shift theorems for the Dirichlet problem hold in a wider range, e.g., if , we may get . It can be checked that in this setting, an estimate of the form
[TABLE]
*is possible since the commutator in (3.43) maps in this case. If an even better shift theorem holds, then the -norm can be further weakened by using commutators of higher order. The best possible achievable local rates are then in for , and in the -norm. *
3.3 The hyper-singular integral equation (proof of Theorem 2.6)
We start with the Galerkin orthogonality
[TABLE]
and a Caccioppoli-type estimate on for functions characterized by the orthogonality
[TABLE]
for some . Here, we define the space of discrete harmonic functions for an open set and as
[TABLE]
Proposition 3.13
[FMP15, Lemma 3.8]** For discrete harmonic functions , we have the interior regularity estimate
[TABLE]
where and are nested boxes and satisfies . The hidden constant depends only on , and the -shape regularity of .
Again we use the Galerkin projection now defined by
[TABLE]
The following lemma collects approximation properties of the Galerkin projection. These properties will be applied in both Lemma 3.16 and Lemma 3.17 below.
Lemma 3.14
Let be the Galerkin projection defined in (3.58) and be cut-off functions, where on . For , we have for
[TABLE]
For ,we have for
[TABLE]
The constant depends only on , the -shape regularity of , and .
**Proof: **Let be a quasi-interpolation operator with approximation properties in the -seminorm, e.g., the Scott-Zhang-projection ([SZ90]). Then, super-approximation (since ) and an inverse inequality, see, e.g., [GHS05, Thm. 3.2], as well as Céa’s lemma imply
[TABLE]
The same argument leads to
[TABLE]
and consequently to the -stability of the Galerkin-projection.
In the following, we need stability and approximation properties of the Scott-Zhang projection in the space provided by the following lemma.
Lemma 3.15
Let be the Scott-Zhang projection defined in [SZ90]. Then, for we have
[TABLE]
and therefore, for every
[TABLE]
The constants , depend only on , the -shape regularity of , and , .
**Proof: **We start with the proof of (3.61). The stability for the case is given in [SZ90] and the stability for the case (note that is a closed surface without boundary) is discussed in [AFF*+*15, Lemma 7]. By interpolation, (3.61) follows for . The starting point for the proof of (3.61) for is that, by Remark 1.1, (iii), we may focus on a single affine piece of and can exploit that the notion of coincides with the standard notion on intervals (in 1D) and polygons (in 2D). In particular, can be defined as the interpolation space between and .
Since , Remark 1.1, (iii) implies for
[TABLE]
It therefore suffices to show .
Since is an interpolation space between and , we can find (cf. [BS78]), for every , a function with
[TABLE]
Let be an approximation operator with the simultaneous approximation property
[TABLE]
see, e.g., [BS78], [BS02, Thm. 14.4.2]. With an inverse inequality, cf. [DFG*+*01, Appendix], the -stability of the Scott-Zhang projection, and (3.3), (3.64), we estimate
[TABLE]
Choosing , we get the -stability of and thus also the -stability of .
We only prove the approximation property (3.62) for as the case is covered by standard properties of the Scott-Zhang operator.
Case : we observe with the stability properties of and the approximation properties of
[TABLE]
Case : we observe with the stability properties of and the approximation properties of
[TABLE]
Case : The remaining cases are obtained with the aid of an interpolation inequality:
[TABLE]
which concludes the proof.
Lemma 3.16
Let Assumption 2 hold and be nested boxes with and be sufficiently small so that the assumption of Proposition 3.13 holds. Let with and assume for the box and some . Let . Then,
[TABLE]
The constant depends only on , the -shape regularity of , , and the constants appearing in Assumption 2.
Proof: Step 1: Splitting into near and far-field.
Let be a cut-off function satisfying on and . We define the near-field and the far field as potentials , with , , where are BEM solutions of
[TABLE]
with . Here, is a function with on such that the compatibility condition holds. Since such a function exists. More precisely, we choose to be the piecewise constant function
[TABLE]
The function solves
[TABLE]
which implies for a constant . Therefore, . Since this implies
[TABLE]
The definition of and on lead to
[TABLE]
Consequently, we obtain
[TABLE]
The last inequality follows from the orthogonality of to discrete functions in on and the arguments shown in (3.69) below (specifically: go through the arguments of (3.69) with ).
Step 2: Approximation of the near field.
Let denote the Scott-Zhang projection. The ellipticity of on and the orthogonality (3.55) of imply
[TABLE]
With the same arguments and Lemma 3.15 we may estimate
[TABLE]
Let solve for . Then . Together with the mapping properties of from Lemma 3.5, , the definition of , and the stability and approximation properties of from Lemma 3.15, we obtain
[TABLE]
With the mapping properties of from Lemma 3.5, an inverse estimate, and (3.69) we obtain for
[TABLE]
We first consider - the case is treated analogously. By construction of , we have
[TABLE]
since , on . Therefore, .
Let be another cut-off function satisfying on and . The multiplicative trace inequality, see, e.g., [Mel05, Thm. A.2], implies for any that
[TABLE]
Since , we may use the interior regularity estimate (3.55) with for the first term on the right-hand side of (3.74). The second factor of (3.74) can be estimated using (3.12) of Lemma 3.4. In total, we get for that
[TABLE]
The mapping properties of imply with (3.69) and (3.72)
[TABLE]
We apply (3.11) - has mean zero - and since is smooth on , we can estimate . Together with (3.72), (3.3), and Young’s inequality this leads to
[TABLE]
Similarly, we get for the second term in (3.75)
[TABLE]
Inserting everything in (3.75) and choosing gives
[TABLE]
Applying the same argument for the exterior trace leads to an estimate for the jump of the trace
[TABLE]
Step 3: Approximation of the far field.
We define the function as the solution of
[TABLE]
Then, we have
[TABLE]
Let where and be another cut-off function with on and . Then, with the Galerkin projection , the triangle inequality and the jump conditions of imply
[TABLE]
The smoothness of on and the coercivity of on lead to
[TABLE]
We apply Lemma 3.4 with a cut-off function satisfying on and . Then and on imply and . The -stability of the Galerkin projection from Lemma 3.14, a facewise trace estimate, and similar estimates as for the near field imply
[TABLE]
It remains to estimate the first term on the right-hand side of (3.77). With an inverse estimate and Lemma 3.14 we get
[TABLE]
We use the abbreviation . The ellipticity of on and the definition of the Galerkin projection imply
[TABLE]
With the commutator we get
[TABLE]
The definition of the Galerkin projection and the super-approximation properties of the Scott-Zhang projection lead to
[TABLE]
For the term involving , we get
[TABLE]
A duality argument implies , for details we refer to the proof of Corollary 2.7. Inserting everything in (3.79) leads to
[TABLE]
Finally, this implies with (3.77) and (3.78) that
[TABLE]
which proves the lemma.
Lemma 3.17
Let be solutions of (2.8), (2.9) and let be subsets of with and . Let be sufficiently small such that at least and be an arbitrary cut-off function with on , . Then, we have
[TABLE]
with a constant depending only on , and the -shape regularity of .
**Proof: **We define , subsets , and volume boxes , where . Throughout the proof, we use multiple cut-off functions , . These smooth functions should satisfy on , and .
We want to use Lemma 3.16. Since for any discrete function , we need to construct a discrete function satisfying the orthogonality (3.55). Using the Galerkin orthogonality with test functions with support and noting that on , we obtain with the commutator defined in (3.14), the abbreviation , and the Galerkin projection from (3.58)
[TABLE]
Here and below, we understand the inverse as the inverse of the bijective operator . Since mapps into no additional terms in the orthogonality (3.80) appear. Thus, defining
[TABLE]
we get on a volume box a discrete harmonic function
[TABLE]
where .
With the Galerkin projection from (3.58) and on , we write
[TABLE]
Lemma 3.14 leads to
[TABLE]
Using the -stability of the Galerkin projection , the mapping properties of and as well as Lemma 3.6, the correction can be estimated by
[TABLE]
For the second term on the right-hand side of (3.81) we have . We apply Lemma 3.16 to and obtain
[TABLE]
The -stability of the Galerkin-projection from Lemma 3.14 and (3.83) lead to
[TABLE]
as well as
[TABLE]
With the estimate and previous arguments (using (3.83), Lemma 3.14, and Lemma 3.6), we may estimate
[TABLE]
Inserting (3.85)–(3.87) in (3.84), we arrive at
[TABLE]
Combining (3.82), (3.83), and (3.88) in (3.81), we finally obtain
[TABLE]
Since we only used the Galerkin orthogonality as a property of the error , we may write for arbitrary with and we have proven the claimed inequality.
**Proof of Theorem 2.6: ** Starting from Lemma 3.17, it remains to estimate the terms and and .
The terms are treated as in the proof of Theorem 2.2. Rather than using the operator we may use the Scott-Zhang projection.
**Proof of Corollary 2.7: ** The assumption leads to
[TABLE]
where the second estimate is the standard global error estimate for the Galerkin BEM applied to the hyper-singular integral equation, see [SS11].
For the remaining term, we use a duality argument. Let solve , , where . Then , and since , we get with the Scott-Zhang projection and Lemma 3.15
[TABLE]
Therefore, the term of slowest convergence has an order of , which proves the Corollary.
4 Numerical Examples
In this section we provide some numerical examples to underline the theoretical results of Section 2.
We only consider Symm’s integral equation on quasi-uniform meshes. Provided the right-hand side and the geometry are smooth enough, it is well-known, that the lowest order boundary element method in two dimensions converges in the energy norm with the rate , where denotes the degrees of freedom. In our examples we will consider problems, where the rate of convergence with uniform refinement is reduced due to singularities.
In order to compute the error between the exact solution and the Galerkin approximation, we prescribe the solution of Poisson’s equation in polar coordinates. Then, the normal derivative of is the solution of
[TABLE]
The regularity of is determined by the choice of . In fact, we have , , and locally for all subsets that are a positive distance away from the singularity at the origin.
The lowest order Galerkin approximation to is computed using the MATLAB-library HILBERT ([AEF*+*14]), where the errors in the -norm are computed using two point Gauß-quadrature. The error in the local -norm is computed with , where is the characteristic function for a union of elements .
4.1 Example 1: L-shaped domain
We start with examples in two dimensions on a rotated L-shaped domain visualized in Figure 1.
On the L-shaped domain, the dual problem permits solutions of regularity for arbitrary , so we have .
Figure 2 shows the global convergence rate in the energy norm (blue) as well as the local convergence rates on the red part of the boundary (, union of elements) in the -norm (red) as well as the -norm (brown). The black dotted lines mark the reference curves of order for various .
In the left plot of Figure 2 we chose , which leads to and, indeed, we observe convergence in the local -norm of almost order 1, which coincides with the theoretical rate obtained in Corollary 2.3. The error in the local -norm is smaller than the error in the -norm, but does converge with the same rate, i.e., an improvement of Theorem 2.2 in the energy norm is not possible. The right plot in Figure 2 shows the same quantities for the choice . Obviously, in this case the rates of convergence are lower, and the local -error does not converge with the best possible rate of one, but rather with the expected rate of , as predicted by Corollary 2.3.
4.2 Example 2: Z-shaped domain
For our second example, we change the geometry to a rotated Z-shaped domain visualized in Figure 3. Here, the dual problem permits solutions of regularity with .
We again observe the expected rate of for the global error in the energy norm in Figure 4. However, in contrast to the previous example on the L-shaped domain, we do not obtain a rate of one for the local error in the -norm for the case , but rather a rate of , since . For the choice , we observe a rate of , which once more matches the theoretical rate of .
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