Return to Article Details A defect-correction nodal finite element method for time-dependent Maxwell's equations on polygonal domains

A Defect-Correction nodal Finite Element Method for Time-dependent Maxwell’s equations on Polygonal DomainsThanks: ∗Department of Mathematics, University of Buea, Molyko, Buea, Cameroon, e-mail: nkeck.jake@ubuea.cm, https://orcid.org/0000-0003-0492-8247.

Jake Léonard Nkeck∗
Date: January 06, 2026; accepted: April 15, 2026; published online: May 05, 2026.
Abstract.

This paper develops a nodal finite element Crank-Nicolson method of lines to solve the time-dependent Maxwell’s equations on polygonal domains with re-entrant corners. Nodal Finite Element methods are used to solve Maxwell’s equations with an optimal convergence rate when the domain is convex or has a smooth boundary, but may fail to converge if the domain has a re-entrant corner. The Defect-Correction method presented is based on a decomposition of the solution in terms of Fourier and Bessel’s series, an extraction of the singular function and an approximation of the regular part of the solution. Optimal convergence results are recovered using the method in both the energy norm and the L2-norm.

Key words and phrases: 
Maxwell’s Equations, Crank-Nicolson Method, Re-entrant Corner, Singular function
2005 Mathematics Subject Classification
37A17, 76F02, 76M10, 74S20, 74S25

1. Introduction

Electromagnetic waves are of particular importance in applied physics, engineering, and materials science, for example, in radars, antennas, and the detection of cracks in metals. Electromagnetic phenomena are modeled by a particular system of partial differential equations (PDEs) called Maxwell’s equations or equations of electromagnetism. Maxwell’s equations involve a couple of vector functions (u,b) called electromagnetic field, where u is the electric field and b is the magnetic field.

A general result of numerical methods for PDEs is that the accuracy of approximation depends on the regularity of the unknown solution, see [1, 2, 3, 4]. It is well known that solutions of boundary value problems in domains with corners, cracks, edges and conic vertices may entail singularities, even if the data are smooth. Moreover, the asymptotic behavior of the solution near these geometric singularities has been well studied and the results are now well known, see, for example [5, 6, 7, 8]. However, unlike general elliptic boundary value problems, the solution of Maxwell’s equations in domains with geometric singularities exhibits some regularity properties that make its approximation particularly difficult.

In the case of time-harmonic Maxwell’s equations in a two-dimensional domain Ω with corners and for a given right hand side function in the Hilbert space L2⁢(Ω)2, it has been shown that the solution belongs to the Sobolev space Hm⁢(Ω)2 (m=1,2) only if the value of the largest angle is smaller than π/m, see, for example [9, 10, 11, 12]. It follows that the solution belongs to the space H1⁢(Ω)2 only if Ω is convex and to the space H2⁢(Ω)2 only if the largest angle at the corners is less than π/2. We would say that the solution of the boundary value problem has geometric singularities if for a given right hand side function in L2⁢(Ω)2 the solution belongs only to the Sobolev space Hs⁢(Ω)2 with s<2. It follows that on non-convex domains, the standard H1-conforming FEM cannot be employed for the solution of Maxwell’s equations.

The work of Costabel [13] in 2002 combined with the bilinear form introduced in [14] has allowed the scientific community to renew the nodal FEM for Maxwell’s Equations and some new finite element schemes have been developed in order to recover the convergence rate on non-convex domains. We mention in particular:

  1. -

    The singular field method (SFM) introduced by Hazard and Lenoir [15], Hazard et al. [16, 17]. This method consists in splitting the solution u into two parts u=ur+γs⁢us, with a ”regular part” ur that lies in the usual Sobolev space H1 and a singular part us that lies in a known finite dimensional space and a constant γs to be determined from the finite element linear system. The constant γs is known as the coefficient of singularity. With this method one can approximate the solution in non-convex polygonal domains with nodal FEM but the rate of convergence is still lower than the one on smooth domains because the splitting is not optimal.

  2. -

    The Orthogonal Singular Field Method (OSFM) introduced by Assous et al. [17], where the solution u is again split into two parts u=ur+(ur′+γs⁢us), a regular part ur that lies in a subspace of H1 and the second part (ur′+us) is in a subspace of the space of solutions orthogonal to the regular space. The OSFM and the SFM have the same rate of convergence but the OSFM is more stable due to the omission of the use of cut-off functions present in the SFM for the instabilities due to the use of cut-off functions.

  3. -

    The ”λ-approach” for two-dimensional vector problems developed by Jamelot in 2004 [18], where the splitting u=ur+γs⁢us is done but γs is given by a formula and depends only on the domain and the initial data. This method ameliorates the rate of convergence of the SFM and the OSFM but the rate is still not optimal (of order 𝒪⁡(h2⁢π/ω−1−ε) in the energy norm and 𝒪⁡(h4⁢π/ω−2−ε) in the L2-norm, ω being the greatest value of the angles of the domain).

  4. -

    The weighted regularization developed by Costabel and Dauge [13], where the boundary conditions are multiplied by a weight that depends on the distance to the geometric singularities. In this method each singularity requires the construction of a new weight. It is stated in [19] that this method requires the approximation space to contain the gradient of C1-scalar functions, which excludes low order finite element spaces (C0-finite element spaces for example). This restriction is removed in the work of Buffa et al. [20] by considering a mixed form of the weighted L2-stabilization technique on special meshes. This method has also been simplified by Otin in [21, 22] where the method is performed by using a weight equal to zero in the elements near the singularity and equal to one in the other elements.

  5. -

    The mixed methods with natural boundary conditions developed by Ciarlet Jr. et al.[4]. These methods consist in the dualisation of the equation on the divergence and the relation on the tangential or normal trace of the field with some Lagrange multipliers. Several authors have also contributed to the development of these methods. We highlight the works of Codina et al. [23, 24, 25] where a novel augmented formulation is produced by adding the Laplacian of the Lagrange multiplier multiplied by a mesh dependent stabilizing term to the equation resulting from the dualisation of the divergence equation.

  6. -

    The L2-projection methods developed by Duan and al. [26, 27]. In these methods, L2-projectors are applied to both curl and div formulations and linear continuous finite elements enriched with some higher order bubble functions are employed in order to approximate low regular functions. These methods do not impose information on the geometric singularities of the domain boundary but are still limited to linear continuous elements.

  7. -

    The interior penalty method [19, 28], where the idea consists of controlling the divergence of the electric field in a Sobolev space with fractional negative exponent. The optimal rate of convergence is recovered with this method.

  8. -

    The Predictor-Corrector nodal FEM that makes use of the explicit extraction formulas for the coefficients of the singularities of the solution near the corners ( see [9, 11, 12, 29, 30]). The optimal convergence rate is recovered by the method. The method can be applied with high order finite element polynomials but faces the problem of logarithmic singularities that may easily happen in the case of Maxwell’s equations.

This paper extends the Predictor-Corrector nodal FEM developed for the 2D time-harmonic Maxwell’s equations on convex and non-convex polygonal domains with exactly one re-entrant angle Ω centered at the origin O⁡(0,0). The method is based on a Fourier decomposition of the solution and a defect-correction algorithm to recover the optimal convergence known for Maxwell’s equations on convex polygonal domains or on domains with a 𝒞2-boundary.

This paper is organized as follows, Section 2 presents the Maxwell’s equations on polygonal domains, Section 3 develops a local decomposition of the solution around the singular corner, Section 4 proposes a Defect-Correction FEM with the error estimates in L2- and the energy norm and Section 5 concludes the paper.

2. The Model Problem

Given a vector function v=(v1,v2)T, define the divergence of v by

div v= ∂v1∂x1+∂v2∂x2.
curl⁡v= ∂v2∂x1−∂v1∂x2.

Given a scalar function v, define curl ⁢v by

curl ⁢v= (∂v∂x2,−∂v∂x1).

Define L2⁢(Ω) to be the space of classes of measurable and square integrable functions over Ω equipped with the norm ‖u‖0=(∫Ω|u⁡(x1,x2)|2⁢dx)1/2 that will also denote the norm in the Cartesian product space L2⁢(Ω)2, dx=d⁢x1⁢d⁢x2 being the Lebesgue measure.

H0⁢(curl,Ω) :={v∈L2⁢(Ω)2:curl⁡v∈L2⁢(Ω)⁢ and v∧n=0⁢ on ⁢∂Ω}
H⁡(div,Ω) :={v∈L2⁢(Ω)2:div v∈L2⁢(Ω)}
H⁡(div0,Ω) :={v∈L2⁢(Ω)2:div v=0⁢ in ⁢Ω}
H0⁢(curl,div,Ω) :=H0⁢(curl,Ω)∩H⁡(div,Ω)
Hm⁢(Ω) :={v:∂α1+α2v∂x1α1⁢∂x2α2∈L2(Ω),α1,α2∈ℕ,α1+α2≤m}
HN⁢(Ω) :={v∈H1⁢(Ω)2:v∧n=0⁢ on ⁢Γ}
H01⁢(Ω) :={u∈H1⁢(Ω):u=0⁢ on ⁢Γ}

equipped with the norms

‖v‖curl :=(‖v‖02+‖curl⁡v‖02)1/2
‖v‖div :=(‖v‖02+‖div v‖02)1/2
‖v‖cd :=(‖v‖02+‖curl⁡v‖02+‖div v‖02)1/2
‖v‖m :=(‖v‖02+∑α1,α2≤m‖∂α1+α2v∂x1α1⁢∂x2α2‖02)1/2.
‖v‖HN⁢(Ω) :=‖v‖1=:‖v‖H01⁢(Ω)

where ∥⋅∥m denotes the norm in Hm⁢(Ω) and also the norm in the cartesian product space Hm⁢(Ω)2. The quantity defined by

|v|cd:=(‖curl⁡v‖02+‖div v‖02)1/2

is the semi-norm in H0⁢(curl,div,Ω).

Given an interval I⊂ℝ and a Hilbert space X, 𝒞k⁢(I,X) will denote the space of bounded k-continuously differentiable functions u on I of the form t↦u⁡(⋅,t)∈X equipped with the norm

‖u‖𝒞k=supt∈I,|α|≤k‖∂αu⁡(⋅,t)‖X.

The space Ck⁢(I,X) will denote the space of functions u:=(u1,u2), u1,u2∈𝒞k⁢(I,X) equipped with the norm

‖u‖Ck=(‖u1‖𝒞k2+‖u2‖𝒞k2)1/2.

The space L2⁢(I,X) is the completion of 𝒞0⁢(I,X) with respect to the norm

‖u‖L2⁢(I,X)=(∫I‖u⁡(⋅,t)‖X2⁢𝑑t)12.

The space L2⁢(I,X) is the space of functions u:=(u1,u2), u1,u2∈L2⁢(I,X) equipped with the norm

‖u‖L2⁢(I,X)=(‖u1‖L2⁢(I,X)2+‖u2‖L2⁢(I,X)2)1/2.

The space Hm⁢(I,X), m∈ℕ, m>0 is the space of functions t↦u⁡(⋅,t)∈X such that ∂α1+α2u∂tα1+α2∈L2⁢(I,Ω) with the norm

‖u‖Hm⁢(I,X)=(∫I∑α1+α2≤m‖∂α1+α2u∂tα1+α2‖X2⁢𝑑t)12.

The space Hm⁢(I,X) is the space of functions u:=(u1,u2), u1,u2∈Hm⁢(I,X) equipped with the norm

‖u‖Hm⁢(I,X)=(‖u1‖Hm⁢(I,X)2+‖u2‖Hm⁢(I,X)2)1/2.

Given a simply connected polygonal domain Ω⊂ℝ2 with boundary ∂Ω, a function f:=(f1,f2)T∈H1⁢([0,T],L2⁢(Ω)2) such that div f=0, two functions u0:=(u10,u20)T∈H0⁢(curl,div,Ω)∩H⁡(div0,Ω)∩H2⁢(Ω)2 and u1:=(u11,u21)T∈H⁡(div0,Ω), find u:=(u1,u2)T∈L2⁢(0,T,H0⁢(curl,div,Ω)) such that

(1) κ2⁢∂2u∂t2+curl⁢curl⁢u= f,in⁢Ω×(0,T),
div⁡u= 0,in⁢Ω×(0,T),
u∧n= 0,on⁢∂Ω×(0,T),
u⁢(⋅,0)= u0⁢(⋅),in⁢Ω,
∂u∂t⁢(⋅,0),= u1⁢(⋅),in⁢Ω,

where n=(n1,n2) is the unit outward normal to Ω, T>0 and κ∈ℝ.

Using the formula curl ⁢curl⁡u=−Δ⁢u+∇(div u) one obtains the system

κ2⁢∂2u∂t2−Δ⁢u= f,in⁢Ω×(0,T),
div⁡u= 0,in⁢Ω×(0,T),
(2) u∧n= 0,on⁢∂Ω×(0,T),
u⁢(⋅,0)= u0⁢(⋅),in⁢Ω,
∂u∂t⁢(⋅,0)= u1⁢(⋅),in⁢Ω,

Problem (2) is equivalent to an initial boundary value problem useful for the Lagrange nodal finite element investigation due to the continuity of the finite element functions along the tangential and the normal components. That result is given by the following proposition.

Proposition .

If κ2 is not an eigenvalue of the Laplace operator −Δ⁡(⋅), Problem (2) is equivalent to the following problem:

find u∈L2⁢(0,T,H0⁢(curl,div,Ω)) such that

κ2⁢∂2u∂t2−Δ⁢u= f,in⁢Ω×(0,T),
div⁡u= 0,on⁢∂Ω×(0,T),
(3) u∧n= 0,on⁢∂Ω×(0,T),
u⁢(⋅,0)= u0⁢(⋅),in⁢Ω,
∂u∂t⁢(⋅,0)= u1⁢(⋅),in⁢Ω,
Proof.

A solution of Problem (2) is obviously a solution of Problem (2).

Suppose u is a solution of Problem (2) and let φ=div u, taking the divergence in the first equation of (2), one obtains that φ∈L2⁢(0,T,H01⁢(Ω)) is the unique solution of the Problem

κ2⁢∂2φ∂t2−Δ⁢φ =0,in⁢Ω×(0,T),
(4) φ =0,on⁢∂Ω×(0,T),
φ⁡(⋅,0) =div u0⁢(⋅)=0,in⁢Ω,
∂φ∂t⁢(⋅,0) =div u1⁢(⋅)=0,in⁢Ω,

But Problem (2) has the unique null solution provided that κ2 is not an eigenvalue of the Laplace operator −Δ⁡(⋅), then φ=0 in Ω×(0,T) and u is also a solution of Problem (2). ∎

Taking the inner product of the first, fourth and the fifth equation of Problem (2) with v∈H0⁢(curl,div,Ω), the integral over Ω and using integration by parts lead to the variational problem: find u∈L2⁢(0,T,H0⁢(curl,div,Ω)) such that

κ2⁢d2d⁢t2⁢∫Ωu⋅v⁢dx+a⁡(u,v)= ∫Ωf⋅v⁢dx,∀v∈H0⁢(curl,div,Ω)
(5) ∫Ωu⁢(⋅,0)⋅v⁢dx= ∫Ωu0⋅v⁢dx,∀v∈H0⁢(curl,div,Ω)
∫Ω∂u∂t⁢(⋅,0)⋅v⁢dx= ∫Ωu1⋅v⁢dx,∀v∈H0⁢(curl,div,Ω)

where a⁡(u,v):=∫Ωcurl⁡u⁢curl⁢v+div⁡u⁢div⁢v⁢dx. The following results prove the existence and uniqueness of the solution of the variational problem (2). To prove it, one can apply Theorem 8.1, page 287 of [31].

Proposition \theproposition.

If f∈H1⁢(0,T,H0⁢(curl,div⁡Ω)), u0∈H0⁢(curl,div,Ω)∩H⁡(div0,Ω)∩H2⁢(Ω)2 and u1∈H⁡(div0,Ω), then the variational problem (2) has a unique solution u∈C0⁢([0,T],H0⁢(curl,div,Ω)) such that ∂u∂t belongs to C0⁢([0,T],H⁡(div0,Ω)). Furthermore the solution depends continuously on the data.

3. Decomposition of the Solution

An approximation of the solution of the variational problem (2) involves a particular study of the relation between HN⁢(Ω) and H0⁢(curl,div,Ω). From [16] page 2033, H0⁢(curl,div,Ω)=HN⁢(Ω)⊕∇XS where

XS:={φ∈H01(Ω):∃f∈𝒩:−∫Ω∇φ⋅∇ψdx=∫Ωfψdx∀ψ∈H01(Ω)},

𝒩 being the orthogonal of Δ⁡(H2⁢(Ω)∩H01⁢(Ω)) in L2⁢(Ω).

This introduction allows the decomposition of the solution into a space regular and a space singular part. The geometric singularity being a local problem see [8, p. 71]it is judicious to study the problem in a circular sector.

For sake of simplicity, it is assumed that the domain Ω has only one corner centered at the origin O⁡(0,0) in the (x1,x2)-plane with angle ω>π/2, ω≠π. Introduce the polar coordinates (r,θ) with x1=r⁢cos⁡θ, x2=r⁢sin⁡θ, 0≤θ≤ω. Let R0>0, consider the restriction on a circular sector G0 with

G0¯={(rcosθ,rsinθ):0≤θ≤ω,0≤r≤R0},

and the cut-off function

η(r):={1,if 0≤r<R0/30≤η(r)≤1,if R0/3≤r≤2⁢R0/30,if r>2⁢R0/3.

Set uη:=η⁢u, uη describes the solution u around the corner O⁡(0,0) and uη is the unique solution of the problem: find uη∈L2⁢(0,T,H0⁢(curl,div,G0)) such that

(6) κ2⁢∂2uη∂t2−Δ⁢uη= fη,in⁢G0×(0,T),
(7) div⁡uη= 0,on⁢∂G0×(0,T),
(8) uη∧n= 0,on⁢∂G0×(0,T),
(9) uη⁢(⋅,0)= η⁢u0⁢(⋅),in⁢G0,
(10) ∂uη∂t⁢(⋅,0)= η⁢u1⁢(⋅),in⁢G0,

where

fη:=(ηf1−u1Δη−2∇η⋅∇u1ηf2−u2Δη−2∇η⋅∇u2).

The one-to-one mapping (x1,x2)↦(r,θ) transforms G0 into a rectangle G~0:={(r,θ):0≤r≤R0,0≤θ≤ω} and we can pass through polar coordinates by setting u~⁢(r,θ,t)=uη⁢(x1,x2,t) and f~⁢(r,θ,t)=fη⁢(x1,x2,t)

(uruθ)= (uη⁢1⁢cos⁡θ+uη⁢2⁢sin⁡θ−uη⁢1⁢sin⁡θ+uη⁢2⁢cos⁡θ),(frfθ)=(fη⁢1⁢cos⁡θ+fη⁢2⁢sin⁡θ−fη⁢1⁢sin⁡θ+fη⁢2⁢cos⁡θ)
(ur0u0⁢θ)= (η⁢u10⁢cos⁡θ+η⁢u20⁢sin⁡θ−η⁢u10⁢sin⁡θ+η⁢u20⁢cos⁡θ),(ur1u1⁢θ)=(η⁢u11⁢cos⁡θ+η⁢u21⁢sin⁡θ−η⁢u11⁢sin⁡θ+η⁢u21⁢cos⁡θ),

Problem (6) becomes

(11) κ2⁢∂2ur∂t2−∂2ur∂r2−1r2⁢∂2ur∂θ2−1r⁢∂ur∂r+2r2⁢∂uθ∂θ+1r2⁢ur= fr,in⁢G0~×(0,T)
κ2⁢∂2uθ∂t2−∂2uθ∂r2−1r2⁢∂2ur⁢θ∂θ2−1r⁢∂uθ∂r−2r2⁢∂ur∂θ+1r2⁢uθ= fθ,in⁢G0~×(0,T)
∂ur∂r+1r⁢ur+1r⁢∂uθ∂θ= 0,ur=0,i⁢f⁢θ=0
∂ur∂r+1r⁢ur+1r⁢∂uθ∂θ= 0,ur=0,if⁢θ=ω
|ur⁢(0,θ,t)|<∞,|uθ⁢(0,θ,t)|< ∞,≤t≤T
ur⁢(R0,θ,t)=uθ⁢(R0,θ,t)= 0, 0<θ<ω⁢ 0≤t≤T
ur⁢(⋅,0)=ur0⁢(⋅),uθ⁢(⋅,0)= uθ0⁢(⋅)
∂ur∂t⁢(⋅,0)=ur1⁢(⋅),∂uθ∂t⁢(⋅,0)= uθ1⁢(⋅)

The derivatives are interpreted in the sense of distributions. The boundary conditions at θ=0 and θ=ω allow us to consider the following Fourier decompositions for ur and uθ,

ur⁢(r,θ,t) =∑k=1∞ur⁢k(r,t)sinλkθ, uθ(r,θ,t)=∑k=1∞uθ⁢k(r,t)cosλkθ
fr⁢(r,θ,t) =∑k=1∞fr⁢k(r,t)sinλkθ, fθ(r,θ,t)=∑k=1∞fθ⁢k(r,t)cosλkθ
ur0,1⁢(r,θ) =∑k=1∞ur⁢k0,1(r)sinλkθ, uθ0,1(r,θ)=∑k=1∞uθ⁢k0,1(r)cosλkθ.

where λk=k⁢π/ω, k∈ℕ, k>0. The system (11) becomes

(12) κ2⁢∂2ur⁢k∂t2−∂2ur⁢k∂r2+λkr2⁢ur⁢k−1r⁢∂ur⁢k∂r−2⁢λkr2⁢uθ⁢k+1r2⁢ur⁢k =fr⁢k
κ2⁢∂2uθ⁢k∂t2−∂2uθ⁢k∂r2+λkr2⁢uθ⁢k−1r⁢∂uθ⁢k∂r−2⁢λkr2⁢ur⁢k+1r2⁢uθ⁢k =fθ⁢k
∂ur⁢k∂r+1r⁢ur⁢k−λkr⁢uθ⁢k=0,ur⁢k =0,if⁢θ=0⁢ or ⁢θ=ω
|ur⁢k⁢(0,t)|<∞,|uθ⁢k⁢(0,t)| <∞,0≤t≤T
ur⁢k⁢(R0,t)=uθ⁢k⁢(R0,t) =0,0≤t≤T
ur⁢k⁢(r,0)=η⁡(r)⁢ur⁢k0⁢(r),uθ⁢k⁢(r,0) =η⁢uθ⁢k0⁢(r),0≤r≤R0
∂ur⁢k∂t⁢(r,0)=η⁡(r)⁢ur⁢k1⁢(r),∂uθ⁢k∂t⁢(r,0) =η⁢uθ⁢k1⁢(r),0≤r≤R0

Setting u3⁢k=ur⁢k+uθ⁢k and u4⁢k=ur⁢k−uθ⁢k the first and the second equations of Problem (12) become

(13) κ2⁢∂2u3⁢k∂t2−∂2u3⁢k∂r2+λk2+1r2⁢u3⁢k−1r⁢∂u3⁢k∂r−2⁢λkr2⁢u3⁢k=fr⁢k+fθ⁢kκ2⁢∂2u4⁢k∂t2−∂2u4⁢k∂r2+λk2+1r2⁢u4⁢k−1r⁢∂u4⁢k∂r−2⁢λkr2⁢u4⁢k=fr⁢k−fθ⁢k

The homogeneous equations associated to the equations (13) can be solved by separation of variables by setting ui⁢k⁢(r,t)=φi⁢k⁢(t)⁢ψi⁢k⁢(r), i=3,4 to obtain the equality φi⁢k′′φi⁢k=1κ2⁢ψi⁢k⁢(ψi⁢k′′−(λk−1)2r2⁢ψi+1r⁢ψi⁢k′), i=3,4.

Due to the mixed boundary conditions at t=0 from the two last equalities of (12) and the smoothness of the solution u in time, the operator −d2⁢(⋅)d⁢t2 has positive and discrete eigenvalues αk⁢m2, m∈ℕ, m≥1 arranged in an increasing sequence. One writes φi⁢k′′φi⁢k=1κ2⁢ψi⁢k⁢(ψi⁢k′′−(λk−1)2r2⁢ψi+1r⁢ψi⁢k′)=−αk⁢m2, i=3,4, m∈ℕ, so, the equations ψi⁢k′′+1r⁢ψi⁢k′−((λk−1)2r2−κ2⁢αk⁢m2)⁢ψi=0, i=3,4 lead to ψi⁢k⁢(r)=∑m=1∞C1⁢i⁢m⁢Jλk−1⁢(κ⁢αk⁢m⁢r)+C2⁢i⁢m⁢Yλk−1⁢(κ⁢αk⁢m⁢r), i=3,4 where C1⁢i⁢m, C2⁢i⁢m are constants and the αk⁢m, m∈ℕ, m≥1 form an increasing sequence of positive numbers such that Jλk−1⁢(κ⁢αk⁢m⁢R0)=Yλk−1⁢(κ⁢αk⁢m⁢R0)=0, Jλk−1 and Yλk−1 are the Bessel functions of the first and second kind respectively.

The boundary conditions |ur⁢k⁢(0,t)|<∞ and |uθ⁢k⁢(0,t)|<∞ in Problem (12) imply that C2⁢i⁢m=0, i=3,4, m∈ℕ, m≥1. Then

ur⁢k⁢(r,t)=∑m=1∞ur⁢k⁢m⁢(t)⁢Jλk−1⁢(κ⁢αk⁢m⁢r), uθ⁢(r,t)=∑m=1∞uθ⁢k⁢m⁢(t)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)
fr⁢k⁢(r,t)=∑m=1∞fr⁢k⁢m⁢(t)⁢Jλk−1⁢(κ⁢αk⁢m⁢r), fθ⁢k⁢(r,t)=∑m=1∞fθ⁢k⁢m⁢(t)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)
ur⁢k0⁢(r)=∑m=1∞ur⁢k⁢m0⁢Jλk−1⁢(κ⁢αk⁢m⁢r), uθ⁢k0⁢(r)=∑m=1∞uθ⁢k⁢m0⁢Jλk−1⁢(κ⁢αk⁢m⁢r)
ur⁢k1⁢(r)=∑m=1∞ur⁢k⁢m1⁢Jλk−1⁢(κ⁢αk⁢m⁢r), uθ⁢k1⁢(r)=∑m=1∞uθ⁢k⁢m1⁢Jλk−1⁢(κ⁢αk⁢m⁢r)

where

fr⁢k⁢m⁢(t)= 1∥Jλk−1(καk⁢m⋅)∥02⁢∫0R0fr⁢k⁢(r,t)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢r⁢𝑑r
= 2ω∥Jλk−1(καk⁢m⋅)∥02⁢∫0ω∫0R0fr⁢(r,θ,t)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢sin⁡(λk⁢θ)⁢r⁢𝑑r⁢𝑑θ,
fθ⁢k⁢m⁢(t)= 1∥Jλk−1(καk⁢m⋅)∥02⁢∫0R0fθ⁢k⁢(r,t)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢r⁢𝑑r
= 2ω∥Jλk−1(καk⁢m⋅)∥02⁢∫0ω∫0R0fθ⁢(r,θ,t)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢cos⁡(λk⁢θ)⁢r⁢𝑑r⁢𝑑θ,
ur⁢k⁢m0= 1∥Jλk−1(καk⁢m⋅)∥02⁢∫0R0η⁡(r)⁢ur⁢k0⁢(r)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢r⁢𝑑r
= 2ω∥Jλk−1(καk⁢m⋅)∥02⁢∫0ω∫0R0η⁡(r)⁢ur0⁢(r,θ)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢sin⁡(λk⁢θ)⁢r⁢𝑑r⁢𝑑θ,
ur⁢k⁢m1= 1∥Jλk−1(καk⁢m⋅)∥02⁢∫0R0η⁡(r)⁢ur⁢k1⁢(r)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢r⁢𝑑r
= 2ω∥Jλk−1(καk⁢m⋅)∥02⁢∫0ω∫0R0η⁡(r)⁢ur1⁢(r,θ)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢sin⁡(λk⁢θ)⁢r⁢𝑑r⁢𝑑θ.

Replacing ur⁢k and uθ⁢k by their decompositions in Problem (12) leads to

(14) ur⁢k⁢m⁢(t)=(1αk⁢m⁢ur⁢k⁢m1+1κ2⁢αk⁢m⁢∫0tfr⁢k⁢m⁢(τ)⁢cos⁡(αk⁢m⁢τ)⁢dτ)⁢sin⁡(αk⁢m⁢t)+(ur⁢k⁢m0−1κ2⁢αk⁢m⁢∫0tfr⁢k⁢m⁢(τ)⁢sin⁡(αk⁢m⁢τ)⁢dτ)⁢cos⁡(αk⁢m⁢t),uθ⁢k⁢m⁢(t)=(1αk⁢m⁢uθ⁢k⁢m1+1κ2⁢αk⁢m⁢∫0tfθ⁢k⁢m⁢(τ)⁢cos⁡(αk⁢m⁢τ)⁢dτ)⁢sin⁡(αk⁢m⁢t)+(ur⁢k⁢m0−1κ2⁢αk⁢m⁢∫0tfθ⁢k⁢m⁢(τ)⁢sin⁡(αk⁢m⁢τ)⁢dτ)⁢cos⁡(αk⁢m⁢t).

Then

ur(r,θ,t)=∑k,m=1∞ur⁢k⁢m(t)Jλk−1(καk⁢mr)sinλkθ,uθ(r,θ,t)=∑k,m=1∞uθ⁢k⁢m(t)Jλk−1(καk⁢mr)cosλkθ,

where ur⁢k⁢m and uθ⁢k⁢m are defined in (14). Using the fact that

Jλk−1⁢(κ⁢αk⁢m⁢r)=∑n=0∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m⁢r2)2⁢n+λk−1,

the solution u~:=(ur,uθ)T has the decomposition

(15) u~⁢(r,θ,t) = ∑k,m=1∞∑n=0∞sk,m,n⁢(r,θ,t)
= w~⁢(r,θ,t)+∑k,m=1∞∑n=0,2⁢n+λk−1<2∞s~k,m,n⁢(r,θ,t)
= w~M⁢(r,θ,t)+∑k=1∞∑n=0,2⁢n+λk−1<2∞∑m=1Ms~k,m,n⁢(r,θ,t),

where M∈ℕ, M≥1,

s~k,m,n⁢(r,θ,t)=(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m⁢r2)2⁢n+λk−1⁢(ur⁢k⁢m(t)sinλkθuθ⁢k⁢m(t)cosλkθ),

and w∈C1⁢(0,T,H2⁢(Ω)2).

Remark .

In cartesian coordinates, uη has the decomposition

(16) uη⁢(x1,x2,t):=w⁢(x1,x2,t)+∑k=1∞∑n=0,2⁢n+λk−1<2∞∑m=1Msk,m,n⁢(r,θ,t),

where

sk,m,n⁢(x1,x2,t)=(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m⁢r2)2⁢n+λk−1⁢(ur⁢k⁢m⁢(t)⁢sin⁡(λk−1)⁢θuθ⁢k⁢m⁢(t)⁢cos⁡(λk−1)⁢θ).
Lemma .
(17) |∑k,m=1∞∑n=0,2⁢n+λk−1<2∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m2)2⁢n+λk−1⁢ur⁢k⁢m⁢(t)|<∞

and

(18) |∑k,m=1∞∑n=0,2⁢n+λk−1<2∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m2)2⁢n+λk−1⁢uθ⁢k⁢m⁢(t)|<∞
Proof.
|∑k,m=1∞∑n=0,2⁢n+λk−1<2∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m2)2⁢n+λk−1⁢ur⁢k⁢m⁢(t)|≤
≤ ∑k,m=1∞∑n=0,2⁢n+λk−1<2∞|κ⁢αk⁢m|24⁢n!⁢|Γ⁡(n+λk)||ur⁢k⁢m0cos(αk⁢mt)
+1κ⁢αk⁢mur⁢k⁢m1sin(αk⁢mt)+1κ2⁢αk⁢m∫0tfr⁢k⁢m(τ)sin(αk⁢mτ)dτ|.

The fact that r⁢Jλk−1⁢(κ⁢αk⁢m⁢r)=1κ⁢αk⁢m⁢(−λk⁢Jλk⁢(κ⁢αk⁢m⁢r)+r⁢d⁢Jλkd⁢r⁢(κ⁢αk⁢m⁢r)) implies that

∫0R0ur0⁢(r)⁢sin⁡(λk⁢θ)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢𝑑r=
= −λkκ⁢αk⁢m∫0R0ur0(r)sin(λkθ)Jλk(καk⁢mr)dr
+1κ⁢αk⁢m∫0R0ur0(r)sin(λkθ)d⁢Jλkd⁢r(καk⁢mr)rdr
= −λkκ⁢αk⁢m∫0R0ur0(r)sin(λkθ)rλk−1(r1−λkJλkdr(καk⁢mr))dr
+[rκ⁢αk⁢m⁢ur0⁢(r)⁢sin⁡(λk⁢θ)⁢Jλk⁢(κ⁢αk⁢m⁢r)]0R0
−1κ⁢αk⁢m∫0R0(ur0(r)+rd⁢ur0d⁢r(r))sin(λkθ)Jλk(καk⁢mr)dr
= −λkκ⁢αk⁢m∫0R0ur0(r)sin(λkθ)rλk−1dd⁢r(r1−λkJλk−1(καk⁢mr))dr
+1κ2⁢αk⁢m2∫0R0(ur0(r)+rd⁢ur0d⁢r)sin(λkθ)rλk−1(−καk⁢mr1−λkJλk(καk⁢mr))dr
= 1−κ⁢αk⁢m⁢λkκ2⁢αk⁢m⁢∫0R0ur0⁢(r)⁢sin⁡(λk⁢θ)⁢rλk−1⁢dd⁢r⁢(r1−λk⁢Jλk−1⁢(κ⁢αk⁢m⁢r))⁢𝑑r
+1κ2⁢αk⁢m2∫0R0d⁢ur0d⁢rsin(λkθ)rλkdd⁢r(r1−λkJλk−1(καk⁢mr))dr
= 1κ2⁢αk⁢m2⁢[((1−κ⁢αk⁢m)⁢ur0+r⁢d⁢ur0d⁢r)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)]0R0
−1κ2⁢αk⁢m2∫0R0(−(κ⁢αk⁢m⁢λk−1)2rur0+d⁢ur0d⁢r+rd2⁢ur0d⁢r2)sin(λkθ)Jλk−1(καk⁢m)dr
= −1κ2⁢αk⁢m2∫0R0(−(κ⁢αk⁢m⁢λk−1)2r2ur0+1rd⁢ur0d⁢r+d2⁢ur0d⁢r2)sin(λkθ)Jλk−1(καk⁢m)rdr
≤ C⁢∥Jλk−1(καk⁢m⋅)∥0|κ⁢αk⁢m|2⁢‖u0‖2, if u0∈H2⁢(G0)2.

One also has

∫0R0ur1⁢(r,θ)⁢sin⁡(λk⁢θ)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢r⁢𝑑r=
= 1κ⁢αk⁢m⁢∫0R0ur1⁢(r)⁢sin⁡(λk⁢θ)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢κ⁢αk⁢m⁢r⁢𝑑r
= 1κ⁢αk⁢m⁢∫0κ⁢αk⁢m⁢R0ur1⁢(Rκ⁢αk⁢m,θ)⁢sin⁡(λk⁢θ)⁢Jλk−1⁢(R)⁢R⁢𝑑R⁢where R=κ⁢αk⁢m⁢r
≤ 1|κ⁢αk⁢m|⁢(∫0κ⁢αk⁢m⁢R0|ur1⁢(Rκ⁢αk⁢m,θ)⁢R1/2|2⁢𝑑R⁢∫0κ⁢αk⁢m⁢R0|Jλk−1⁢(R)⁢R1/2|2⁢𝑑R)12
≤ C∥Jλk−1(καk⁢m⋅)∥0∥u1∥0.

Using the same way one can show that

∫0R0fr⁢k⁢m(r)sin(λkθ)Jλk−1(καk⁢mr)dr≤C∥Jλk−1(καk⁢m⋅)∥0∥f∥0.

Hence (3) becomes

|∑k,m=1∞∑n=0,2⁢n+λk−1<2∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m2)2⁢n+λk−1⁢ur⁢k⁢m⁢(t)|≤
≤ C∑k,m=1∞∑n=0,2⁢n+λk−1<2∞[(‖u0‖2+1κ⁢αk⁢m⁢‖u1‖0)2ωn!|Γ(n+λk)|∥Jλk−1(καk⁢m⋅)∥0
+1|κ⁢αk⁢m|2∫0tsin(αk⁢mτ)dτ∥f∥0]
≤ |∑k,m=1∞∑n=0,2⁢n+λk−1<2∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m2)2⁢n+λk−1⁢ur⁢k⁢m⁢(t)|
≤ ∑k,m=1∞∑n=0,2⁢n+λk−1<2∞C⁡(‖u0‖2+1|κ⁢αk⁢m|⁢‖u1‖0+T⁢‖f‖0|κ⁢αk⁢m|2)2ωn!|Γ(n+λk)|∥Jλk−1(καk⁢m⋅)∥0
≤ ∑k,m=1∞∑n=0,2⁢n+λk−1<2∞C⁡(R0,T,u0,u1,f)2ωn!|Γ(n+λk)|∥Jλk−1(καk⁢m⋅)∥0
< ∞.

Similar methods can be used with uθ0, uθ1 and fθ⁢k⁢m to show (18). ∎

A truncation of the summation on the integer m can be done and the following error estimate is obtained.

Lemma .

Let M∈ℕ, M>1, and let {αk⁢m}m≥1 be an increasing sequence of positive numbers such that Jλk−1⁢(κ⁢αk⁢m⁢R0)=0 where λk=k⁢π/ω, R0>0 is fixed and κ∈ℝ is defined as in (1). Let

cr⁢(t)=∑k,m=1∞∑n=0,2⁢n+λk−1<2∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m2)2⁢n+λk−1⁢ur⁢k⁢m⁢(t),
cθ⁢(t)=∑k,m=1∞∑n=0,2⁢n+λk−1<2∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m2)2⁢n+λk−1⁢uθ⁢k⁢m⁢(t),
cr,M⁢(t)=∑m=1M∑k=1∞∑n=0,2⁢n+λk−1<2∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m2)2⁢n+λk−1⁢ur⁢k⁢m⁢(t),
cθ,M⁢(t)=∑m=1M∑k=1∞∑n=0,2⁢n+λk−1<2∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m2)2⁢n+λk−1⁢uθ⁢k⁢m⁢(t).

Then

(20) |cr⁢(t)−cr,M⁢(t)|≤C⁢maxk≥1,n≥0, 2⁢n+λk−1<2⁢{|αk⁢M|−λk}

and

(21) |cθ⁢(t)−cθ,M⁢(t)|≤C⁢maxk≥1,n≥0, 2⁢n+λk−1<2⁢{|αk⁢M|−λk}.
Proof.
|cr⁢(t)−cr,M⁢(t)|= |∑m=M+1∞∑k=1∞∑2⁢n+λk−1<2∞(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m2)2⁢n+λk−1⁢ur⁢k⁢m⁢(t)|
≤ ∑m=M+1∞∑k=1∞∑2⁢n+λk−1<2∞C2ωn!|Γ(n+λk)|∥Jλk−1(καk⁢m⋅)∥0

But

Jλk−1⁢(κ⁢αk⁢m⁢r)=(κ⁢αk⁢m⁢r)λk−12λk−1⁢Γ⁢(λk)⁢(1−(κ⁢αk⁢m⁢r)22⁢(2⁢λk)+(κ⁢αk⁢m⁢r)42⁢(4)⁢(2⁢λk)⁢(2⁢λk+2)−⋯)

then

|cr⁢(t)−cr,M⁢(t)| ≤ C⁡(R0)⁢∑m=M+1∞∑k=1∞∑n=0,2⁢n+λk−1<2∞2λk−1⁢Γ⁢(λk)2⁢ω⁢n!⁢|Γ⁡(λk+n)|⁢|αk⁢m|λk
≤ C⁢maxk≥1,n≥0, 2⁢n+λk−1<2⁢{|αk⁢M|−λk}

The inequality (21) can be deduced using the same manner. ∎

Remark .

αk⁢M→∞ as M→∞ but since λk>0, |αk⁢M|−λk→0 as M→∞.

4. The Defect-Correction Finite Element method

4.1. A Semi-discrete Approximation

This section presents a space discretization of the solution by a Galerkin approximation with H1-conforming finite element methods. The Galerkin method considers a quasi-uniform and shape-regular triangulation 𝒯h of Ω with diameter h, and finds a semi-discrete approximation uh∈L2⁢(0,T,Vh) of the solution u∈L2⁢(0,T,H⁡(curl,div,Ω)) of Problem (2) satisfying

(22) κ2⁢d2d⁢t2⁢∫Ωuh⋅vh⁢dx+a⁡(uh,vh)=∫Ωf⋅vh⁢dx,∀vh∈Vh∫Ωuh⁢(⋅,0)⋅vh⁢dx=∫Ωu0⋅vh⁢dx,∀vh∈Vh∫Ω∂uh∂t⁢(⋅,0)⋅vh⁢dx=∫Ωu1⋅vh⁢dx,∀vh∈Vh

where Vh:={vh∈𝒞⁢(Ω)2:vh|K∈𝒫1⁢(K)2⁢and vh∧n=0⁢ on ⁢∂Ω}⊂HN⁢(Ω) is a finite dimensional space.

The following result presents the standard error estimates for regular solutions u∈L2⁢(0,T,H2⁢(Ω)2) which happens when Ω is convex or has a 𝒞2-boundary. A proof can be adapted from the one in [32, Theorem 4.1, p.  575],

Theorem 1.

If Ω is a convex polygonal domain with all its angles less than or equal to π/2, u⁢(⋅,t) the solution of Problem (2) and uh⁢(⋅,t) the solution of Problem (22), t∈(0,T), if u∈L∞⁢(0,T,H⁡(curl, div,Ω)) and ∂u∂t∈L2⁢(0,T,H⁡(curl, div,Ω)) and ∂ku∂tk∈L2⁢(0,T,L2⁢(Ω)2), k=3,4, then

‖u⁢(⋅,t)−uh⁢(⋅,t)‖c⁢d≤C⁢h‖u⁢(⋅,t)−uh⁢(⋅,t)‖0≤C⁢h2.

When the domain Ω is convex with an angle greater than π/2 the solution may converge slowly and if Ω is not convex, the solution may fail to converge. The following algorithm based on the decomposition (16) proposes a way to recover the optimal convergence as in Theorem 1.

Algorithm 1 Defect-Correction Algorithm
  1. 1)

    Solve Problem (22) in Vh and obtain the solution uh(0).

  2. 2)

    Compute the sk,m,n(0) using formula (16), replacing u with uh(0), k,m,n∈ℕ, k≥1, 1≤m≤M, M∈ℕ, 2⁢n+λk−1<2, that i,s

    sk,m,n(0)⁢(x1,x2,t)=(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m⁢r2)2⁢n+λk−1⁢(ur⁢k⁢m(0)⁢(t)⁢sin⁡(λk−1)⁢θuθ⁢k⁢m(0)⁢(t)⁢cos⁡(λk−1)⁢θ),

    where

    ur⁢k⁢m(0)⁢(t)= (1αk⁢m⁢ur⁢k⁢m(0)⁢1+1κ2⁢αk⁢m⁢∫0tfr⁢k⁢m(0)⁢(τ)⁢cos⁡(αk⁢m⁢τ)⁢𝑑τ)⁢sin⁡(αk⁢m⁢t),
    +(ur⁢k⁢m(0)⁢0−1κ2⁢αk⁢m⁢∫0tfr⁢k⁢m(0)⁢(τ)⁢sin⁡(αk⁢m⁢τ)⁢𝑑τ)⁢cos⁡(αk⁢m⁢t)
    uθ⁢k⁢m(0)⁢(t)= (1αk⁢m⁢uθ⁢k⁢m(0)⁢1+1κ2⁢αk⁢m⁢∫0tf⁢(0)θ⁢k⁢m⁢(τ)⁢cos⁡(αk⁢m⁢τ)⁢𝑑τ)⁢sin⁡(αk⁢m⁢t)
    +(ur⁢k⁢m(0)⁢0−1κ2⁢αk⁢m⁢∫0tf⁢(0)θ⁢k⁢m⁢(τ)⁢sin⁡(αk⁢m⁢τ)⁢𝑑τ)⁢cos⁡(αk⁢m⁢t),
    fr⁢k⁢m(0)⁢(t)= 2ω∥Jλk−1(καk⁢m⋅)∥02⁢∫0ω∫0R0fr(0)⁢(r,θ,t)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢sin⁡(λk⁢θ)⁢r⁢𝑑r⁢𝑑θ,
    fθ⁢k⁢m(0)⁢(t)= 2ω∥Jλk−1(καk⁢m⋅)∥02⁢∫0ω∫0R0fθ(0)⁢(r,θ,t)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢cos⁡(λk⁢θ)⁢r⁢𝑑r⁢𝑑θ,
    (fr(0)fθ(0))= (fη⁢1(0)⁢cos⁡θ+fη⁢2(0)⁢sin⁡θ−fη⁢1(0)⁢sin⁡θ+fη⁢2(0)⁢cos⁡θ),
    fη(0):= (fη⁢1(0)fη⁢2(0))=(ηf1−u(0)1Δη−2∇η⋅∇u(0)1ηf2−u(0)2Δη−2∇η⋅∇u(0)2),
    (ur(0)uθ(0))= (uη⁢1(0)⁢cos⁡θ+uη⁢2(0)⁢sin⁡θ−uη⁢1(0)⁢sin⁡θ+uη⁢2(0)⁢cos⁡θ),
    ur⁢k⁢m(0)⁢0= 2ω∥Jλk−1(καk⁢m⋅)∥02⁢∫0ω∫0R0η⁡(r)⁢ur0⁢(r,θ)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢sin⁡(λk⁢θ)⁢r⁢𝑑r⁢𝑑θ,
    ur⁢k⁢m(0)⁢1= 2ω∥Jλk−1(καk⁢m⋅)∥02⁢∫0ω∫0R0η⁡(r)⁢ur1⁢(r,θ)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢sin⁡(λk⁢θ)⁢r⁢𝑑r⁢𝑑θ,
    uθ⁢k⁢m(0)⁢0= 2ω∥Jλk−1(καk⁢m⋅)∥02⁢∫0ω∫0R0η⁡(r)⁢uθ0⁢(r,θ)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢cos⁡(λk⁢θ)⁢r⁢𝑑r⁢𝑑θ,
    uθ⁢k⁢m(0)⁢1= 2ω∥Jλk−1(καk⁢m⋅)∥02⁢∫0ω∫0R0η⁡(r)⁢uθ1⁢(r,θ)⁢Jλk−1⁢(κ⁢αk⁢m⁢r)⁢cos⁡(λk⁢θ)⁢r⁢𝑑r⁢𝑑θ.
  3. 3)

    Find wh⁢M(1) solution of

    (23) κ2⁢d2d⁢t2⁢∫Ωwh⁢M(1)⋅vh⁢dx+a⁡(wh⁢M(1),vh)=
    =∫Ω(f−κ2⁢∑k,n,m=1M∂2sk,m,n(0)∂t2)⋅vh⁢dx−∑k,m,na⁡(sk,m,n(0),vh),∀vh∈Vh,
    ∫Ωwh⁢M(1)⁢(⋅,0)⋅vh⁢dx=∫Ω(u0−∑k,n,m=1Msk,m,n(0)⁢(⋅,0))⋅vh⁢dx,∀vh∈Vh,
    ∫Ω∂wh⁢M(1)∂t⁢(⋅,0)⋅vh⁢dx=∫Ω(u1−∑k,n,m=1M∂sk,m,n(0)∂t⁢(⋅,0))⋅vh⁢dx,∀vh∈Vh,

    where a⁡(u,v)=∫Ωcurlu⁢curlv+div⁡u⁢div⁢v⁢dx.

  4. 4)

    Compute uh⁢M(1)=wh⁢M(1)+∑k,n,m=1Msk,m,n(0).

Error Estimates

From the decomposition (16) and the Defect-correction Algorithm 1, one can derive the following error estimates.

Lemma .

Let 𝒯h be a quasi-uniform and shape-regular triangulation of Ω and let Πh be the usual Lagrange interpolation operator over the triangulation 𝒯h. Then for k,m,n∈ℕ, k≥1, m≥1, 2⁢n+λk−1<2, λk=k⁢π/ω,

(24) ‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖c⁢d ≤C⁢hλk−1,
(25) ‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖0 ≤C⁢hλk.
Proof.

Let us divide the triangulation 𝒯h of the domain Ω into two parts ℳh1={K∈𝒯h:(0,0)∈K} and ℳh2={K∈𝒯h:(0,0)∉K}, one has

‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖02 ≤ ∑K∈𝒯h‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖02
≤ ∑K∈ℳh1‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖2
+∑K∈ℳh2∥sk,m,n(⋅,t)−Πhsk,m,n(⋅,t)∥02.

By the Cauchy-Schwartz inequality

∑K∈ℳh1‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖02≤C⁢∑K∈ℳh1‖sk,m,n⁢(⋅,t)‖02+‖Πh⁢sk,m,n⁢(⋅,t)‖02.

2⁢n+λk−1<2 happens when n=0,1, then for K∈ℳh1,

‖sk,m,n⁢(⋅,t)‖02 ≤ C⁢∫0hK(r2⁢λk−1+r2⁢λk+1)⁢(|ur⁢k⁢m⁢(t)|2+|uθ⁢k⁢m⁢(t)|2)⁢𝑑r
≤ C⁢max⁡{hK2⁢λk,hK2⁢λk+2}
≤ C⁢h2⁢λk.

Πh⁢sk,m,n⁢(⋅,t) being a polynomial of degree 1 then for K∈ℳh1,

‖Πh⁢sk,m,n⁢(⋅,t)‖02 ≤ C⁢max⁡{|sk,m,n⁢(x1,x2,t)|2,(x1,x2)∈K}⁢meas⁢(K)
≤ C⁢h2⁢λk−2⁢hK2
≤ C⁢h2⁢λk.

Hence ∑K∈ℳh1‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖02≤C⁢hλk.

For K∈ℳh2, sk,m,n⁢(⋅,t)∈H2⁢(K)2 then

∑K∈ℳh2‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖02≤C⁢h4.

Then ‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖02≤C⁢max⁡{h2⁢λk,h4}≤C⁢h2⁢λk and

‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖0≤C⁢hλk.

Using the same method as above, one can prove that

‖sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t)‖c⁢d≤C⁢hλk−1.

∎

Lemma .

Let 𝒯h be a quasi-uniform and shape-regular triangulation of Ω and let Πh be the usual Lagrange interpolation operator over the triangulation 𝒯h. Then for M,n,k∈ℕ, m≥1, k≥1, n≥0, 2⁢n+λk−1<2, λk=k⁢π/ω, there exist C>0 such that

(26) ‖∑m=1M(sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t))+∑m=M+1∞sk,m,n⁢(⋅,t)‖0≤C⁢hλk⁢|αk⁢M|−λk

and

(27) ‖∑m=1M(sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t))+∑m=M+1∞sk,m,n⁢(⋅,t)‖c⁢d≤C⁢hλk−1⁢|αk⁢M|−λk.
Proof.

Let us divide the triangulation 𝒯h of the domain Ω into two parts ℳh1={K∈𝒯h:(0,0)∈K} and ℳh2={K∈𝒯h:(0,0)∉K}.

‖∑m=1M(sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t))+∑m=M+1∞sk,m,n⁢(⋅,t)‖02≤
≤∑K∈ℳh1‖∑m=1M(sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t))+∑m=M+1∞sk,m,n⁢(⋅,t)‖2
+∑K∈ℳh2∥∑m=1M(sk,m,n(⋅,t)−Πhsk,m,n(⋅,t))+∑m=M+1∞sk,m,n(⋅,t)∥02.

For K∈ℳh1, one can use the inequalities (20), (21) and (24) to obtain

‖∑m=1M(sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t))+∑m=M+1∞sk,m,n⁢(⋅,t)‖0≤
≤∑m=1M‖(−1)nn!⁢Γ⁢(n+λk)⁢(κ⁢αk⁢m⁢r2)2⁢n+λk−1⁢((ur⁢k⁢m(t)−ur⁢k⁢m(0)(t))sinλkθ(uθ⁢k⁢m(t)−uθ⁢k⁢m(0)(t))cosλkθ)‖0
+C⁢hKλk⁢|αk⁢M|−λk
≤C⁡(hKλk⁢maxm=1,⋯,M⁢|αk⁢m|−λk+hKλk⁢|αk⁢M|−λk)
≤C⁢hλk⁢|αk⁢M|−λk.

For K∈ℳh2,

‖∑m=1M(sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t))+∑m=M+1∞sk,m,n⁢(⋅,t)‖0≤C⁢h2⁢|αk⁢M|−λk

Then

‖∑m=1M(sk,m,n⁢(⋅,t)−Πh⁢sk,m,n⁢(⋅,t))+∑m=M+1∞sk,m,n⁢(⋅,t)‖02≤C⁢hλk⁢|αk⁢M|−λk

This shows (26).

The inequality (27) can be shown using the same way as previous.

∎

Theorem 2.

Let 𝒯h be a quasi-uniform and shape-regular triangulation of Ω, let M∈ℕ, M≥1, let u∈L2⁢(0,T,H0⁢(curl,div,Ω)) be the solution of Problem (2), and uh⁢M(1) be the solution of Problem (22) using the Defect-Correction Algorithm 1, then for any t∈(0,T),

(28) ‖u⁢(⋅,t)−uh⁢M(1)⁢(⋅,t)‖c⁢d ≤C⁢max2⁢n+λk−1<2⁢{h,hλk−1⁢|αk⁢M|−λk},
(29) ‖u⁢(⋅,t)−uh⁢M(1)⁢(⋅,t)‖0 ≤C⁢max2⁢n+λk−1<2⁢{h2,hλk−1⁢|αk⁢M|−λk}.
Proof.
u−uh⁢M(1) = w−∑k,n,m=1∞sk,m,n−wh⁢M(1)−∑k,n,m=1Msk,m,n(0)
= w−wh⁢M(1)+∑k,n,m=1M[sk,m,n−Πh⁢sk,m,n+(Πh⁢sk,m,n−sk,m,n(0))]
+∑k,n,m=M+1∞sk,m,n

then

‖u−uh⁢M(1)‖c⁢d≤
≤ ‖w−wh⁢M(1)‖c⁢d+∑k,n,m=1M‖sk,m,n−Πh⁢sk,m,n‖c⁢d+‖Πh⁢sk,m,n−sk,m,n(0)‖c⁢d
+∑k,n,m=M+1∞∥sk,m,n−Πhsk,m,n∥c⁢d+∥Πhsk,m,n−sk,m,n(0)∥c⁢d
≤ ‖w−wh⁢M(1)‖c⁢d+C⁢hλk−1⁢[(∫0t‖u−uh(0)‖02⁢𝑑τ)1/2+|αk⁢M|−λk]
≤ C⁡(‖w−wh⁢M(1)‖c⁢d+hλk−1⁢‖u−uh⁢M(0)‖0+hλk−1⁢|αk⁢M|−λk)
≤ C⁡(‖w−wh⁢M(1)‖c⁢d+hλk−1⁢‖w−wh⁢M(0)‖c⁢dCLOSE
+hλk−1∑m=1M∥sk,m,n−Πhsk,m,n∥0+hλk−1∑m=M+1∞∥sk,m,n∥0
OPEN+hλk−1⁢|αk⁢M|−λk)
(30) ≤ C⁡(‖w−wh⁢M(1)‖c⁢d+hλk−1⁢‖w−wh⁢M(0)‖c⁢d+hλk−1⁢(2+hλk)⁢|αk⁢M|−λk)
≤ C⁡(‖w−wh⁢M(1)‖c⁢d+hλk−1⁢‖w−wh⁢M(0)‖c⁢d+hλk−1⁢|αk⁢M|−λk).

The next step consists to find an appropriate bound of ‖w−wh⁢M(1)‖c⁢d.

Set Πh⁢w=wh, s=∑k,m,nsk,m,n and s(0)=∑k,n,m=1Msk,m,n(0), one has

(31) κ2⁢d2d⁢t2⁢∫Ωwh⋅vh⁢dx+a⁡(wh,vh)=∫Ω(f−κ2⁢∂2s∂t2)⋅vh⁢dx−a⁡(s,vh)⁢∀vh∈Vh.

Taking the difference of (31) with the first equation of (22) leads to

κ2⁢d2d⁢t2⁢∫Ω(wh−wh⁢M(1))⋅vh⁢dx+a⁡(wh−wh⁢M(1),vh)=
=−∫Ωκ2∂2(s−s(0))∂t2⋅vhdx−a(s−s(0),vh).

for any vh∈Vh. Then for vh⁢(⋅)=∂2(wh−wh⁢M(1))∂t2⁢(⋅,t)∈Vh, integration by parts gives

12⁢dd⁢t⁢‖κ2⁢∂(wh−wh⁢M(1))∂t‖02+12⁢dd⁢t⁢(a⁡(wh−wh⁢M(1),wh−wh⁢M(1)))==∫Ωκ2⁢∂(s−s(0))∂t⋅∂(wh−wh⁢M(1))∂t⁢dx−a⁡(s−s(0),∂(wh−wh⁢M(1))∂t).

Taking the integral between 0 and t and the Inequality (27) give

‖κ2⁢∂(wh−wh⁢M(1))∂t‖02+a⁡(wh−wh⁢M(1),wh−wh⁢M(1))=
= 2⁢[∫0t∫Ωκ2⁢∂(s−s(0))∂t⋅∂(wh−wh⁢M(1))∂t⁢dx⁢𝑑τ−∫0ta⁡(s−s(0),∂(wh−wh⁢M(1))∂t)⁢𝑑τ]
= 2[∫0t∫Ωκ2∂(s−s(0))∂t⋅∂(wh−wh⁢M(1))∂tdxdτ−a(s−s(0),wh−wh⁢M(1))
+∫0ta(s−s(0),∂(wh−wh⁢M(1))∂t)dτ−κ22∫Ω∂(s−s(0))∂t⋅∂(s−s(0))∂tdx
−12a(s−s(0),s−s(0))−∫0ta(s−s(0),∂(wh−wh⁢M(1))∂t)dτ]
≤ 2⁢‖∂(s−s(0))∂t‖0|κ2⁢∂(wh−wh⁢M(1))∂t|0+2⁢‖s−s(0)‖c⁢d|wh−wh⁢M(1)|c⁢d
+‖∂(s−s(0))∂t‖0⁢‖κ2⁢∂(s−s(0))∂t‖0+|s−s(0)|c⁢d2
≤ C⁡[hλk−1⁢|αk⁢M|−λk⁢(‖κ2⁢∂(wh−wh⁢M(1))∂t‖02+|wh−wh⁢M(1)|02)+h2⁢(λk−1)⁢|αk⁢M|−2⁢λk].

Since a⁡(wh−wh⁢M(1),wh−wh⁢M(1))=|wh−wh⁢M(1)|c⁢d2 one deduces that

(‖κ2⁢∂(wh−wh⁢M(1))∂t‖02+|wh−wh⁢M(1)|c⁢d2)1/2 ≤ (h2⁢λk−2⁢|αk⁢M|−2⁢λk1−C⁢hλk−1⁢|αk⁢M|−λk)1/2
≤ C⁢hλk−1⁢|αk⁢M|−λk.

The semi-norm |⋅|c⁢d being equivalent to the norm ∥⋅∥c⁢d in H0⁢(curl,div,Ω) (see [18]), one has

(32) ‖wh−wh⁢M(1)‖c⁢d≤(‖κ2⁢∂(wh−wh⁢M(1))∂t‖02+|wh−wh⁢M(1)|c⁢d2)1/2≤C⁢hλk−1⁢|αk⁢M|−λk.

Using (32) in (30) leads to

‖u−uh⁢M(1)‖c⁢d≤
≤C⁡[‖w−wh⁢M(1)‖c⁢d+‖∑k,n,m=1M(sk,m,n−Πh⁢sk,m,n)+∑k,n,m=M+1∞sk,m,n‖c⁢d]
≤ C⁡(‖w−wh⁢M(1)‖c⁢d+hλk−1⁢|αk⁢M−λk|)
≤ (‖w−wh‖c⁢d+‖wh−wh⁢M(1)‖c⁢d+hλk−1⁢|αk⁢M−λk|)
≤ C⁡(h+hλk−1⁢|αk⁢M−λk|)
≤ C⁢max2⁢n+λk−1<2⁢{h,hλk−1⁢|αk⁢M|−λk}

Hence, inequality (28) is proved.

Following the same steps used to establish inequality (30) replacing the norm ∥⋅∥c⁢d by the norm ∥⋅∥0 one has

‖u−uh⁢M(1)‖0≤
≤C⁡[‖w−wh⁢M(1)‖0+‖∑k,n,m=1M(sk,m,n−Πh⁢sk,m,n)+∑k,n,m=M+1∞sk,m,n‖0]
≤ C⁡(‖w−wh⁢M(1)‖0+hλk−1⁢|αk⁢M−λk|)
≤ C⁡(‖w−wh‖0+‖wh−wh⁢M(1)‖0+hλk−1⁢|αk⁢M−λk|)
≤ C⁡(h2+hλk−1⁢|αk⁢M−λk|)
≤ C⁢max2⁢n+λk−1<2⁢{h2,hλk−1⁢|αk⁢M|−λk}

and (29) is proved. ∎

Remark .

If M∈ℕ is chosen so that hλk−1⁢|αk⁢M|−λk≤h2, the error estimates (28) and (29) are optimal.

4.2. A Crank-Nicolson full discretization

Considering a quasi-uniform and shape-regular triangulation 𝒯h of the polygonal domain Ω and a Galerkin solution uh of the variational problem (22), let {ϕj⁢h}1≤j≤N be a basis of the space Vh, one has uh⁢(⋅,t)=∑j=1Nuj⁢h⁢(t)⁢ϕj⁢h⁢(⋅)=UhT⁢(t)⁢Φh⁢(⋅) where Uh⁢(t)=(uj⁢h⁢(t))1≤j≤NT and Φh=(ϕj⁢h)1≤j≤N, satisfies the variational system

κ2⁢Mh⁢d2⁢Uhd⁢t2+Ah⁢Uh =Fh⁢(t),t∈(0,T),
Mh⁢Uh⁢(0) =(∫Ωu0⋅ϕl⁢h⁢dx)1≤l≤NT,
Mh⁢d⁢Uhd⁢t⁢(0) =(∫Ωu1⋅ϕl⁢h⁢dx)1≤l≤NT,

where Mh=(∫Ωϕj⁢h⋅ϕl⁢h⁢dx)1≤j,l≤N, Ah=(a⁡(ϕj⁢h,ϕl⁢h))1≤j,l≤N and

Fh⁢(t)=(∫Ωf⁢(⋅,t)⋅ϕl⁢h⁢dx)1≤l≤NT.

The full discretization consists to subdivide the interval [0,T] into L subintervals [tj−1,tj] of size τ=tj−tj−1=TL, j=1,⋯,L such that [0,T]=⋃j=1L[tj−1,tj], 0=t0<t1<⋯<tL=T. The σ-schemes (0≤σ≤1) consists of approximating Uh⁢(tl)=(uj⁢h⁢(tl))1≤j≤NT, 0≤l≤L such that

(33) κ2τ2⁢Mh⁢(Uh⁢(tl+1)−2⁢Uh⁢(tl)+Uh⁢(tl−1))+
+σ⁢Ah⁢Uh⁢(tl+1)+(1−2⁢σ)⁢Ah⁢Uh⁢(tl)+σ⁢Ah⁢Uh⁢(tl−1)
=σ⁢Fh⁢(tl+1)+(1−2⁢σ)⁢Fh⁢(tl)+σ⁢Fh⁢(tl−1),
Mh⁢Uh⁢(0) =(∫Ωu0⋅ϕl⁢h⁢𝐝𝐱)1≤l≤NT,
Mh⁢d⁢Uhd⁢t⁢(0) =(∫Ωu1⋅ϕl⁢h⁢𝐝𝐱)1≤l≤NT.

So if we set uh⁢τ⁢(⋅,t) be an interpolation of the solution (Uh⁢(tl))1≤l≤L, that is, uh⁢τ⁢(⋅,tl)=Uh⁢(tl)⁢Φ⁢(⋅) with a Crank-Nicolson scheme (σ=1/2), one has the following error estimates from Theorem 1

‖u⁢(⋅,tl)−uh⁢τ⁢(⋅,tl)‖c⁢d≤C⁡(h+τ2),‖u⁢(⋅,tl)−uh⁢τ⁢(⋅,tl)‖0≤C⁡(h2+τ2),

for l=1,…,L if Ω is a convex polygonal domain and if u belongs to L∞⁢(0,T,H⁡(curl, div,Ω)), ∂u∂t is in L2⁢(0,T,H⁡(curl, div,Ω)) and ∂ku∂tk belongs to L2⁢(0,T,L2⁢(Ω)2), k=3,4.

The following algorithm is developed to recover the convergence rate of the Crank-Nicolson scheme when the domain Ω is not convex.

Algorithm 2 Defect-Correction Algorithm
  1. 1)

    Solve Problem (33) and obtain the solution uh⁢τ(0).

  2. 2)

    Compute the sk,m,n(0) using formula (16), replacing u with uh⁢τ(0), k,m,n∈ℕ, k≥1, 1≤m≤M, M∈ℕ, M≥1, 2⁢n+λk−1<2.

  3. 3)

    Find wh⁢τ⁢M(1) solution of

    (34) κ2⁢d2d⁢t2⁢∫Ωwh⁢τ⁢M(1)⋅vhdx+a⁡(wh⁢τ⁢M(1),vh)==∫Ω(f−κ2∑k,m,n∂2sk,m,n(0)∂t2)⋅vhdx−∑k,m,na(sk,m,n(0),vh),∀vh∈Vh,
    ∫Ωw(1)h⁢τ⁢M(⋅,0)⋅vhdx=∫Ω(u0−∑k,m,ns(0)k,m,n(⋅,0))⋅vhdx,∀vh∈Vh,∫Ω∂wh⁢τ⁢M(1)∂t(⋅,0)⋅vhdx=∫Ω(u1−∑k,m,n∂sk,m,n(0)∂t(⋅,0))⋅vhdx,∀vh∈Vh.
  4. 4

    Compute uh⁢τ⁢M(1)=wh⁢τ⁢M(1)+∑k,m,nsk,m,n(0).

Error Estimates of the Crank-Nicolson FEM

Theorem 3.

Let 𝒯h be a quasi-uniform and shape-regular triangulation of Ω, let M∈ℕ, M≥1, let u∈L2⁢(0,T,H0⁢(curl,div,Ω)) be the solution of Problem (2), and uh⁢τ⁢M(1) be the interpolation of the solution of Problem (33) using the Defect-Correction Algorithm 2 in a subdivision of the interval [0,T] in sub-interval [tl−1,tl] of size τ=TL, l=1,⋯,L such that [0,T]=⋃l=1L[tl−1,tl], 0=t0<t1<⋯<tL=T. Then for any 1≤l≤L,

(35) ‖u⁢(⋅,tl)−uh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d≤C⁡(maxk≥1,n≥0, 2⁢n+λk−1<2⁡{h,hλk−1⁢|αk⁢M|−λk}+τ2),
(36) ‖u⁢(⋅,tl)−uh⁢τ⁢M(1)⁢(⋅,tl)‖0≤C⁡(maxk≥1,n≥0, 2⁢n+λk−1<2⁡{h2,hλk−1⁢|αk⁢M|−λk}+τ2).
Proof.
‖u⁢(⋅,tl)−uh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d≤
≤ ‖u⁢(⋅,tl)−uh⁢M(1)⁢(⋅,tl)‖c⁢d+‖uh⁢M(1)⁢(⋅,tl)−uh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d
≤ C⁡(max2⁢n+λk−1⁡{h,hλk−1⁢|αk⁢M|−λk})+‖uh⁢(⋅,tl)−uh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d.

But

uh⁢M(1)⁢(⋅,tl)=wh⁢M(1)⁢(⋅,tl)+∑k,n,m=1Msk,m,n(0)⁢and⁢uh⁢τ⁢M(1)⁢(⋅,tl)=wh⁢τ⁢M(1)⁢(⋅,tl)++∑k,n,m=1Msk,m,n,τ(0),

​​​​where 𝐬k,m,n,τ(0) is the interpolation of the 𝐬k,m,n(0)⁢(⋅,tl),0≤l≤L.

Then

‖uh⁢M(1)⁢(⋅,tl)−uh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d≤
≤ ‖wh⁢M(1)⁢(⋅,tl)−wh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d+∑k,n,m=1M‖sk,m,n(0)−sk,m,n,τ(0)‖c⁢d
≤ ‖wh⁢M(1)⁢(⋅,tl)−wh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d+C⁡(maxk,n, 2⁢n+λk−1<2⁡{hλk−1⁢|αk⁢M|−λk}+τ2).

Also, using (32)

‖wh⁢M(1)⁢(⋅,tl)−wh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d≤
≤ ‖wh⁢M(1)⁢(⋅,tl)−wh⁢(⋅,tl)‖c⁢d+‖wh⁢(⋅,tl)−wh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d
≤ ‖wh⁢M(1)⁢(⋅,tl)−wh⁢(⋅,tl)‖c⁢d
+‖wh⁢(⋅,tl)−wh⁢τ(1)⁢(⋅,tl)‖c⁢d+‖wh⁢τ⁢(⋅,tl)−wh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d
≤ C⁡(maxk,n,2⁢n+λk−1<2⁡{hλk−1⁢|αk⁢M|−λk}+h+τ2+‖wh⁢τ⁢(⋅,tl)−wh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d).

But one can use a similar method as the one in Theorem 2 to show that

‖wh⁢τ⁢(⋅,tl)−wh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d≤C⁡(max2⁢n+λk−1<2⁡{hλk−1⁢|αk⁢M|−λk}+τ2).

Hence

‖u⁢(⋅,tl)−uh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d≤C⁡(maxk≥1,n≥0, 2⁢n+λk−1<2⁡{h,hλk−1⁢|αk⁢M|−λk}+τ2).

One can use the same method as above to show (36). ∎

Remark .

One can remark that if M is chosen such that

maxk≥1,n≥0, 2⁢n+λk−1<2⁡{hλk−1⁢|αk⁢M|−λk}≤h2,

then the optimal convergence of a linear Crank-Nicolson FEM is obtained, that is

‖u⁢(⋅,tl)−uh⁢τ⁢M(1)⁢(⋅,tl)‖c⁢d≤C⁡(h+τ2)‖u⁢(⋅,tl)−uh⁢τ⁢M(1)⁢(⋅,tl)‖0≤C⁡(h2+τ2)

5. conclusion

This paper presents a finite element method to solve the time-dependent Maxwell’s equations on non-convex polygonal domains. The nodal FEM is coupled with a Fourier decomposition that extracts the singular behavior of the solution and recovers the optimal linear convergence. The extension to polygonal domains with multiple re-entrant corners can be handled by the method through the use of local cut-off functions near the corners and adding the different singular parts to the final solution. However, the method assumes that the solution is sufficiently regular in time, and the initial data are also sufficiently smooth, so time-singularities and singularities due to the smoothness of the initial data or the change of boundary conditions are not handled by the method.

References