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Applicable Analysis
An International Journal
Volume 99, 2020 - Issue 7
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Articles

Space-time finite element methods stabilized using bubble function spaces

Pages 1153-1170 | Received 14 Jun 2018, Accepted 09 Sep 2018, Published online: 24 Sep 2018

ABSTRACT

In this paper, a stabilized space-time finite element method for solving linear parabolic evolution problems is analyzed. The proposed method is developed on a base of a space-time variational setting, that helps on the simultaneous and unified discretization in space and in time by finite element techniques. Stabilization terms are constructed by means of classical bubble spaces. Stability of the discrete problem with respect to an associated mesh dependent norm is proved, and a priori discretization error estimates are presented. Numerical examples confirm the theoretical estimates.

1. Introduction

Parabolic evolution equations are used to describe numerous physical phenomena, as for example heat transfer. The traditional methods for parabolic problems usually apply a separate method for the time discretization, e.g. implicit Runge–Kutta methods. During the last decades, efficient discontinuous Galerkin finite element methods have been presented for the time discretization of parabolic problems, see, e.g. an analysis for Galerkin time-stepping methods in [Citation1–3], we also refer to the monograph [Citation4]. Adaptive algorithms based on a posteriori error estimates have also been presented and successfully tested for linear and nonlinear problems, see e.g. [Citation5,Citation6] and the references therein. In [Citation7,Citation8], space-time adaptive wavelet methods for parabolic evolution problems have been studied. Also in the literature, p and hp finite element methods for parabolic problems have been presented, see [Citation9,Citation10].

Another approach that has been followed is the derivation of space-time finite element methods, based on appropriate space-time variational settings. The basic idea is to consider the time variable t as just another variable, lets say xd+1, if we consider that x=(x1,,xd) are the spatial variables. In that way, the time derivative, which appears in the parabolic PDE model, plays the role of a convection term in the time direction xd+1. By multiplying the given parabolic problem by a space-time test function and applying integration by parts, we can derive the weak space-time formulation. The derived weak formulation helps on the unified space-time discretization by finite element techniques. This means that we discretize the problem in space and in time by using a common finite element space. In this spirit, in [Citation11], space-time finite element methods have been developed for elastodynamics. In particular, the method uses discontinuous Galerkin techniques for the time discretization and incorporates Petrov–Galerkin techniques, see [Citation12], to ensure stability. Stream-line diffusion techniques that are presented in [Citation12], have been also used for developing space-time finite element methods for conservation laws and fluid flow problems, see e.g. [Citation13,Citation14] and the references there. In [Citation15,Citation16], the stability of Petrov–Galerkin discretizations of parabolic problems have been studied and stable space-time trial and test functions have been proposed. In [Citation17], conforming space-time finite element approximations to parabolic problems have been investigated. In [Citation18], upwind-stabilized single-patch space-time Isogeometric analysis (IgA) schemes for parabolic evolution problems are proposed. Recently in [Citation19,Citation20], the authors based on [Citation18], analyzed a time discontinuous Galerkin multipatch IgA scheme and demonstrated the efficiency of a space-time solver implemented on a parallel environment.

In this paper, we focus on the model problem tuκΔu=f, with zero initial and boundary conditions, and the diffusivity parameter κ is positive and constant. Following standard procedures, e.g. Nitsche techniques for imposing weakly boundary conditions, see [Citation21], the current analysis can be extended to more general initial boundary problems. We propose a new space-time finite element method, which is stabilized by introducing classical bubble spaces, see [Citation22–24]. The bubble basis functions vanish on the edges of the mesh elements and, in addition, do not affect the continuity properties of the solution. By enriching in that way the initial finite element space, the numerical solution consists of two components, where the first lives in the initial finite element space, and the second lives in the bubble space. For developing our analysis, we are motivated and inspired by the subgrid scale stabilization techniques presented in [Citation25,Citation26], for solving linear first-order problems. There, the idea is to couple the initial finite element space with new subgrid scale spaces and to construct artificial diffusion terms in these new spaces. The artificial diffusion terms are added in the numerical scheme in order to ensure stability. The innovation in our approach is that, instead of using subgrid spaces on different meshes, we use bubble spaces and the artificial diffusion terms are formed in these spaces. We include a positive parameter θ in the corresponding bubble diffusion terms, that can control the magnitude of the artificial diffusion in the time direction. We prove stability of the discrete problem with respect to the produced norm, which is a mesh depended norm. Also, optimal error estimates for the full numerical solution containing the bubble component are shown. The latter is achieved by choosing the value of θ to be close to the mesh size but independent of κ. During the discretization error analysis, we analytically present the dependence of the constants on to the diffusivity parameter κ. In the end, this helps to have a clear idea, about the form of the constants that appear in the error bounds for the difference between the solution u and the discrete solution uh. In Section 5, we perform tests for different values of κ. To author's knowledge, it is the first time that this type of stabilized space-time finite element methods are presented and analyzed.

The paper is structured as follows. In Section 2, the model parabolic problem is presented. In Section 3, we formulate the stabilized space-time finite element scheme. In Section 4, we present the error analysis and derive the error estimates. We discuss numerical examples in Section 5. The paper closes with the conclusions.

2. The model problem

2.1. Preliminaries

Let Ω be a bounded Lipschitz domain in Rd, d1. Let α=(α1,,αd) be a multi-index of non-negative integers α1,,αd with degree |α|=j=1dαj. For any α, we define the differential operator Dxα=Dx1α1Dxdαd, with Dxj=/xj, j=1,,d. As usual, L2(Ω) denotes the Sobolev space for which Ω|φ(x)|2dx<, endowed with the norm φL2(Ω)=(Ω|φ(x)|2dx)1/2. Let ℓ be a non-negative integer, define H(Ω)={φL2(Ω):DxαφL2(Ω), for all |α|}, the standard Sobolev spaces endowed with the following norms φH(Ω)=(0|α|DxαφL2(Ω)2)1/2, and seminorms |φ|H(Ω)=(|α|=DxαφL2(Ω)2)1/2. Also we define the subspace H01(Ω) of H1(Ω) H01(Ω)={φH1(Ω):φ=0 on ∂Ω}. Let I=[0,T] with T>0 be the time interval. For later use, we define the space-time cylinder Q=Ω×(0,T) and its boundary parts Σ=∂Ω×(0,T), ΣT=Ω×{T} and Σ0=Ω×{0}, see an illustration Figure (a). We denote the gradient by φ=(xφ,tφ), where xφ is the gradient with respect to the spatial variables. Similarly, we denote by n=(nx,nt) the normal component on Q, with nx the components related to space direction and nt the component related to time direction. Let ,m be positive integers, for functions defined in Q, we define the Sobolev spaces (1a) H,m(Q)={φL2(Q):DxαφL2(Q) with 0|α|, and tiφL2(Q), i=1,,m}(1a) and the subspaces (1b) H01,0(Q)={φL2(Q):xφ[L2(Q)]d, φ=0 on Σ},(1b) (1c) H0,0¯1,1(Q)={φL2(Q):xφ[L2(Q)]d, tφL2(Q),φ=0 on Σ,φ=0 on ΣT},(1c) (1d) H0,0_1,1(Q)={φL2(Q):xφ[L2(Q)]d, tφL2(Q),φ=0 on Σ, φ=0 on Σ0}.(1d) For a function φH,m(Q) with ,m1, we define the norms and the seminorms (2a) φH,m(Q):=|α|DαφL2(Q)2+i=0mtiφL2(Q)21/2,(2a) (2b) |φ|H,m(Q):=|α|=DαφL2(Q)2+tmφL2(Q)21/2.(2b)

Figure 1. (a) The space-time domain Q with the boundary parts and its mesh Th(Q). (b) The bubble function on the reference triangular mesh element. (c) The bubble function on the reference rectangular mesh element.

Figure 1. (a) The space-time domain Q with the boundary parts and its mesh Th(Q). (b) The bubble function on the reference triangular mesh element. (c) The bubble function on the reference rectangular mesh element.

We recall Hölder's and Young's inequalities (3) QuvdxuL2(Q)vL2(Q)andQuvdxϵ2uL2(Q)2+12ϵvL2(Q)2,(3) that hold for all uL2(Q) and vL2(Q) and for any fixed ϵ(0,).

We will use the following Poincare's inequality: Let ΩRd, d=1,2, be a bounded rectangular domain and let Γ∂Ω with |Γ|>0. For simplicity we assume that Γ lies on the plane with x1=0. Let vC(Ω) and v(xΓ)=0 for all xΓΓ. For any interior point x=(x1,,xd), we have (4) v(x1,,xd)=v(xΓ)+xΓ,1x1vx1(τ,x2,,xd)dτ.(4) The first inequality in (Equation3) yields (5) (v(x1,,xd))2=xΓ,1x11vx1(τ,x2,,xd)dτ2CΩxΓ,1x1vx1(τ,x2,,xd)2dτ,(5) where the constant CΩ depends on the length of Ω. Integrating (Equation5) over Ω, we can obtain (6) Ωv2(x)dxCΩ2Ω(x1v)2dx.(6) We refer to [Citation27] for a proof of (Equation6) for more general domains Ω.

In what follows, positive constants c and C appearing in inequalities are generic constants which do not depend on the mesh-size h and on u. In many cases, we will indicate on what may the constants depend for an easier understanding of the proofs. We will write ab meaning that cabCa, with c,C generic constants.

2.2. The model parabolic problem

In the space-time cylinder Q¯=Ω¯×[0,T], with ΩRd,d=1,2,3, we consider the initial boundary value problem (7) utκΔu=f in Qandu=0 on Σ,u(,0)=u0 on Σ0,(7) as a model problem, where the diffusivity parameter 0<κ1 is taken to be constant, f:QR, with fL2(Q), and u0:ΩR, with u0L2(Ω) are given functions, and u:Q¯R is the unknown. Using the standard procedure and integration by parts with respect to both x and t, we can easily derive the following space-time variational formulation of (Equation7): find uH01,0(Q) such that (8) a¯(u,v)=l¯(v), for all vH0,0¯1,1(Q)(8) with (9) a¯(u,v)=Qu(x,t)tv(x,t)dxdt+κQxu(x,t)xv(x,t)dxdt,(9) (10) l¯(v)=Qf(x,t)v(x,t)dxdt+Ωu0(x)v(x,0)dx.(10)

The variational problem (Equation8) is known to have a unique weak solution, see [Citation28] and in [Citation29,Citation30] for a more comprehensive analysis on existence and uniqueness results. For simplicity, we only consider homogeneous Dirichlet boundary conditions on Σ and u0=0. However, the analysis presented in this paper can easily be generalized to other constellations of boundary conditions.

Assumption 2.1

We assume that the solution u of (Equation8) belongs to V0,0_:=H0,0_1,1(Q)Hs(Q) with some s2.

Note that in Assumption 2.1 we require uniform regularity properties for the solution in x and t directions. In the following Sections we are going to present the discretization error analysis based on Assumption 2.1. In [Citation19,Citation20], error estimates have been given for Isogeometric Analysis methods considering anisotropic regularity properties for the solution u.

3. The discrete problem

3.1. A usual finite element scheme

Let Th(Q) be a partition of space-time domain Q into triangular (or quadrilateral elements), that is Q¯=EThE, see Figure (a). We denote by hE the diameter of ETh(Q) and the mesh size is defined as h=maxE{hE}. We assume that Th(Q) is uniform, i.e. there exists a positive number Cun, such that ρEh/Cun, where ρE is the diameter of the circle inscribed in ETh(Q). Associated with Th(Q), we define the finite element subspace Vh0 of H0,0_1,1(Q), consisting of continuous functions in space and in time, by (11) Vh0={vhH0,0_1,1(Q):vh|EPp(E), for every ETh(Q)},(11) where Pp(E) is the polynomial space of total degree p, see e.g. [Citation31–33]. In our analysis we focus on the case p=1.

The usual finite element approximation of (Equation7) would read: find uhVh0 such that (12a) a(uh,vh)=(f,vh) vhVh0,(12a) where (12b) a(uh,vh)=Qtuhvhdxdt+κQxuhxvhdxdt.(12b) Setting vh=uh in (Equation12a) and using the identity 2Quhuhdxdt=Qt(uh2)dxdt=ΣTuh2ds, we have uhL2(ΣT)2+κxuhL2(Q)2fL2(Q)uhL2(Q), and by inequalities (Equation3) and (Equation6), we can obtain the following estimate (13) 12uhL2(ΣT)2+κ2xuhL2(Q)22CΩ2κfL2(Q)2,(13) where CΩ is the constant that appears in (Equation6). In the stability estimate (Equation13) the control of xuh can be very poor if the parameter κ is very small. Furthermore (Equation13) does not provide a direct control of tuhL2(Q). Thus in the case where κ is small, the finite element scheme (Equation12) may not perform well. Therefore it is crucial to improve the stability properties of (Equation12). Next we present a technique for stabilizing the finite element scheme (Equation12) by adding artificial diffusion terms, which do not deteriorate the approximate properties of the method. The idea is to enrich the original finite dimensional space by adding a bubble function space, and then to construct the artificial diffusion terms in this space.

3.2. The stabilized scheme

We introduce the larger finite subspace Vh,b of H0,0_1,1(Q) that can be written as a direct sum as follows (14) Vh,b={vhH0,0_1,1(Q):vh|EP1(E)VB(E), for every ETh(Q)},(14) with VB(E):=VB|E, where VB denotes the space of bubble functions, that vanish entirely on the boundary of the mesh elements and have exactly one degree of freedom in each ETh(Q). For example, in case of triangular elements, it is spanned by a cubic functions VB:={vbH01(Q):vb|E=CEλ1λ2λ3}, where λi,i=1,2,3 are linear polynomials vanishing on one side of E and taking the value one at the opposite vertex. The constant CE is chosen such that maxxEvb(x)=1. Thus, every bubble basis function φVB(E) satisfies, (i) φ(x)>0 for xE, (ii) φ(x)=0 for xE, and (iii) Eφ2(x)dx=CEhE2, with CE depending on the uniformity of Th but is independent of hE. An illustration of bubble functions on two-dimensional elements is presented in Figure (b,c).

Based on Vh,b defined in (Equation14), any vhVh,b can be decomposed into two parts, i.e. vh=vh1+vhb with vh1Vh0 and vhbVB. In view of this, we introduce the discrete problem: find uhVh,b such that (15a) a(uh,vh)+bh(uhb,vhb)=(f,vh), vhVh,b,(15a) where a(,) as in (Equation12b) and (15b) bh(uhb,vhb)=θhQtuhbtvhbdxdt,(15b) with θ>0 to be a positive constant, which will be determined later. We recall the following inverse estimate and the scaled trace inequality, see proofs in [Citation31] and in [Citation21].

Lemma 3.1.

Let vH1(Q), vhVh,b and let a mesh element ETh(Q). Then there exist constants cinv, ctrac>0 independent of h such that (16) vhL2(E)cinvh1vhL2(E),(16) (17) vL2(E)ctrach1/2(vL2(E)+hvL2(E)).(17)

For convenience, we introduce the discrete bilinear form (18) ah(uh,vh)=a(uh,vh)+bh(uhb,vhb),(18) and the associated mesh dependent norm (19) vhh=(κxvhL2(Q)2+θhtvhbL2(Q)2+12vhL2(ΣT)2)1/2.(19) Note that, the terms with the time derivatives in (Equation19) are related to the bubble function space.

Lemma 3.2.

The discrete form ah(,):Vh,b×Vh,bR defined in (Equation18), is Vh,b-coercive with respect to the norm h, i.e., (20) ah(vh,vh)Csvhh2, vhVh,b.(20)

Proof.

Let vhVh,b. Since vh(x,0)=0 and nt|Σ=0, it follows by Green's formula Qtvhvh+vhtvhdxdt=Qntvh2ds, that (21) Qtvhvhdxdt=12Qtvh2dxdt=12ΣTvh2ds12Σ0vh2ds=12vhL2(ΣT)2.(21) The definition of ah and (Equation21) imply (22) ah(vh,vh)=Q12tvh2+θh(tvhb)2+κ|xvh|2dxdt=12vhL2(ΣT)2+κxvhL2(Q)2+θhtvhbL2(Q)2,(22) which is (Equation20) with Cs=1 and this completes the proof.

Proposition 3.1.

Let uh be the solution given by (Equation15). Then there is a Cκ,Ω>0 such that the solution uh satisfies the following a priori estimate (23) uhhCκ,ΩfL2(Q).(23)

Proof.

Using uhVh,b as a test function in (Equation15), and utilizing (Equation3) and (Equation20)) together with the Poincare inequality (Equation6), we successively obtain (24) Csuhh2ah(uh,uh)1κ1/2Qκ1/2fuhdxdtCΩ1κ1/2fL2(Q)κ1/2xuhL2(Q)CΩ1κfL2(Q)(κxuhL2(Q)2+12uhL2(ΣT)2+θhtuhbL2(Q)2)1/2,(24) where we have previously used that Cs=1 and κ1. Setting Cκ,Ω=CΩ(1/κ) we get (Equation23).

Note that the estimate in (Equation23) provides a direct control of tuhbL2(Q)2 due to the appearance of b(,) in the finite element scheme (Equation15), cf. (Equation13). A direct result of (Equation23) and (Equation20) is the following corollary.

Corollary 3.1.

The discrete problem defined in (Equation15) is well posed, i.e. it has a unique solution which satisfies the stability estimate (Equation23).

Next, we show the boundedness of a(,) on V0,0_×Vh,b, where the space V0,0_ is defined in Assumption 2.1. We define the norms (25a) vh,=(κxvL2(Q)2+θhtvL2(Q)2+12vL2(ΣT)2)1/2,(25a) (25b) vh,V=(κxvL2(Q)2+θhtvL2(Q)2+12vL2(ΣT)2+(θh)1vL2(Q)2)1/2.(25b) We point out that the h, is defined for all vV0,0_ and is similar to the h given in (Equation19), which is defined for all vhVh,b. The mesh-dependent norm h,V will be used later for deriving bounds for the discretization error.

Lemma 3.3.

There is a constant Cb(κ,θ,h)>0 such that (26) |a(u,vh)|Cb(κ,θ,h)uh,Vvhh, (u,vh)(V0,0_×Vh,b).(26)

Proof.

Let vh=vh1+vhbVh,b. We treat every term of the form a(,) separately. We apply integration by parts and (Equation3) to infer (27) Qtuvhdxdt=Qutvhdxdt+ΣTuvhdσ((θh)1uL2(Q)2)1/2((θh)tvhL2(Q)2)1/2+uL2(ΣT)vhL2(ΣT)(16)((θh)1uL2(Q)2)1/2c1θhh2κκvhL2(Q)21/2+212uL2(ΣT)21/212vhL2(ΣT)21/2(6)(θh)1uL2(Q)21/2(c2θ(κh)1)1/2κxvhL2(Q)2+θhtvhbL2(Q)2+12vhL2(ΣT)21/2+2uL2(ΣT)κxvhL2(Q)2+θhtvhbL2(Q)2+12vhL2(ΣT)21/2(c2θ(κh)1)1/2uh,Vvhh+2uh,Vvhhc3(θ(κh)1+1)1/2uh,Vvhh,(27)

where c3 depends on the constants appearing in (Equation16) and (Equation6). Similarly for the second term, applying (Equation3), we get (28) Qκ1/2xuκ1/2xvhdxdt(κxuL2(Q)2)1/2(κxvhL2(Q)2)1/2uh,Vvhh.(28) Combining all the above bounds and setting Cb(κ,θ,h)=2c3(θ(κh)1+1)1/2, we can derive the desired result.

4. Error analysis

Proposition 4.1

weak consistency

Let Assumption 2.1 hold and let uh the solution given by (Equation15), and furthermore let zhVh,b and vh1Vh0. Then (29a) ah(uh,zh)=a(u,zh),and(29a) (29b) ah(vh1,zh)=a(vh1,zh).(29b)

Proof.

Multiplying (Equation7) by zhVh,b, integrating over Q, and then applying integration by parts, we arrive at the variational identity (30) a(u,zh)=(f,zh).(30) We recall the problem (Equation15) and directly have (31) ah(uh,zh)=(f,zh)=a(u,zh).(31) Furthermore, we observe that bh(vh1,zh)=0 for any vh1Vh0, and (Equation29b) directly follows.

Lemma 4.1.

Let uh solve (Equation15) and let zh1Vh0. Under Assumption 2.1, there exists a c, independent of h such that (32) (uuhL2(ΣT)2+κxuxuhL2(Q)2+θhtuhbL2(Q)2)cκ(uzh1L2(Q)2+uzh1L2(ΣT)2).(32)

Proof.

Let zh1 be a function in Vh0. By (Equation29) and by subtracting similar terms, we have that (33) Q(tuhtzh1)φh+κQx(uhzh1)xφh+θhQtuhbtφhb=Q(tutzh1)φh+κQx(uzh1)xφh, φhVh,b.(33) Setting above φh=uh1+uhbzh1 and applying integration by parts on the first term on the left side, we have (34) ΣT|tuhtzh1|2dσ+κQ|x(uhzh1)|2dxdt+θhQ|tuhb|2dxdt1κQ|tutzh1|21/2κQ|uhzh1|21/2+Qκ|x(uzh1)|21/2Qκ|x(uhzh1)|21/2,(34) and by applying (Equation3) and (Equation4) on the right hand side, yields (35) uhzh1L2(ΣT)2+κxuhxzh1L2(Q)2+θhtuhbL2(Q)21cϵκtutzh1L2(Q)2+cϵκxuhxzh1L2(Q)2+κcϵxuxzh1L2(Q)2+cϵκxuhxzh1L2(Q)2.(35) Gathering the same terms and setting 0<cϵ<12, we get (36) (12cϵ)(uhzh1L2(ΣT)2+κxuhxzh1L2(Q)2+θhtuhbL2(Q)2)1cϵκtutzh1L2(Q)2+κcϵxuxzh1L2(Q)2+uzh1L2(ΣT)2.(36) Using 0<κ1, applying triangle inequality and setting c=(1/(12cϵ))(1/cϵ), the assertion follows.

Below we give the main error bound for the finite element solution uhVh,b.

Theorem 4.1.

Let uh=uh1+uhb solve (Equation15). Under Assumption 2.1 and choosing θh, there exist a constant c,V, depending on cinv in (Equation16), such that (37) uuhh,2c,V2(μ1(κ,θ,h)uzh1h,V2+μ2(κ,θ,h)uzh1L2(Q)2),for zh1Vh0,(37) where μ1(κ,θ,h)=(1+γ~2(κ,θ,h)+γ~3(κ,θ,h)+γ~(κ,θ,h)) and μ2(κ,θ,h)=γ~2(κ,θ,h)h2, with γ~(κ,θ,h)=(θh)1/2γ(κ,θ,h) and γ(κ,θ,h)=(1/(θh)1/2+cinvκ1/2/h).

Proof.

Let us consider the functions zh1Vh0 and σh=(uh1+uhb)zh1. Using triangle inequality, we decompose the error as (38) 12uuhh,2=12((θh)tutuhL2(Q)2+κxuxuhL2(Q)2+12uuhL2(ΣT)2)(θh)tutzh1L2(Q)2+κxuxzh1L2(Q)2+12uzh1L2(ΣT)2T1+(θh)tuh1tzh1L2(Q)2T2+(θh)tuhb0tzhbL2(Q)2+κxuhxzh1L2(Q)2+12uhzh1L2(ΣT)2T3uzh1h,V2+T2+T3,(38) where we previously set T1:=uzh1h,2, T2:=(θh)tuh1tzh1L2(Q)2, T3:=σhh2, and in the last inequality we used that T1uzh1h,V2. We will proceed by giving bounds for every term appearing in (Equation38). We first show few auxiliary results. Let vhVh,b and σh1=uh1zh1, then using (Equation16), (Equation18) and (Equation29) and the fact that 0<h,θ,κ1, we can obtain that (39) tuh1tzh1L2(Q)=tσh1L2(Q)supvhVh,b|Qt((uh1+uhb)zh1uhb)vhdxdt|vhL2(Q)supvhVh,bQtuhbvh+κxσhxvh+θhtuhbtvhbdxdtvhL2(Q)+supvhVh,bQt(utzh1)vh+κx(uzh1)xvhvhL2(Q)(16)(θh)1/2(θh)1/2(tuhbL2(Q)+cinvθtuhbL2(Q)))+t(uzh1)L2(Q)+κ1/2(κ1/2x(uzh1)L2(Q)+κ1/2xσhL2(Q)))supvhVh,bvhL2(Q)vhL2(Q)c0(θh)1/2(θhtuhbL2(Q)2+κxσhL2(Q)2+12σhL2(ΣT)2)1/2+cinvκ1/2h(θhtuhbL2(Q)2+κxσhL2(Q)2+12σhL2(ΣT)2)1/2+cinvκ1/2h(κ1/2x(uzh1)L2(Q))+(θh)1/2(θh)1/2t(uzh1)L2(Q)c01(θh)1/2+cinvκ1/2hσhh+1(θh)1/2+cinvκ1/2huzh1h,Vc0γ(κ,θ,h)(uzh1h,V+σhh),(39) where we previously set c0=(1+θcinv). Using (Equation39) and the relation (40) (θh)1/2tuh1tzh1L2(Q)+(θh)1/2tuhb0tzhbL2(Q)(θh)1/2t(uh1+uhb)tzh1L2(Q),(40) and observing that (θh)1/2γ(κ,θ,h)1, it follows that (41) (θh)1/2tσhL2(Q)2c0(θh)1/2γ(κ,θ,h)(uzh1h,V+σhh).(41) Furthermore, working as in the proof of (Equation26) and using (Equation41) and (Equation3), we can find (42) a(uzh1,σh)=Q(uzh1)tσhdxdt+ΣT(uzh1)σhdσ+Qκ1/2x(uzh1)κ1/2xσhdxdt((θh)1uzh1L2(Q)2)1/2((θh)tσhL2(Q)2)1/2+uzh1L2(ΣT)σhL2(ΣT)+(κx(uzh1)L2(Q)2)1/2(κxσhL2(Q)2)1/22c0((θh)1uzh1L2(Q)2)1/2(θh)1/2γ(κ,θ,h)(uzh1h,V+σhh)+2uzh1h,Vσhh(θh)1/2γ(κ,θ,h)uzh1h,V2+2c0h1uzh1L2(Q)hγ(κ,θ,h)σhh+2uzh1h,Vσhh(θh)1/2γ(κ,θ,h)uzh1h,V2+2cεh2uzh1L2(Q)2+εh2γ2(κ,θ,h)σhh2+cεuzh1h,V2+εσhh2(θh)1/2γ(κ,θ,h)uzh1h,V2+2cεh2uzh1L2(Q)2+ε(hθ1+cinvκ)σhh2+cεuzh1h,V2+εσhh2,(using that θh)2cε(θh)1/2γ(κ,θ,h)uzh1h,V2+2cεh2uzh1L2(Q)2+2εCinv,κσhh2,(42) where we used that (θh)1/2γ(κ,θ,h)>1, we chose cε>1, and in the last step we set Cinv,k=1+cinvκ. Furthermore, using the properties of ah(,) and (Equation29), we have (43) Csσhh2ah(σh,σh)=ah(uh,σh)ah(zh1,σh)=(29)a(u,σh)a(zh1,σh)=a(uzh1,σh).(43) By replacing Cs=1 and by choosing ε1/4Cinv,κ in (Equation42), we obtain that (44) 12σhh22cε((θh)1/2γ(κ,θ,h)uzh1h,V2+h2uzh1L2(Q)2).(44) Now, we can bound the terms in (Equation38). Recalling the definition of γ~(κ,θ,h), inequality (Equation44) immediately implies (45) T3=σhh2Cεγ~(κ,θ,h)uzh1h,V2+Cεh2uzh1L2(Q)2.(45) Also, combining (Equation39) and (Equation45), we have that (46) T2=θhtuh1tzh1L2(Q)22γ~2(κ,θ,h)(uzh1h,V2+σhh2)2Cε(γ~2(κ,θ,h)uzh1h,V2+γ~2(κ,θ,h)γ~(κ,θ,h)uzh1h,V2+γ~2(κ,θ,h)h2uzh1L2(Q)2)2Cε((γ~2(κ,θ,h)+γ~2(κ,θ,h)γ~(κ,θ,h))uzh1h,V2+γ~2(κ,θ,h)h2uzh1L2(Q)2).(46) Finally, inserting the bounds (Equation46) and (Equation45) in (Equation38) and using that γ~21, we obtain (47) 12uuhh,22Cε(1+γ~2(κ,θ,h)+γ~2(κ,θ,h)γ~(κ,θ,h)+γ~(κ,θ,h))uzhh,V2+2Cε2γ~2(κ,θ,h)h2uzh1L2(Q)2.(47) Setting c,V2=4Cε, we can derive estimate (Equation37).

Remark 4.1

Let us consider a fixed Th(Q) and let us recall the forms of μ1(κ,θ,h) and μ2(κ,θ,h) in (Equation37). Then (i) setting a fixed value θ=θc, we have μ1(κ,θc,h)θch1+θc1+1/2h(1+1/2)+θc1/2h1/2 and μ2(κ,θc,h) h2+θch3, (ii) setting θh, we have that μ1(κ,θ,h)cinvκ and μ2(κ,θ,h)h2. Note that in the previous cases (i) and (ii), the associated constants depend on cinv and κ.

Below, we recall some approximation estimates of the finite element space. For the proof we refer to [Citation31].

Lemma 4.2.

Let s, m be integers such that 0m1<s and let the space Vh0 defined in (Equation11). Then for every vV0,0_ with V0,0_=H0,0_1,1(Q)Hs(Q), there exists a linear interpolation operator πhv:VVh0 such that (48) |vπhv|Hm(Q)cintphmin(p+1,s)mvHs(Q),(48) where cintp=c(m,s,Q) and p=1.

Lemma 4.3.

Let the space Vh0 defined in (Equation11). Let s2 be an integer, and let a function vV0,0_ with V0,0_=H0,0_1,1(Q)Hs(Q). There exists a linear interpolation operator πhv:VVh0 such that (49a) vπhvL2(ΣT)2c1h2r1vHs(Q)2,(49a) (49b) vπhvh,V2c2h2r1(κh1+θ+θ1+1)vHs(Q)2,(49b) where r=2 and c1,c2 depend on the constants appearing in (Equation17) and in (Equation48), but not on h and v.

Proof.

Introducing the operator πhv of Lemma 4.2 and by applying (Equation17) and (Equation48), we have (50) uπhvL2(ΣT)22ctrac2h1(vπhvL2(Q)2)+h2(vπhv)L2(Q)2)c1h2r1vHs(Q)2.(50) In the same way, we have (51) κx(vπhv)L2(Q)2cintpκh2r2vHs(Q)2,θht(vπhv)L2(Q)2cintpθh2r1vHs(Q)2,(θh)1(vπhv)L2(Q)2cintpθ1h2r1vHs(Q)2,(51) Collecting the estimates (Equation50) and (Equation51), we easily obtain (52) vπhvh,V2c2(κh2r2+θh2r1+θ1h2r1+h2r1)vHs(Q)2,(52) which is (Equation49b).

Remark 4.2

The interpolation estimates given in (Equation49) have been derived for linear polynomial spaces, see (Equation11). Analogous estimates can be derived for higher polynomial spaces. In that case we set r=min(p+1,s).

In the proposed scheme (Equation15), the parameter θ can control the artificial diffusion terms. Its value can be adjusted according to the needs of the scheme for obtaining optimal approximation properties, see Remark 4.1. Below, we show that if θ is close to the grid size h, we obtain optimal order of convergence. The value of θ can be determined without having to tune it with respect to κ. However, in some finite element schemes the value of θ must be adjusted with respect to h and κ for getting optimal rates, e.g. see discussion for the Galerkin/least square methods in [Citation24,Citation33].

Theorem 4.2

error estimates

Let u be the solution of (Equation7) and let uh be the solution of (Equation15), respectively. Under the Assumption 2.1, the solution uh satisfies the estimate (53) uuhh,c1huHs(Q),for θh,(53) and moreover for any θ>0, (54) (uuhL2(ΣT)2+κxuxuhL2(Q)2+θhtuhbL2(Q)2)1/2c2κhuHs(Q),(54) with c1 depending on the constants in (Equation37) and in (Equation49) and c2 on the constants in (Equation32) and (Equation48).

Proof.

The estimate (Equation53) follows directly from (Equation29), (Equation37), Remark (4.1) and (Equation49b). The estimate (Equation54) follows form (Equation32) and (Equation48).

Remark 4.3

In realistic cases, the solutions of parabolic evolution problems may present an anisotropic regularity behavior, for example different regularities properties with respect to time and to space direction. This may result in the case where the contribution of the discretization error in t direction can be different than the contribution of the discretzation error in x direction. In such cases, it is more appropriate to discretize the problem using anisotropic meshes, using small mesh size in the directions where the solution is less smooth and larger mesh size in the directions where the solution is smoother [Citation34]. This is a topic that we will investigate in a forthcoming paper. A discretization of these type of problems using Isogeometric Analysis methodology is presented in [Citation20].

Remark 4.4

For the sake of simplicity, we have presented the discretization analysis for spaces with degree p=1. However, assuming further regularity properties on u, we can follow the same analysis and to show optimal estimates for spaces with degree p>1, see Example 2 in Section 5.

5. Numerical examples

In this section, we present several numerical examples for validating the theoretical estimates. Although in the analysis, we used linear polynomial spaces, next we perform tests using both linear, (p=1), and second order, (p=2), polynomial spaces, which are combined with the associated cubic bubble space. We perform tests for QRd+1 with d=1 and d=2, using triangular and tetrahedral mesh elements correspondingly. One can apply the proposed method for solving problems on QRd+1 with d=3. The code that we have at our disposal does not support such calculations yet. Every example has been solved applying several mesh refinement steps with corresponding mesh size hs=(h0/2s), s=1,2,. Every Ths(Q) satisfies the properties mentioned in Section 3. We present tables with the asymptotic convergence rates r of the error. The convergence rates r have been computed by the ratio r=ln(es/es+1)/ln(hs/hs+1), where the error es:=uuhh, is computed on Ths(Q). We mention that we use highly smooth solutions, i.e. min(p+1,s)=p+1, and thus the expected values for the rates are r=p, see (Equation49b) and Remark 4.2. We consider test cases with κ{1,0.005}, and we study the behavior of the rates for θ=hs. Lastly, we point out that since the support of a bubble function is restricted to the interior of the element, we eliminate the associated variable from the produced linear system by static condensation.

Example 1: QR2, p=1. In the first example, the problem is considered in Q=(0,1)×(0,2). The exact solution is given by the formula (55) u(x,t)=sin(2πx)sin(πt).(55)

The source function f is determined by (Equation55). Note that u=0 on Σ and u0=0, see (Equation7). In Figure , we plot the exact solution on Q. We solve the problem using linear polynomials, i.e. p=1. We begin by first setting κ=1. The numerical convergence rates for the several levels of the mesh refinement are presented in the second column in Table . They are in good agreement with the theoretically predicted estimates given in (Equation53). The numerical solution uhVh,b gives optimal convergence rates, i.e. the values of r are very close to one for all the refinement steps. Next, we want to investigate the asymptotic behavior of the numerical convergence rates when the value of κ is small. We perform the same computations by setting κ=0.005. The associated convergence rates are presented in the last column in Table . We observe that for the first mesh levels, the rates r are a little higher than the expected value. However, as we move on to the last mesh levels, the values of r are close to one, and are in agreement with the values predicted by the theory.

Figure 2. Example 1: The solution u on Q.

Figure 2. Example 1: The solution u on Q.

Table 1. Example 1: The convergence rates r.

Example 2: QR2, p=2. In the second example, we consider the problem on Q=(0,1)×(0,1). The exact solution is given by the formula (56) u(x,t)=sin(2πt)sin(2πx).(56) The source function f is defined to match the solution in (Equation56). In Figure , we plot the exact solution u on a relative coarse mesh with h=0.25. We solve the problem using second order, i.e. p=2, polynomial space. For the first group of computations we set κ=1 and θ=hs. In the second column in Table , we show the convergence rates r. The values of r are approaching the value two, and are the expected rates based (Equation49b) and Remark 4.2. We repeat the same computations setting κ=0.005 and keep the same values for θ. The produced rates r are shown in the last column in Table . We observe that, for the last mesh levels, the rates are approaching the expected value r=2. We can see again that the asymptotic convergence behavior of the error is the same for both values of κ. Example 3: QR3, p=1. In this example, the problem is considered on Q=Ω×(0,1) with Ω=(0,1)2. The exact solution is given by the formula (57) u(x,y,t)=(cos(2π(xy))cos(2π(x+y)))sin(2πt).(57) Note that u=0 on Σ and u0=0. The function f is determined by (Equation57). In Figure , we plot the contours of u for t=0.8. The problem has been solved on a sequence of meshes, as in the previous tests, using linear polynomial space, i.e. p=1. We perform similar computations as before. In the second column in Table , we can see the convergence rates for κ=1. The last column in Table  shows the rates for κ=0.005. In both cases, the rates are optimal for linear polynomial spaces and are in agreement with the theoretical results in Theorem 4.2.

Figure 3. Example 2: The solution u on Q.

Figure 3. Example 2: The solution u on Q.

Figure 4. Example 3: The solution u on QR3.

Figure 4. Example 3: The solution u on Q⊂R3.

Table 2. Example 2: The convergence rates r.

Table 3. Example 3: The convergence rates r.

Finally, we can conclude that the proposed bubble stabilization finite element scheme performs well for all the examples. The produced numerical solution gives optimal order of convergence in the h,-norm, when the problems have smooth solutions.

6. Conclusions

In this article, we have proposed and analyzed a bubble stabilized space-time finite element method for solving linear parabolic evolution problems. The construction of the method was based on a space-time variational formulation of the initial PDE problem, which allows the unified space-time discretization by finite element techniques. We presented a discretization error analysis and proved that the method has optimal convergence properties, when θh and the PDE problem has a smooth solution. The convergence properties are not affected by the choice of the value of the diffusion parameter κ, which appears in the PDE problem. The theoretical results have been verified by performing several numerical examples. A possible extension of our work here is to combine it with time or space-time mesh adaptivity techniques.

Acknowledgements

The author wish to thank Andreas Schafelner for the further validation of the results in Section 5.

Disclosure statement

No potential conflict of interest was reported by the author.

Additional information

Funding

This work was supported by the Austrian Science Fund (FWF) [grant number NFN S117-03].

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