Research article Special Issues

W1,-seminorm superconvergence of the block finite element method for the five-dimensional Poisson equation

  • This study focused on the superconvergence of the finite element method for the five-dimensional Poisson equation in the W1,-seminorm. Specifically, we investigated the block finite element method, which is a tensor-product finite element approach applied to regular rectangular partitions of the domain. First, we introduced the finite element scheme for the equation and discussed various functions related to it, along with their properties. Next, we proposed a weight function and established its important properties, which play a crucial role in the theoretical analysis. By utilizing the properties of the weight function and employing weighted-norm analysis techniques, we derived an optimal order estimate in the W2,1-seminorm for the discrete derivative Green's function (DDGF). Furthermore, we provided an interpolation fundamental estimate of the second type, also known as the weak estimate of the second type, for the block finite element. This weak estimate is based on a five-dimensional interpolation operator of the projection type. Finally, by combining the derived W2,1-seminorm estimate for the DDGF and the weak estimate for the block finite element, we obtained a superconvergence estimate for the block finite element approximation in the pointwise sense of the W1,-seminorm. The correctness of the theoretical results was demonstrated through a numerical example.

    Citation: Jinghong Liu. W1,-seminorm superconvergence of the block finite element method for the five-dimensional Poisson equation[J]. AIMS Mathematics, 2023, 8(12): 31092-31103. doi: 10.3934/math.20231591

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  • This study focused on the superconvergence of the finite element method for the five-dimensional Poisson equation in the W1,-seminorm. Specifically, we investigated the block finite element method, which is a tensor-product finite element approach applied to regular rectangular partitions of the domain. First, we introduced the finite element scheme for the equation and discussed various functions related to it, along with their properties. Next, we proposed a weight function and established its important properties, which play a crucial role in the theoretical analysis. By utilizing the properties of the weight function and employing weighted-norm analysis techniques, we derived an optimal order estimate in the W2,1-seminorm for the discrete derivative Green's function (DDGF). Furthermore, we provided an interpolation fundamental estimate of the second type, also known as the weak estimate of the second type, for the block finite element. This weak estimate is based on a five-dimensional interpolation operator of the projection type. Finally, by combining the derived W2,1-seminorm estimate for the DDGF and the weak estimate for the block finite element, we obtained a superconvergence estimate for the block finite element approximation in the pointwise sense of the W1,-seminorm. The correctness of the theoretical results was demonstrated through a numerical example.



    Superconvergence is a crucial topic in the research field of Galerkin finite element methods. With advancements in research technologies, numerous superconvergence results have been obtained and a theoretical framework on superconvergence has been established [1,2,3,4]. Notably, superconvergence research in the finite element method is closely associated with the dimensions of the problems. For one- and two-dimensional problems, superconvergence research has been nearly perfect, and significant progress has also been made for the three-dimensional setting [5,6,7,8,9,10,11,12,13,14,15,16,17]. However, for dimensions four and higher, superconvergence results are relatively scarce. One of the primary reasons is the difficulty in estimating the discrete Green's function (DGF) and discrete derivative Green's function (DDGF), which play critical roles in superconvergence research, particularly in pointwise superconvergence [10,12,13,14,18,19,20]. Unfortunately, the high-dimensional DGF and DDGF of dimensions four and higher cannot be straightforwardly extrapolated from those of low-dimensional cases. Consequently, establishing bounds for the high-dimensional DGF and DDGF becomes a vital aspect of researching high-dimensional pointwise superconvergence. Recently, we have obtained some results in this regard [12,14,19]. In this paper, we will illustrate a superconvergence analytic technique by considering a five-dimensional problem as an example, which may be applied to other high-dimensional superconvergence issues. First, by utilizing a weighted-function analysis technique, we will derive an optimal estimate for the W2,1-seminorm of the five-dimensional DDGF. Second, in conjunction with a weak estimate for the finite element approximation, we can obtain a pointwise superconvergence estimate for the derivatives of the finite element approximation. Finally, we validate the theoretical results through a numerical example. It is important to note that although we provide the W1,1-seminorm estimate for the five-dimensional DDGF, we do not discuss its applications to superconvergence [19]. Furthermore, the W2,1-seminorm estimate for the DDGF in this paper is distinct from the W1,1-seminorm estimate in [19]. Additionally, as high-dimensional partial differential equations (PDEs) in dimensions four and higher are encountered in various areas such as financial mathematics, particle physics, statistical physics and general relativity, research on high-dimensional finite element superconvergence holds significant importance.

    In the following, we adhere to the standard notations for the Sobolev spaces and their norms. The symbol C represents a constant that is independent of the discretization parameter h.

    Consider the following Poisson equation with the Dirichlet boundary condition:

    LuΔu=f  inΩ,   u=0  onΩ, (1.1)

    where ΩR5 is a bounded polytopic domain. The weak formulation of problem (1.1) is finding uH10(Ω) such that

    a(u,v)=(f,v)vH10(Ω), (1.2)

    where

    a(u,v)Ωuvdx1dx2dx3dx4dx5,  (f,v)Ωfvdx1dx2dx3dx4dx5.

    Let {Th} be a regular family of rectangular partitions of ˉΩ. Denote by Sh(Ω) the space of continuous piecewise tensor-product m-order polynomials with respect to this kind of partition and let Sh0=Sh(Ω)H10(Ω). Discretizing problem (1.2) using Sh0 as approximating space means finding uhSh0 such that a(uh,v)=(f,v) for all vSh0. Here, we have the following Galerkin orthogonality relation:

    a(uuh,v)=0  vSh0. (1.3)

    For every ZΩ, we define the discrete derivative δ function Z,δhZSh0 and the L2-projection PhuSh0 such that [19]

    (v,Z,δhZ)=v(Z)  vSh0,
    (uPhu,v)=0  vSh0,

    where R5 and ||=1. v(Z) stands for the one-sided directional derivative

    v(Z)=lim|ΔZ|0v(Z+ΔZ)v(Z)|ΔZ|, ΔZ=|ΔZ|.

    Remark 1.1. Since ΔZ=|ΔZ|, that is, ΔZ is of the same direction as , provided that the direction is given for, the above limit exists, no matter what direction is given, v(Z) is well defined.

    Let Z,GZH2(Ω)H10(Ω) be the solution of the elliptic problem LZ,GZ=Z,δhZ. We may call Z,GZ the regularized derivative Green's function (RDGF), and denote by Z,GhZ (the so-called DDGF) the finite element approximation to Z,GZ. Thus,

    a(Z,GZZ,GhZ,v)=0  vSh0.

    One of the main tasks of this article is how to obtain the optimal estimate for the Z,GhZ.

    As for Z,δhZ and Ph, we have [19]

    Z,δhZϕαCh5α72,α>0, (1.4)
    Phw1,qCw1,q,5<q. (1.5)

    The rest of the paper is arranged as follows. In section two, we will bound the terms |Z,GZ|2,1 and |Z,GhZ|2,1. Section three is devoted to the weak estimate of the second type for the finite element method, and section four is about W1,-seminorm superconvergence of the finite element approximation. A numerical example is given in section five. Finally, we simply summarize the paper in section six.

    To derive the estimate for the DDGF, we introduce the weight function defined by

    ϕϕ(X)=(|XˉX|2+θ2)52XˉΩ,

    where ˉXˉΩ is a fixed point, θ=γh and γ[5,+) is a suitable real number.

    For every αR, we give the following notations:

    |nv|2=|β|=n|Dβv|2,  |nv|ϕα,Ω=(Ωϕα|nv|2dX)12,  v2m,ϕα,Ω=mn=0|nv|2ϕα,Ω,

    where β=(β1,β2,β3,β4,β5), |β|=β1+β2+β3+β4+β5 and βi0,i=1,2,3,4,5 are integers. In particular, for the case of m=0, we write

    vϕα,Ω=(Ωϕα|v|2dX)12.

    As for the weight function ϕ, we have the properties [19]

    |nϕα|C(α,n)ϕα+n5,αR,n=1,2, (2.1)
    ΩϕαdXC(α1)1θ5(α1)α>1, (2.2)
    ΩϕdXC(τ)|lnθ|,θτ<1, (2.3)
    ΩϕαdXC(1α)10<α<1. (2.4)

    In addition, we need to assume that there exists a q0 (5<q0) such that

    L:W2,q(Ω)W1,q0(Ω)Lq(Ω)(1<q<q0)

    is a homeomorphism [4]. It means that for all vW2,q(Ω)W1,q0(Ω), we have the so-called a priori estimate:

    v2,q,ΩC(q)Lv0,q,Ω, (2.5)

    where C(q) denotes a positive constant only depending on q. Next, we give some lemmas used in the proofs of our main results.

    Lemma 2.1. For Z,GZ the RDGF, we have the weighted-norm estimate

    2Z,GZϕ1Ch1|lnh|1720. (2.6)

    Proof. By the triangular inequality, the a priori estimate (2.5) and the definition of Z,GZ, we have

    2Z,GZ2ϕ1=Ω(ϕ12|2Z,GZ|)2dXC(Ω|2(ϕ12Z,GZ)|2dX+Ω|2ϕ12Z,GZ|2dX+Ω|ϕ12|2|Z,GZ|2dX)C(2(ϕ12Z,GZ)20+Z,GZ2ϕ15+|Z,GZ|21,ϕ35)C(L(ϕ12Z,GZ)20+Z,GZ2ϕ15+|Z,GZ|21,ϕ35)C(LZ,GZ2ϕ1+|Z,GZ|21,ϕ35+Z,GZ2ϕ15)CZ,δhZ2ϕ1+C|a(Z,GZ,ϕ35Z,GZ)|+CZ,GZ2ϕ15CZ,δhZ2ϕ1+C|(Z,δhZ,ϕ35Z,GZ)|+CZ,GZ2ϕ15CZ,δhZ2ϕ1+CZ,GZ2ϕ15,

    namely,

    2Z,GZ2ϕ1CZ,δhZ2ϕ1+CZ,GZ2ϕ15. (2.7)

    Further, from the inverse estimate, the stability estimate (1.5), the a priori estimate (2.5) and the Sobolev embedding theorem [21],

    Z,GZ2ϕ15=(ϕ15Z,GZ,Z,GZ)=a(w,Z,GZ)=(Z,δhZ,w)=Phw(Z)|Phw|1,Ch5q|Phw|1,qCh5qw1,qCh5qq45w2,5Ch5qq45ϕ15Z,GZ0,5Ch5qq45ϕ15Z,GZ2,53Ch5qq45L(ϕ15Z,GZ)0,53, (2.8)

    where Lw=ϕ15Z,GZ in Ω and w|Ω=0. Taking q=|lnh| in (2.8) yields

    Z,GZ2ϕ15C|lnh|45L(ϕ15Z,GZ)0,53. (2.9)

    However, from (2.1), the definition of Z,GZ and the triangular inequality,

    L(ϕ15Z,GZ)0,53C(ϕ15LZ,GZ0,53+Z,GZ0,53+ϕ15Z,GZ0,53)=C(ϕ15Z,δhZ0,53+Z,GZ0,53+ϕ15Z,GZ0,53). (2.10)

    In addition, from the H¨older inequality,

    Z,GZ0,53ϕ120,5Z,GZϕ1. (2.11)

    Since [19]

    Z,GZϕ1C|lnh|910, (2.12)

    from (2.2), (2.11) and (2.12),

    Z,GZ0,53Ch2|lnh|910. (2.13)

    Using the H¨older inequality again, we have

    ϕ15Z,δhZ0,53ϕ3100,3Z,δhZϕ1. (2.14)

    From (1.4), (2.2) and (2.14),

    ϕ15Z,δhZ0,53Ch2. (2.15)

    Similarly,

    ϕ15Z,GZ0,53ϕ3100,3Z,GZϕ15Ch1Z,GZϕ15. (2.16)

    From (2.9), (2.10), (2.13), (2.15) and (2.16),

    Z,GZ2ϕ15Ch2|lnh|45+Ch2|lnh|1710+Ch1|lnh|45Z,GZϕ15Ch2|lnh|45+Ch2|lnh|1710+C(ϵ)h2|lnh|85+ϵZ,GZ2ϕ15. (2.17)

    Taking ϵ=12 in (2.17) yields

    Z,GZ2ϕ15Ch2|lnh|1710. (2.18)

    Combining (1.4), (2.7) and (2.18) immediately yields the result (2.6).

    Lemma 2.2. For Z,GZ the RDGF, we have the W2,1-seminorm estimate

    |Z,GZ|2,1Ch1|lnh|2720. (2.19)

    Proof. Obviously,

    |Z,GZ|2,1(ΩϕdX)122Z,GZϕ1. (2.20)

    By (2.3), (2.6) and (2.20), we immediately obtain the result (2.19).

    In order to derive the estimate of the DDGF Z,GhZ, we need the following result [19].

    Lemma 2.3. [19] For Z,GZ and Z,GhZ, the RDGF and the DDGF, respectively, we have

    |Z,GZZ,GhZ|1,1C|lnh|1310. (2.21)

    Now, we can derive the following important estimate.

    Theorem 2.1. For Z,GhZ the DDGF, we have the W2,1-seminorm estimate

    |Z,GhZ|h2,1Ch1|lnh|2720, (2.22)

    where |Z,GhZ|h2,1=eTh|Z,GhZ|2,1,e.

    Proof. We denote by ΠZ,GZ the interpolant of projection type to Z,GZ. Thus, by the triangle inequality, the interpolation error estimate and the inverse property, we have

    |Z,GhZ|h2,1|Z,GZZ,GhZ|h2,1+|Z,GZ|2,1|Z,GZ|2,1+|Z,GZΠZ,GZ|h2,1+|ΠZ,GZZ,GhZ|h2,1C|Z,GZ|2,1+Ch1|ΠZ,GZZ,GhZ|1,1C|Z,GZ|2,1+Ch1|Z,GZΠZ,GZ|1,1+Ch1|Z,GZZ,GhZ|1,1C|Z,GZ|2,1+Ch1|Z,GZZ,GhZ|1,1. (2.23)

    Combining (2.19), (2.21) and (2.23) yields the result (2.22).

    In this section, we first introduce an interpolation operator of projection type, and then derive the weak estimate of the second type for the finite element by using the interpolation operator of projection type.

    Let element

    e=(x1,eh1,e,x1,e+h1,e)×(x2,eh2,e,x2,e+h2,e)×(x3,eh3,e,x3,e+h3,e)×(x4,eh4,e,x4,e+h4,e)×(x5,eh5,e,x5,e+h5,e)I1×I2×I3×I4×I5,

    and let {l1,j(x1)}j=0, {l2,j(x2)}j=0, {l3,j(x3)}j=0, {l4,j(x4)}j=0, {l5,j(x5)}j=0 be the normalized orthogonal Legendre polynomial systems on L2(I1), L2(I2), L2(I3), L2(I4), L2(I5), respectively. Now, let x1x2x3x4x5uL2(e) then we have the following expansion:

    x1x2x3x4x5u=i1=0i2=0i3=0i4=0i5=0αi1i2i3i4i55k=1lk,ik(xk),

    where

    αi1i2i3i4i5=ex1x2x3x4x5u5k=1lk,ik(xk)dX.

    Set

    ωk,0(xk)=1,ωk,j+1(xk)=xkxk,ehk,elk,j(ξ)dξ,  k=1,,5,j0.

    By the Parseval equality for X=(x1,x2,x3,x4,x5)e,

    u(X)=i1=0i2=0i3=0i4=0i5=0βi1i2i3i4i55k=1ωk,ik(xk), (3.1)

    where

    β00000=u(x1,eh1,e,x2,eh2,e,,x5,eh5,e),
    βi10000=I1x1u(x1,x2,eh2,e,,x5,eh5,e)l1,i11(x1)dx1,
    βi1i2000=I1×I2x1x2u(x1,x2,x3,eh3,e,,x5,eh5,e)l1,i11(x1)l2,i21(x2)dx1dx2,
    βi1i2i3i4i5=ex1x2x3x4x5u(X)5k=1lk,ik1(xk)dX,

    where ik1,k=1,,5. Similarly, the other coefficients can also be given.

    We introduce standard tensor-product polynomial spaces of degree m1 denoted by Tm, i.e.,

    q(X)=(i1,i2,i3,i4,i5)Iai1i2i3i4i5xi11xi22xi33xi44xi55,qTm,

    where the indexing set I is as follows:

    I={(i1,i2,i3,i4,i5)|0ikm,k=1,,5}.

    Define the tensor-product interpolation operator of projection type by Πem: H5(e)Tm(e) such that

    Πemu(X)=(i1,i2,i3,i4,i5)Iβi1i2i3i4i55k=1ωk,ik(xk). (3.2)

    By the definitions of the finite element space Sh0(Ω) and Πem, we have the tensor-product interpolation operator of project type

    Πm:H5(Ω)H10(Ω)Sh0(Ω),

    where (Πmu)|e=Πemu.

    For simplicity, we write

    λi1i2i3i4i5=βi1i2i3i4i55k=1ωk,ik(xk).

    Thus, from (3.1) and (3.2),

    uΠemu=(mi1=0mi2=0mi3=0mi4=0i5=m+1+mi1=0mi2=0mi3=0i4=m+1i5=0+mi1=0mi2=0i3=m+1i4=0i5=0+mi1=0i2=m+1i3=0i4=0i5=0+i1=m+1i2=0i3=0i4=0i5=0)λi1i2i3i4i5.

    Next, we will derive the weak estimate of the second type for the finite element.

    Theorem 3.1. Let {Th} be a regular family of rectangular partitions of ˉΩ, uWm+2,(Ω)H10(Ω) and vSh0(Ω) then the tensor-product m-degree interpolation operator of projection type Πm satisfies the weak estimate of the second type

    |a(uΠmu,v)|Chm+2um+2,,Ω|v|h2,1,Ω,  m2, (3.3)

    where |v|h2,1,Ω=eTh|v|2,1,e.

    Proof. By the properties of ωk,i(xk) as well as the orthogonality of the Legendre polynomial system, we have

    e(uΠemu)vdX=ervdXIe eTh,

    where

    r=(mi1=0mi2=0mi3=0mi4=0m+2i5=m+1+mi1=0mi2=0mi3=0m+2i4=m+1m+2i5=0+mi1=0mi2=0m+2i3=m+1m+2i4=0m+2i5=0+mi1=0m+2i2=m+1m+2i3=0m+2i4=0m+2i5=0+m+2i1=m+1m+2i2=0m+2i3=0m+2i4=0m+2i5=0)λi1i2i3i4i5. (3.4)

    Clearly, r only contains finite terms.

    Among the indices ik,k=1,,5, when some ik=m+1 or m+2 and the others are zero, we have by the orthogonality of the Legendre polynomial system

    eλi1i2i3i4i5vdX=0. (3.5)

    For m2, without loss of generality, we assume ik0,k=1,,j and ij+1==i5=0.

    Ii1ij00eλi1ij00vdX=js=1exsλi1ij00xsvdX=js=1Is. (3.6)

    We assume i1m+1; thus, i1m+13. By the orthogonality of the Legendre polynomial system,

    I1=βi1ij00×el1,i11(x1)ω2,i2(x2)ωj,ij(xj)x1vdX=0. (3.7)

    In addition,

    I2=βi1ij00×eω1,i1(x1)l2,i21(x2)ωj,ij(xj)x2vdX=βi1ij00×eD1ω1,i1(x1)l2,i21(x2)ωj,ij(xj)x1x2vdX, (3.8)

    and it is easy to prove

    |βi1ij00|Chm+2j2um+2,,e. (3.9)

    In fact,

    D1ω1,i1(x1)l2,i21(x2)ωj,ij(xj)=O(hj2). (3.10)

    Combining (3.8)–(3.10) yields

    |I2|Chm+2um+2,,e|v|2,1,e. (3.11)

    Similarly, we have

    |Ik|Chm+2um+2,,e|v|2,1,e,k=3,,j. (3.12)

    From (3.6), (3.7), (3.11) and (3.12),

    |Ii1ij00|Chm+2um+2,,e|v|2,1,e,k=3,,j. (3.13)

    When each ik0,k=1,,5, similar to the above arguments, we easily get

    |eλi1i2i3i4i5vdX|Chm+2um+2,,e|v|2,1,e. (3.14)

    From (3.4), (3.5), (3.13) and (3.14),

    |Ie|Chm+2um+2,,e|v|2,1,e.

    Summing over all elements proves the result (3.3).

    In this section, we will give the superconvergent estimate for the m-degree block finite element approximation by using the weak estimate of the second type and the W2,1-seminorm estimate for the DDGF.

    Let uh be the m-degree block finite element approximation to u, the solution of problem (1.2) and Πmu the corresponding interpolant of projection type to u. Thus, we have the following theorem.

    Theorem 4.1. Let {Th} be a regular family of rectangular partitions of ˉΩ and uWm+2,(Ω)H10(Ω) then we have the superconvergent estimate

    |uhΠmu|1,,ΩChm+1|lnh|2720um+2,,m2. (4.1)

    Proof. For every ZΩ, applying the definition of Z,GhZ and the Galerkin orthogonality relation (1.3), we derive

    Z,(uhΠmu)(Z)=a(uhΠmu,Z,GhZ)=a(uΠmu,Z,GhZ). (4.2)

    From (2.22), (3.3) and (4.2), we immediately obtain the result (4.1).

    Example 5.1. Consider the following Poisson equation:

    {Δu=finΩ=(0,1)×(0,1)×(0,1)×(0,1)×(0,1),u=0onΩ,

    where

    f=5π2sin(πx1)sin(πx2)sin(πx3)sin(πx4)sin(πx5).

    The true solution is

    u=sin(πx1)sin(πx2)sin(πx3)sin(πx4)sin(πx5).

    Let uh be the tensor-product two-degree finite element approximation to u on uniform rectangular meshes and Πu the corresponding interpolant of the projection type. Set X=(0.5,0.5,0.5,0.5,0.5), Y=(0.25,0.25,0.25,0.25,0.25) and Z=(0.125,0.125,0.125,0.125,0.125). We solve Example 5.1 and obtain the following numerical results (see Table 1):

    Table 1.  Numerical results at X, Y and Z.
    h |ˉ(uhΠu)(X)| |ˉ(uhΠu)(Y)| |ˉ(uhΠu)(Z)|
    0.5 8.0218e-003 6.7152e-003 4.9384e-003
    0.25 1.9724e-003 5.3517e-004 5.1322e-004
    0.125 3.1481e-004 5.8873e-005 6.0237e-005

     | Show Table
    DownLoad: CSV

    Here, the operator ˉ=(ˉx1,ˉx2,ˉx3,ˉx4,ˉx5) and ˉxiv=12(|+xiv|+|xiv|),i=1,,5. The numerical results demonstrate our theoretical results.

    In this paper, we proposed two important analytic tools: The DDGF and the weak estimate of the second type. By combining these tools, we obtained a pointwise superconvergence estimate for the finite element approximation in the W1,-seminorm, which is a challenging issue in the field of superconvergence for the finite element method. The main difficulty of the paper lies in deriving the optimal order estimate for the DDGF in the W2,1-seminorm. Notably, the estimates for the DDGF vary for different dimensions of elliptic equations, necessitating different approaches for them. Although the methods presented in the paper are specifically developed for the five-dimensional second-order elliptic equation, they can also be applied to other high-dimensional second-order elliptic equations.

    The author declares he has not used Artificial Intelligence (AI) tools in the creation of this article.

    This work was supported by the Special Projects in Key Fields of Ordinary Colleges and Universities in Guangdong Province (2022ZDZX3016) and the Projects of Talents Recruitment of Guangdong University of Petrochemical Technology (2021rc003).

    The author declares no conflict of interest.



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