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A locally mass-conservative enriched Petrov-Galerkin method without penalty for the Darcy flow in porous media

Huangxin Chen School of Mathematical Sciences and Fujian Provincial Key Laboratory on Mathematical Modeling and High Performance Scientific Computing, Xiamen University, Fujian, 361005, China [email protected] Piaopiao Dong School of Mathematical Sciences and Fujian Provincial Key Laboratory on Mathematical Modeling and High Performance Scientific Computing, Xiamen University, Fujian, 361005, China [email protected] Shuyu Sun Computational Transport Phenomena Laboratory, Division of Physical Science and Engineering, King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia [email protected]  and  Zixuan Wang School of Mathematical Sciences and Fujian Provincial Key Laboratory on Mathematical Modeling and High Performance Scientific Computing, Xiamen University, Fujian, 361005, China [email protected]
Abstract.

In this work we present an enriched Petrov-Galerkin (EPG) method for the simulation of the Darcy flow in porous media. The new method enriches the approximation trial space of the conforming continuous Galerkin (CG) method with bubble functions and enriches the approximation test space of the CG method with piecewise constant functions, and it does not require any penalty term in the weak formulation. Moreover, we propose a framework for constructing the bubble functions and consider a decoupled algorithm for the EPG method based on this framework, which enables the process of solving pressure to be decoupled into two steps. The first step is to solve the pressure by the standard CG method, and the second step is a post-processing correction of the first step. Compared with the CG method, the proposed EPG method is locally mass-conservative, while keeping fewer degrees of freedom than the discontinuous Galerkin (DG) method. In addition, this method is more concise in the error analysis than the enriched Galerkin (EG) method. The coupled flow and transport in porous media is considered to illustrate the advantages of locally mass-conservative properties of the EPG method. We establish the optimal convergence of numerical solutions and present several numerical examples to illustrate the performance of the proposed method.

Key words and phrases:
enriched Petrov-Galerkin method, local mass conservation, post-processing, error analysis
2010 Mathematics Subject Classification:
65M60, 65N30, 76S05
Corresponding author: Shuyu Sun ([email protected])
The work of Huangxin Chen is supported by the NSF of China (Grant No. 12122115, 11771363). The work of Shuyu Sun is supported by King Abdullah University of Science and Technology (KAUST) through the grants BAS/1/1351-01 and URF/1/5028-01.

1. Introduction

The standard continuous Galerkin (CG) finite element method has been widely applied for the solution of second-order elliptic problems for its simplicity in implementation. However, the CG method possesses limitations in local mass conservation, which is significant in numerous applications, particularly when the coupling of flow and transport is considered [21, 48]. Indeed, violation of local mass conservation in velocity fields could cause spurious sources and sinks to the transport simulations, which might lead to numerical inaccuracy for the solution of transport equations.

Lots of numerical methods preserving local mass conservation have been proposed in the literature, which include the mixed finite element method [1, 2, 3, 4, 46], the finite volume method [12, 14, 23, 26, 34], the discontinuous Galerkin (DG) [5, 8, 15, 20, 25, 28, 36, 42] method, the recent weak Galerkin method [32], the mixed virtual element method [22] and the reduced basis method [10]. Besides, many other different finite element schemes based on the DG method have been derived, such as the local discontinuous Galerkin method [13, 18], the symmetric interior penalty Galerkin method [41, 45], the nonsymmetric interior penalty Galerkin method [37, 39], the incomplete interior penalty Galerkin method [21, 33, 41], the Oden-Babuška-Baumann-DG method [35, 44] and the hybridizable discontinuous Galerkin method [20]. They can tackle rough coefficient cases and capture the nonsmooth features of the solution very well since the function space itself is naturally discontinuous. However, the main disadvantage of the primal DG method is that it has a very large number of degrees of freedom, which can result in expensive computational cost.

In addition, quite a few works have also constructed alternative processing strategies to preserve the local mass conservation [16, 19, 24, 27, 43]. Among these methods, the enriched Galerkin (EG) method [29, 30, 31, 40] precisely enriches the CG finite element space with piecewise constant functions, which has fewer degrees of freedom than the DG method while maintaining local mass conservation. Due to the fact that the EG method is essentially a special DG method, its theoretical analysis is relatively similar to the DG method.

In this paper, our objective is to propose a new enriched Petrov-Galerkin (EPG) method for the simulation of the Darcy flow in porous media. The novelties of this work are as follows:

(I) We design a finite element method which enriches the approximation trial space for the CG method with bubble functions and enriches the approximation test space for the CG method with piecewise constant functions respectively. The main difference between the proposed enrich Petrov-Galerkin (EPG) method and the EG method is the selection of the trial functions. Since the bubble function is zero on the boundary of each element, the trial function is still continuous. Unlike the DG method or the EG method, we can still make use of the analysis framework for the conforming finite element method, which greatly simplifies the analysis compared with the DG and EG methods. Meanwhile, the EPG method and the EG method have the same degree of freedom because the degree of freedom for the bubble function on each element is only one. Moreover, the continuity of trial space results in the vanishment of the jump on the element boundaries. Therefore, there is no need to add penalty terms on the interior edges or faces like the DG method or the EG method.

(II) We present a framework to construct the bubble functions and propose a decoupled algorithm based on the EPG method. The first step in solving pressure is to use the classical CG method, which is easy to obtain. The second step is to modify the numerical solution from the CG method, which is regarded as a post-processing correction. It is clear that this algorithm achieves local mass conservation through the second step.

(III) We consider the coupled flow and transport in porous media to demonstrate the merit of the proposed EPG method. The local mass conservation for the velocity field in flow can ensure to preserve the positivity property of concentration in the transport. We present several interesting numerical examples to illustrate the advantages of the EPG method.

The paper is organized as follows. In Section 2, we introduce the governing equations of flow and transport in porous media and state the EPG approximation. In Section 3, we establish the well-posedness of the EPG method and present the optimal convergence analysis of the numerical solution for Darcy flow. Local mass conservation for the velocity based on the EPG method and the solution of the coupled flow and transport are considered in Section 4. We provide several numerical experiments to illustrate the advantages of the EPG method in Section 5. In Section 6, we summarize and discuss various features of the EPG method and conclude this paper with possible future work.

2. Mathematical model and the EPG method

2.1. Governing equations

In this work, we consider the coupled Darcy flow and species transport within a single flowing phase in porous media. The velocity computed from the Darcy flow will be used for simulations of the species transport in the porous media to solve for the concentration.

For the Darcy flow, it has the following form:

(2.1) (𝑲p)=u\displaystyle-\nabla\cdot(\boldsymbol{K}\nabla p)=\nabla\cdot\textit{{u}} =f,inΩ,\displaystyle=f,\qquad\ \ {\rm in}\ \Omega,
(2.2) p\displaystyle p =pD,onΓD,\displaystyle=p_{D},\qquad{\rm on}\ \Gamma_{D},
(2.3) 𝑲pn=un\displaystyle-\boldsymbol{K}\nabla p\cdot\textit{{n}}=\textit{{u}}\cdot\textit{{n}} =gN,onΓN,\displaystyle=g_{N},\qquad{\rm on}\ \Gamma_{N},

where Ω\Omega is a bounded polygonal/polyhedral domain in d\mathbb{R}^{d} (dd = 2 or 3) with boundary Ω\partial\Omega, and n denotes the unit outward normal vector on Ω\partial\Omega. The unknowns are the pressure pp and the velocity u. Assume that the conductivity 𝑲\boldsymbol{K} (the ratio of the permeability and the viscosity) is uniformly symmetric positive definite and bounded from above and below. For simplicity, we assume 𝑲=K𝑰\boldsymbol{K}=K\boldsymbol{I} in the following, where 𝑰\boldsymbol{I} is the identity matrix, and KK is a piecewisely positive and bounded constant. We impose a Dirichlet boundary condition on ΓD\Gamma_{D} and a Neumann boundary condition on ΓN\Gamma_{N} (ΓDΓN=Ω\Gamma_{D}\cup\Gamma_{N}=\partial\Omega, ΓDΓN=\Gamma_{D}\cap\Gamma_{N}=\emptyset).

The species transport equation in porous media is described as follows:

(2.4) ϕct+(uc)=f^,\displaystyle\frac{\partial\phi c}{\partial t}+\nabla\cdot(\textit{{u}}c)=\widehat{f}, (x,t)Ω×(0,Tf],\displaystyle(x,t)\in\Omega\times(0,T_{f}],
(2.5) c=cI,\displaystyle c=c_{I}, (x,t)Γin×(0,T],\displaystyle(x,t)\in\Gamma_{in}\times(0,T],
(2.6) c(x,0)=c0(x),\displaystyle c(x,0)=c_{0}(x), xΩ,\displaystyle x\in\Omega,

where ϕ\phi is porosity of porous media, f^\widehat{f} is the source or sink term, and TfT_{f} denotes the final simulation time. Let Ω=ΓinΓout\partial\Omega=\Gamma_{in}\cup\Gamma_{out} with Γin={xΩ:un<0}\Gamma_{in}=\{x\in\partial\Omega:\textit{{u}}\cdot\textit{{n}}<0\} as the inflow boundary and Γout={xΩ:un0}\Gamma_{out}=\{x\in\partial\Omega:\textit{{u}}\cdot\textit{{n}}\geq 0\} as the outflow/no-flow boundary. cIc_{I} denotes the inflow concentration and an initial concentration c0c_{0} is specified to close the system.

2.2. The EPG method

Let 𝒯h\mathcal{T}_{h} be a family of partitions of Ω\Omega composed of triangles if dd = 2 or tetrahedrons if dd = 3. Our method can be extended to quadrilaterals if dd = 2 or hexahedra if dd = 3, but the space of k(T)\mathbb{P}_{k}(T) below will need to be replaced by k(T)\mathbb{Q}_{k}(T). For convenience of presentation, the following necessary notations are given:

Mk(𝒯h):={pL2(Ω):p|Tk(T),T𝒯h},\displaystyle M^{k}(\mathcal{T}_{h}):=\{p\in L^{2}(\Omega):p|_{T}\in\mathbb{P}_{k}(T),\quad\forall T\in\mathcal{T}_{h}\},
M0k(𝒯h):=Mk(𝒯h)C0(Ω),\displaystyle M_{0}^{k}(\mathcal{T}_{h}):=M^{k}(\mathcal{T}_{h})\cap C^{0}(\Omega),
Mb(𝒯h):={pL2(Ω):p|T=αTh(x)λ1λ2λd+1,T𝒯h},\displaystyle M^{b}(\mathcal{T}_{h}):=\{p\in L^{2}(\Omega):p|_{T}=\alpha_{T}h(x)\lambda_{1}\lambda_{2}\cdots\lambda_{d+1},\quad\forall T\in\mathcal{T}_{h}\},

where Mk(𝒯h)M^{k}(\mathcal{T}_{h}) denotes the space of piecewise discontinuous polynomials of degree kk, while M0k(𝒯h)M_{0}^{k}(\mathcal{T}_{h}) consists of continuous polynomials. Mb(𝒯h)M^{b}(\mathcal{T}_{h}) is the space of piecewise bubble functions and αT\alpha_{T} means the degree of freedom.

We now define the average and jump for vHs(𝒯h)v\in H^{s}(\mathcal{T}_{h}). Let Ti,Tj𝒯hT_{i},T_{j}\in\mathcal{T}_{h} and eTiTje\in\partial T_{i}\cap\partial T_{j} with nen_{e} exterior to TiT_{i}. Denote

(2.7) {v}:=12(v|Ti+v|Tj),[v]:=v|Tiv|Tj.\displaystyle\{v\}:=\frac{1}{2}\left(v|_{T_{i}}+v|_{T_{j}}\right),\quad[v]:=v|_{T_{i}}-v|_{T_{j}}.

We comment that the average {v}\{v\} or the jump [v][v] actually means the function value vv itself if it is on the Dirichlet boundaries. Next we denote the upwind value of concentration c|ec^{*}|_{e} as follows:

c|e:={c|Ti,ifune0,c|Tj,ifune<0.\displaystyle c^{*}|_{e}:=\begin{cases}c|_{T_{i}},\quad{\rm if}\ \textit{{u}}\cdot\textit{{n}}_{e}\geq 0,\\ c|_{T_{j}},\quad{\rm if}\ \textit{{u}}\cdot\textit{{n}}_{e}<0.\end{cases}

We now propose the EPG method for the Darcy flow, which enriches the approximation trial space of the CG method with bubble functions and enriches the approximation test space of the CG method with piecewise constant functions. The trial and test finite element spaces Vh1V_{h}^{1} and Vh2V_{h}^{2} for the EPG method are denoted as

Vh1:=M0k(𝒯h)+Mb(𝒯h),\displaystyle V_{h}^{1}:=M_{0}^{k}(\mathcal{T}_{h})+M^{b}(\mathcal{T}_{h}),
Vh2:=M0k(𝒯h)+M0(𝒯h).\displaystyle V_{h}^{2}:=M_{0}^{k}(\mathcal{T}_{h})+M^{0}(\mathcal{T}_{h}).

For the Darcy flow, we introduce the bilinear form a(ph,qh)a(p_{h},q_{h}) and the linear functional l(qh)l(q_{h}) as follows:

(2.8) a(ph,qh)=T𝒯hTKphqhdxeΓhΓh,De{Kphne}[qh]𝑑σeΓhΓh,De{Kqhne}[ph]𝑑σ,\displaystyle a(p_{h},q_{h})=\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}K\nabla p_{h}\cdot\nabla q_{h}dx-\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}\int_{e}\{K\nabla p_{h}\cdot\textit{{n}}_{e}\}[q_{h}]d\sigma-\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}\int_{e}\{K\nabla q_{h}\cdot\textit{{n}}_{e}\}[p_{h}]d\sigma,
(2.9) l(qh)=T𝒯hTfqh𝑑xeΓh,NegNqh𝑑σeΓh,DeKqhnepDdσ,\displaystyle l(q_{h})=\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}fq_{h}dx-\sum\limits_{e\in\Gamma_{h,N}}\int_{e}g_{N}q_{h}d\sigma-\sum\limits_{e\in\Gamma_{h,D}}\int_{e}K\nabla q_{h}\cdot\textit{{n}}_{e}p_{D}d\sigma,

where the set of all faces (d=3d=3) or edges (d=2d=2) on interior boundaries, Dirichlet boundaries, Neumann boundaries for 𝒯h\mathcal{T}_{h} is denoted by Γh,Γh,D\Gamma_{h},\Gamma_{h,D} and Γh,N\Gamma_{h,N}, respectively. On each face, a unit normal vector ne\textit{{n}}_{e} is uniquely chosen. It is obvious that the EPG method uses a weak formulation similar to the EG method, but it does not require any penalty term due to the continuity of the trial space.

The EPG method for the Darcy flow is to seek phVh1p_{h}\in V_{h}^{1} satisfying

(2.10) a(ph,qh)=l(qh),qhVh2.\displaystyle a(p_{h},q_{h})=l(q_{h}),\quad\forall q_{h}\in V_{h}^{2}.

Now we present a decoupled algorithm for the EPG method, which contains two steps. In the first step, we consider the continuous situation. In the second step, we solve the bubble function, which is regarded as a post-processing correction of the first step.

We decompose php_{h} and qhq_{h} in (2.10) as follows:

ph=phc+phb,phcM0k(𝒯h),phbMb(𝒯h),\displaystyle p_{h}=p_{h}^{c}+p_{h}^{b},\quad p_{h}^{c}\in M_{0}^{k}(\mathcal{T}_{h}),p_{h}^{b}\in M^{b}(\mathcal{T}_{h}),
qh=qhc+qh0,qhcM0k(𝒯h),qh0M0(𝒯h).\displaystyle q_{h}=q_{h}^{c}+q_{h}^{0},\quad q_{h}^{c}\in M_{0}^{k}(\mathcal{T}_{h}),q_{h}^{0}\in M^{0}(\mathcal{T}_{h}).

The EPG method can also be rewritten as follows:

(2.11) a(phc,qhc)+a(phb,qhc)+a(phc,qh0)+a(phb,qh0)=l(qhc)+l(qh0).\displaystyle a(p_{h}^{c},q_{h}^{c})+a(p_{h}^{b},q_{h}^{c})+a(p_{h}^{c},q_{h}^{0})+a(p_{h}^{b},q_{h}^{0})=l(q_{h}^{c})+l(q_{h}^{0}).

If we choose qhc|Γh,D=0q_{h}^{c}|_{\Gamma_{h,D}}=0, then we have

a(phb,qhc)\displaystyle a(p_{h}^{b},q_{h}^{c}) =T𝒯hTKphbqhcdx\displaystyle=\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}K\nabla p_{h}^{b}\cdot\nabla q_{h}^{c}dx
=T𝒯hTphb(Kqhc)n𝑑σT𝒯hTphb(Kqhc)𝑑x\displaystyle=\sum\limits_{T\in\mathcal{T}_{h}}\int_{\partial T}p_{h}^{b}(K\nabla q_{h}^{c})\cdot\textit{{n}}d\sigma-\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}p_{h}^{b}\nabla\cdot(K\nabla q_{h}^{c})dx
=T𝒯hTphb(Kqhc)𝑑x.\displaystyle=-\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}p_{h}^{b}\nabla\cdot(K\nabla q_{h}^{c})dx.

The bubble function phbp_{h}^{b} could be carefully chosen such that a(phb,qhc)=0a(p_{h}^{b},q_{h}^{c})=0. More details on the construction of bubble functions will be provided in the subsequent sections. Now the decoupled algorithm of the EPG method (2.10) is briefly summarized as follows:

Algorithm 2.1.

(A decoupled algorithm of the EPG method)

Step 1. Let qh0=0q_{h}^{0}=0 and qhcM0k(𝒯h)q_{h}^{c}\in M_{0}^{k}(\mathcal{T}_{h}). Then (2.11) can be simplified as follows: find phcM0k(𝒯h)p_{h}^{c}\in M_{0}^{k}(\mathcal{T}_{h}) such that

a(phc,qhc)=l(qhc),qhcM0k(𝒯h).\displaystyle a(p_{h}^{c},q_{h}^{c})=l(q_{h}^{c}),\qquad\forall q_{h}^{c}\in M_{0}^{k}(\mathcal{T}_{h}).

Step 2. Let qhc=0q_{h}^{c}=0 and qh0M0(𝒯h)q_{h}^{0}\in M^{0}(\mathcal{T}_{h}). Now we can recover phbp_{h}^{b} as follows: find phbMb(𝒯h)p_{h}^{b}\in M^{b}(\mathcal{T}_{h}) such that

(2.12) a(phb,qh0)=l(qh0)a(phc,qh0),qh0M0(𝒯h).\displaystyle a(p_{h}^{b},q_{h}^{0})=l(q_{h}^{0})-a(p_{h}^{c},q_{h}^{0}),\qquad\forall q_{h}^{0}\in M^{0}(\mathcal{T}_{h}).

Step 3. Get ph=phc+phbp_{h}=p_{h}^{c}+p_{h}^{b}.

We note that the decoupled algorithm of the EPG method divides the solution php_{h} into two parts. The first part of the solution is the standard solution of the CG method and the well-posedness of phcp_{h}^{c} is well-known. Therefore, in order to verify the well-posedness of php_{h}, we need to focus on the well-posedness of phbp_{h}^{b}, which is in the second step of the algorithm. The Babuška theory (cf. [7, 11, 47]) reveals that the problem (2.10) or (2.12) is well-posed if and only if the continuity and coercivity (inf-sup) condition of the bilinear forms are satisfied.

Since the well-posedness of phcp^{c}_{h} is well-known, we will provide the well-posedness of phbp_{h}^{b} in the next section. Now we define the energy norm as follows:

(2.13) φhVh:=(T𝒯hTKφhφhdx+eΓhΓh,D1hee[φh]2dσ)1/2,φhVh.\displaystyle\interleave\varphi_{h}\interleave_{V_{h}}:=\left(\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}K\nabla\varphi_{h}\cdot\nabla\varphi_{h}dx+\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}\frac{1}{h_{e}}\int_{e}[\varphi_{h}]^{2}d\sigma\right)^{1/2},\forall\varphi_{h}\in V_{h}.

The energy norm defined by (2.13) can be applied to both Vh1V_{h}^{1} and Vh2V_{h}^{2} spaces. Since phVh1p_{h}\in V_{h}^{1} is globally continuous, the jump term vanishes on Γh\Gamma_{h}. Therefore, for any phVh1p_{h}\in V_{h}^{1} and qhVh2q_{h}\in V_{h}^{2}, we can describe the energy norms as follows:

(2.14) phVh1=(T𝒯hTKphphdx+eΓh,D1hee[ph]2dσ)1/2,\displaystyle\interleave p_{h}\interleave_{V_{h}^{1}}=\left(\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}K\nabla p_{h}\cdot\nabla p_{h}dx+\sum\limits_{e\in\Gamma_{h,D}}\frac{1}{h_{e}}\int_{e}[p_{h}]^{2}d\sigma\right)^{1/2},
(2.15) qhVh2=(T𝒯hTKqhqhdx+eΓhΓh,D1hee[qh]2dσ)1/2.\displaystyle\interleave q_{h}\interleave_{V_{h}^{2}}=\left(\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}K\nabla q_{h}\cdot\nabla q_{h}dx+\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}\frac{1}{h_{e}}\int_{e}[q_{h}]^{2}d\sigma\right)^{1/2}.

3. Analysis of the EPG method

In this section, we present theoretical analysis of the EPG method, including continuity, coercivity of the bilinear form and the convergence analysis. It should be noted that the positive constant CC that appears during the subsequent proofs could have different values but it is depending only the data KK and the shape regularity of the meshes.

3.1. Continuity of the bilinear forms

Theorem 3.1.

The bilinear form (2.8) is continuous, i.e.,

(3.1) |a(ph,qh)|CphVh1qhVh2,phVh1,qhVh2,\displaystyle|a(p_{h},q_{h})|\leq C\interleave p_{h}\interleave_{V_{h}^{1}}\interleave q_{h}\interleave_{V_{h}^{2}},\quad\forall p_{h}\in V_{h}^{1},q_{h}\in V_{h}^{2},

where C>0C>0 is a constant independent of the mesh size hh.

Proof.

For the right-hand side of (2.8), there are three terms which will be analyzed respectively. The first term can be bounded by the Hölder inequality or the Cauchy-Schwarz inequality as follows:

|TKphqhdx|\displaystyle\left|\int_{T}K\nabla p_{h}\cdot\nabla q_{h}dx\right| K1/2ph0,TK1/2qh0,T,\displaystyle\leq\|K^{1/2}\nabla p_{h}\|_{0,T}\|K^{1/2}\nabla q_{h}\|_{0,T},

which directly yields

(3.2) |T𝒯hTKphqhdx|\displaystyle\left|\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}K\nabla p_{h}\cdot\nabla q_{h}dx\right| K1/2ph0,𝒯hK1/2qh0,𝒯h\displaystyle\leq\|K^{1/2}\nabla p_{h}\|_{0,\mathcal{T}_{h}}\|K^{1/2}\nabla q_{h}\|_{0,\mathcal{T}_{h}}
phVh1qhVh2.\displaystyle\leq\interleave p_{h}\interleave_{V_{h}^{1}}\interleave q_{h}\interleave_{V_{h}^{2}}.

For the second term, by the Hölder inequality and the trace inequality, we have

|e{Kphne}[qh]𝑑σ|\displaystyle\left|\int_{e}\{K\nabla p_{h}\cdot\textit{{n}}_{e}\}[q_{h}]d\sigma\right| {Kphne}0,e[qh]0,e\displaystyle\leq\|\{K\nabla p_{h}\cdot\textit{{n}}_{e}\}\|_{0,e}\|[q_{h}]\|_{0,e}
Che1/2ph0,we[qh]0,e\displaystyle\leq Ch_{e}^{-1/2}\|\nabla p_{h}\|_{0,w_{e}}\|[q_{h}]\|_{0,e}
CK1/2ph0,we(1he)1/2[qh]0,e,\displaystyle\leq C\|K^{1/2}\nabla p_{h}\|_{0,w_{e}}\|(\frac{1}{h_{e}})^{1/2}[q_{h}]\|_{0,e},

where wew_{e} represents all elements adjacent to ee. Therefore, we obtain

(3.3) |eΓhΓh,De{Kphne}[qh]𝑑σ|\displaystyle\left|\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}\int_{e}\{K\nabla p_{h}\cdot\textit{{n}}_{e}\}[q_{h}]d\sigma\right| CK1/2ph0,𝒯h(1he)1/2[qh]0,ΓhΓh,D\displaystyle\leq C\|K^{1/2}\nabla p_{h}\|_{0,\mathcal{T}_{h}}\|(\frac{1}{h_{e}})^{1/2}[q_{h}]\|_{0,\Gamma_{h}\cup\Gamma_{h,D}}
CphVh1qhVh2.\displaystyle\leq C\interleave p_{h}\interleave_{V_{h}^{1}}\interleave q_{h}\interleave_{V_{h}^{2}}.

We comment that [qh][q_{h}] actually means the function value qhq_{h} instead of the jump if it is on Γh,D\Gamma_{h,D}. The third term can be directly bounded since we use the same norm for both Vh1V_{h}^{1} and Vh2V_{h}^{2} spaces. For any phVh1p_{h}\in V_{h}^{1}, the jump term vanishes on Γh\Gamma_{h}. Now we can conclude the result by (3.2), (3.3) and the triangle inequality. ∎

In fact, based on the arbitrariness of php_{h} and qhq_{h} in (3.1), we can take php_{h} as phbp_{h}^{b} and qhq_{h} as qh0q_{h}^{0}, which directly shows the continuity condition of the bilinear form in the second step of the decoupled algorithm as follows:

(3.4) |a(phb,qh0)|CphbVh1qh0Vh2,phbMb(𝒯h),qh0M0(𝒯h).\displaystyle|a(p^{b}_{h},q^{0}_{h})|\leq C\interleave p^{b}_{h}\interleave_{V_{h}^{1}}\interleave q^{0}_{h}\interleave_{V_{h}^{2}},\quad\forall p^{b}_{h}\in M^{b}(\mathcal{T}_{h}),q^{0}_{h}\in M^{0}(\mathcal{T}_{h}).

In order to show the well-posedness of (2.12), next we only need to prove the inf-sup condition of a(phb,qh0)a(p_{h}^{b},q_{h}^{0}).

3.2. Coercivity of the bilinear forms

Denote phb=T𝒯hαTbTp_{h}^{b}=\sum\limits_{T\in\mathcal{T}_{h}}\alpha_{T}b_{T} where phbp_{h}^{b} is a global bubble function while bTb_{T} is its local bubble basis function and αT\alpha_{T} is a constant on TT. Let α\alpha be a piecewise constant function with α|T=αT\alpha|_{T}=\alpha_{T} for any T𝒯hT\in\mathcal{T}_{h}. The definition of [α][\alpha] on the face (d=3d=3) or the edge (d=2d=2) ee is based on the previous definition in (2.7). For any phbMb(𝒯h)p^{b}_{h}\in M^{b}(\mathcal{T}_{h}) and qh0M0(𝒯h)q^{0}_{h}\in M^{0}(\mathcal{T}_{h}), we denote phbMb(𝒯h):=phbVh1\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})}:=\interleave p_{h}^{b}\interleave_{V^{1}_{h}} and qh0M0(𝒯h):=qh0Vh2\interleave q_{h}^{0}\interleave_{M^{0}(\mathcal{T}_{h})}:=\interleave q_{h}^{0}\interleave_{V^{2}_{h}}. Obviously, we have phbMb(𝒯h)=K1/2phb0,𝒯h\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})}=\|K^{1/2}\nabla p_{h}^{b}\|_{0,\mathcal{T}_{h}}. Besides, we define another energy norm \interleave\cdot\interleave_{*} for phbp_{h}^{b} by

(3.5) phb:=(eΓhΓh,Dhe1[α]0,e2)1/2.\displaystyle\interleave p_{h}^{b}\interleave_{*}:=\left(\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}h_{e}^{-1}\|[\alpha]\|_{0,e}^{2}\right)^{1/2}.
Lemma 3.2.

The energy norms (2.14) and (3.5) for phbp_{h}^{b} are equivalent, i.e., for phbMb(𝒯h)\forall p_{h}^{b}\in M^{b}(\mathcal{T}_{h}), there hold

phbMb(𝒯h)Cphb,\displaystyle\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})}\leq C\interleave p_{h}^{b}\interleave_{*},
phbCphbMb(𝒯h),\displaystyle\interleave p_{h}^{b}\interleave_{*}\leq C\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})},

where C>0C>0 is a constant independent of the mesh size hh.

Proof.

It is obvious that Mb(𝒯h)\interleave\cdot\interleave_{M^{b}(\mathcal{T}_{h})} and \interleave\cdot\interleave_{*} are both energy norms exactly when the set Γh,D\Gamma_{h,D} is non-empty. Firstly, by the scaling argument and the fact that the norms for the finite dimensional space are equivalent, we have

phbMb(𝒯h)2\displaystyle\interleave p_{h}^{b}\interleave^{2}_{M^{b}(\mathcal{T}_{h})} =K1/2phb0,𝒯hCT^𝒯^hhTd2K^1/2p^hb0,T^2Ce^Γ^hΓ^h,Dhed2[α^]0,e^2\displaystyle=\|K^{1/2}\nabla p_{h}^{b}\|_{0,\mathcal{T}_{h}}\leq C\sum\limits_{\hat{T}\in\mathcal{\hat{T}}_{h}}h_{T}^{d-2}\|\hat{K}^{1/2}\nabla\hat{p}_{h}^{b}\|_{0,\hat{T}}^{2}\leq C\sum\limits_{\hat{e}\in\hat{\Gamma}_{h}\cup\hat{\Gamma}_{h,D}}h_{e}^{d-2}\|[\hat{\alpha}]\|_{0,\hat{e}}^{2}
CeΓhΓh,Dhe1[α]0,e2=Cphb2,\displaystyle\leq C\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}h_{e}^{-1}\|[\alpha]\|^{2}_{0,e}=C\interleave p_{h}^{b}\interleave^{2}_{*},

where the reference constant or function such as K^\hat{K}, [α^][\hat{\alpha}] or p^hb\hat{p}_{h}^{b} is defined on the reference element T^𝒯^h\hat{T}\in\mathcal{\hat{T}}_{h} or the reference face (dd = 3) / edge (dd = 2) e^Γ^hΓ^h,D\hat{e}\in\hat{\Gamma}_{h}\cup\hat{\Gamma}_{h,D}. Similarly, we can also have

phb2\displaystyle\interleave p_{h}^{b}\interleave^{2}_{*} =eΓhΓh,Dhe1[α]0,e2Ce^Γ^hΓ^h,Dhed2[α^]0,e^2\displaystyle=\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}h_{e}^{-1}\|[\alpha]\|_{0,e}^{2}\leq C\sum\limits_{\hat{e}\in\hat{\Gamma}_{h}\cup\hat{\Gamma}_{h,D}}h_{e}^{d-2}\|[\hat{\alpha}]\|_{0,\hat{e}}^{2}
CT^𝒯^hhTd2K^1/2p^hb0,T^2CT𝒯hK1/2phb0,T2=CphbMb(𝒯h)2.\displaystyle\leq C\sum\limits_{\hat{T}\in\mathcal{\hat{T}}_{h}}h_{T}^{d-2}\|\hat{K}^{1/2}\nabla\hat{p}_{h}^{b}\|_{0,\hat{T}}^{2}\leq C\sum\limits_{T\in\mathcal{T}_{h}}\|K^{1/2}\nabla p_{h}^{b}\|_{0,T}^{2}=C\interleave p_{h}^{b}\interleave^{2}_{M^{b}(\mathcal{T}_{h})}.

Now we complete the proof. ∎

Next we start to construct the bubble function such that the orthogonality a(phb,qhc)=0a(p_{h}^{b},q_{h}^{c})=0 is satisfied for any phbMb(𝒯h)p_{h}^{b}\in M^{b}(\mathcal{T}_{h}) and qh0M0(𝒯h)q_{h}^{0}\in M^{0}(\mathcal{T}_{h}). For any phb=T𝒯hαTbTp_{h}^{b}=\sum\limits_{T\in\mathcal{T}_{h}}\alpha_{T}b_{T}, we define bTb_{T} in any T𝒯hT\in\mathcal{T}_{h} as follows:

(3.6) bT={i=1d+1bT,i,k=1,i=1d+1bT,i+j=1Jγjλ12λd+12ψj,k2,\displaystyle b_{T}=\begin{cases}\sum\limits_{i=1}^{d+1}b_{T,i},&\quad k=1,\\ \sum\limits_{i=1}^{d+1}b_{T,i}+\sum\limits_{j=1}^{J}\gamma_{j}\lambda_{1}^{2}\cdots\lambda_{d+1}^{2}\psi_{j},&\quad k\geq 2,\end{cases}

where J=Ck+d2dJ=C_{k+d-2}^{d} and bT,ib_{T,i} is a dd-dimensional one-sided bubble function with the undetermined coefficient βi\beta_{i}, i.e., bT,i=βiλ12λd+12λib_{T,i}=\beta_{i}\frac{\lambda_{1}^{2}\cdots\lambda_{d+1}^{2}}{\lambda_{i}}. Here, γj\gamma_{j} is also an undetermined coefficient and ψj\psi_{j} is a basis function in the barycentric coordinate form of Mk2(T)M^{k-2}(T).

We should illustrate that βi\beta_{i} and γj\gamma_{j} are well-defined. Firstly, we set the undetermined coefficient βi\beta_{i} satisfying

(3.7) eiβiKλiniλ12λd+12λi2dσ=1.\displaystyle\int_{e_{i}}\beta_{i}K\nabla\lambda_{i}\cdot\textit{{n}}_{i}\frac{\lambda_{1}^{2}\cdots\lambda_{d+1}^{2}}{\lambda_{i}^{2}}d\sigma=1.

Thus, βi\beta_{i} is well-defined by βi=1eiKλiniλ12λd+12λi2dσ,\beta_{i}=\frac{1}{\int_{e_{i}}K\nabla\lambda_{i}\cdot\textit{{n}}_{i}\frac{\lambda_{1}^{2}\cdots\lambda_{d+1}^{2}}{\lambda_{i}^{2}}d\sigma}, where the denominator can be easily observed as nonzero. Secondly, it is easy to get that a(phb,qhc)=0a(p_{h}^{b},q_{h}^{c})=0 when k=1k=1. For k2k\geq 2, we will show that the construction of bTb_{T} in (3.6) satisfies the orthogonality property a(phb,qhc)=0a(p_{h}^{b},q_{h}^{c})=0 if the parameter {γj}j=1J\{\gamma_{j}\}^{J}_{j=1} are well chosen. If a(phb,qhc)=0a(p_{h}^{b},q_{h}^{c})=0 is satisfied, for any T𝒯hT\in\mathcal{T}_{h}, the above bTb_{T} satisfies that

(Ki=1d+1bT,i,ψi)T+(j=1JγjKλ12λd+12ψj,ψi)T=0,ψiMk2(T),i=1,,J,\displaystyle(K\sum\limits_{i=1}^{d+1}b_{T,i},\psi_{i})_{T}+(\sum\limits_{j=1}^{J}\gamma_{j}K\lambda_{1}^{2}\cdots\lambda_{d+1}^{2}\psi_{j},\psi_{i})_{T}=0,\quad\forall\ \psi_{i}\in M^{k-2}(T),\ i=1,\cdots,J,

where (,)T(\cdot,\cdot)_{T} means the inner product on TT. Then, we get the linear system for {γj}j=1J\{\gamma_{j}\}^{J}_{j=1} as follows:

(m11m12m1Jm21m22m2JmJ1mJ2mJJ)(γ1γ2γJ)=((Ki=1d+1bT,i,ψ1)T(Ki=1d+1bT,i,ψ2)T(Ki=1d+1bT,i,ψJ)T),\displaystyle\begin{pmatrix}m_{11}&m_{12}&\cdots&m_{1J}\\ m_{21}&m_{22}&\cdots&m_{2J}\\ \vdots&\vdots&\ddots&\vdots\\ m_{J1}&m_{J2}&\cdots&m_{JJ}\end{pmatrix}\begin{pmatrix}\gamma_{1}\\ \gamma_{2}\\ \vdots\\ \gamma_{J}\end{pmatrix}=\begin{pmatrix}-(K\sum\limits_{i=1}^{d+1}b_{T,i},\psi_{1})_{T}\\ -(K\sum\limits_{i=1}^{d+1}b_{T,i},\psi_{2})_{T}\\ \vdots\\ -(K\sum\limits_{i=1}^{d+1}b_{T,i},\psi_{J})_{T}\end{pmatrix},

where mij=(Kλ12λd+12ψj,ψi)Tm_{ij}=(K\lambda_{1}^{2}\cdots\lambda_{d+1}^{2}\psi_{j},\psi_{i})_{T}. Next, we will show that {γj}j=1J\{\gamma_{j}\}^{J}_{j=1} is well defined by the above linear system. Define a new space Wh(T)W_{h}(T) as follows:

Wh(T):={ψL2(T):ψspan{ψ¯1,,ψ¯J}},T𝒯h,\displaystyle W_{h}(T):=\{\psi\in L^{2}(T):\psi\in{\rm span}\{\overline{\psi}_{1},\cdots,\overline{\psi}_{J}\}\},\quad\forall T\in\mathcal{T}_{h},

where ψ¯i:=K1/2λ1λd+1ψi\overline{\psi}_{i}:=K^{1/2}\lambda_{1}\cdots\lambda_{d+1}\psi_{i} is the basis function for Wh(T)W_{h}(T). The coefficient matrix can be simplified as follows:

mij=(Kλ12λd+12ψj,ψi)T=(ψ¯j,ψ¯i)T,\displaystyle m_{ij}=(K\lambda_{1}^{2}\cdots\lambda_{d+1}^{2}\psi_{j},\psi_{i})_{T}=(\overline{\psi}_{j},\overline{\psi}_{i})_{T},

which yields a nonsingular coefficient matrix because {ψ¯i}i=1J\{\overline{\psi}_{i}\}_{i=1}^{J} are linearly independent. Besides, the right-hand term of the above linear system is nonzero, which shows that {γj}j=1J\{\gamma_{j}\}^{J}_{j=1} can be well determined. Thus, we can suitably choose the bubble function such that the orthogonality property a(phb,qhc)=0a(p_{h}^{b},q_{h}^{c})=0 holds true.

Next we show the coercivity estimate for the bilinear form a(phb,qh0)a(p_{h}^{b},q_{h}^{0}).

Theorem 3.3.

The following coercivity results hold true:

(3.8) supphb0a(phb,qh0)phbMb(𝒯h)Cqh0M0(𝒯h),qh0M0(𝒯h),\displaystyle\mathop{sup}\limits_{p_{h}^{b}\neq 0}\frac{a(p_{h}^{b},q_{h}^{0})}{\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})}}\geq C\interleave q_{h}^{0}\interleave_{M^{0}(\mathcal{T}_{h})},\quad\forall q_{h}^{0}\in M^{0}(\mathcal{T}_{h}),
(3.9) supqh00a(phb,qh0)qh0M0(𝒯h)CphbMb(𝒯h),phbMb(𝒯h),\displaystyle\mathop{sup}\limits_{q_{h}^{0}\neq 0}\frac{a(p_{h}^{b},q_{h}^{0})}{\interleave q_{h}^{0}\interleave_{M^{0}(\mathcal{T}_{h})}}\geq C\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})},\quad\forall p_{h}^{b}\in M^{b}(\mathcal{T}_{h}),

where C>0C>0 is a constant independent of the mesh size hh.

Proof.

By the definition of (3.6), we have

(3.10) TKbTndσ=e1β1Kλ1n1λ22λd+12dσ++ed+1βd+1Kλd+1nd+1λ12λd2dσ.\displaystyle\int_{\partial T}K\nabla b_{T}\cdot\textit{{n}}d\sigma=\int_{e_{1}}\beta_{1}K\nabla\lambda_{1}\cdot\textit{{n}}_{1}\lambda_{2}^{2}\cdots\lambda_{d+1}^{2}d\sigma+\cdots+\int_{e_{d+1}}\beta_{d+1}K\nabla\lambda_{d+1}\cdot\textit{{n}}_{d+1}\lambda_{1}^{2}\cdots\lambda_{d}^{2}d\sigma.

Obviously, each of the above d+1d+1 terms on the right-hand side of (3.10) equals to 1 according to (3.7).

Firstly, for any qh0M0(𝒯h)q_{h}^{0}\in M^{0}(\mathcal{T}_{h}), we choose αT=qh0|T\alpha_{T}=-q_{h}^{0}|_{T}. We consider the integral on the face (d=3d=3) or the edge (d=2d=2) ee of an element TT as follows:

eKphbnedσ=αTeKbTnedσ=αT,\displaystyle\int_{e}K\nabla p_{h}^{b}\cdot\textit{{n}}_{e}d\sigma=\alpha_{T}\int_{e}K\nabla b_{T}\cdot\textit{{n}}_{e}d\sigma=\alpha_{T},

which yields

e{Kphbne}𝑑σ={12[qh0],eΓh,qh0,eΓh,D,\displaystyle\int_{e}\{K\nabla p_{h}^{b}\cdot\textit{{n}}_{e}\}d\sigma=\begin{cases}-\frac{1}{2}[q_{h}^{0}],&\quad e\in\Gamma_{h},\\ -q_{h}^{0},&\quad e\in\Gamma_{h,D},\end{cases}

where ne\textit{{n}}_{e} is uniquely chosen. Therefore, we have

(3.11) a(phb,qh0)=eΓhΓh,De{Kphbne}[qh0]𝑑σ12eΓhΓh,Dehe1[qh0]2𝑑σ=12qh0M0(𝒯h)2.\displaystyle a(p_{h}^{b},q_{h}^{0})=-\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}\int_{e}\{K\nabla p_{h}^{b}\cdot\textit{{n}}_{e}\}[q_{h}^{0}]d\sigma\geq\frac{1}{2}\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}\int_{e}h_{e}^{-1}[q_{h}^{0}]^{2}d\sigma=\frac{1}{2}\interleave q_{h}^{0}\interleave_{M^{0}(\mathcal{T}_{h})}^{2}.

By Lemma 3.2, we have

(3.12) phbMb(𝒯h)\displaystyle\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})} Cphb=C(eΓhΓh,Dhe1[qh0]0,e2)1/2=Cqh0M0(𝒯h).\displaystyle\leq C\interleave p_{h}^{b}\interleave_{*}=C\left(\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}h_{e}^{-1}\|[q_{h}^{0}]\|_{0,e}^{2}\right)^{1/2}=C\interleave q_{h}^{0}\interleave_{M^{0}(\mathcal{T}_{h})}.

Following (3.11) and (3.12), we directly obtain

a(phb,qh0)phbMb(𝒯h)Ca(phb,qh0)qh0M0(𝒯h)C2qh0M0(𝒯h),\displaystyle\frac{a(p_{h}^{b},q_{h}^{0})}{\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})}}\geq C\frac{a(p_{h}^{b},q_{h}^{0})}{\interleave q_{h}^{0}\interleave_{M^{0}(\mathcal{T}_{h})}}\geq\frac{C}{2}\interleave q_{h}^{0}\interleave_{M^{0}(\mathcal{T}_{h})},

which yields the estimate (3.8).

Secondly, for any phbMb(𝒯h)p_{h}^{b}\in M^{b}(\mathcal{T}_{h}), we choose qh0|T=αTq_{h}^{0}|_{T}=-\alpha_{T}. Similarly, we obtain

(3.13) a(phb,qh0)\displaystyle a(p_{h}^{b},q_{h}^{0}) 12eΓhΓh,Dehe1[qh0]2dσ=12phb2CphbMb(𝒯h)2.\displaystyle\geq\frac{1}{2}\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}\int_{e}h_{e}^{-1}[q_{h}^{0}]^{2}d\sigma=\frac{1}{2}\interleave p_{h}^{b}\interleave_{*}^{2}\geq C\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})}^{2}.

By Lemma 3.2, we also have

(3.14) qh0M0(𝒯h)\displaystyle\interleave q_{h}^{0}\interleave_{M^{0}(\mathcal{T}_{h})} =(eΓhΓh,Dhe1[qh0]0,e2)1/2=phbCphbMb(𝒯h).\displaystyle=\left(\sum\limits_{e\in\Gamma_{h}\cup\Gamma_{h,D}}h_{e}^{-1}\|[q_{h}^{0}]\|_{0,e}^{2}\right)^{1/2}=\interleave p_{h}^{b}\interleave_{*}\leq C\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})}.

By (3.13) and (3.14), we obtain

a(phb,qh0)qh0M0(𝒯h)Ca(phb,qh0)phbMb(𝒯h)CphbMb(𝒯h),\displaystyle\frac{a(p_{h}^{b},q_{h}^{0})}{\interleave q_{h}^{0}\interleave_{M^{0}(\mathcal{T}_{h})}}\geq C\frac{a(p_{h}^{b},q_{h}^{0})}{\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})}}\geq C\interleave p_{h}^{b}\interleave_{M^{b}(\mathcal{T}_{h})},

which yields the estimate (3.9). Now we complete the proof. ∎

The continuity and the two inf-sup conditions for the bilinear form a(phb,qh0)a(p_{h}^{b},q_{h}^{0}) have been proved through Theorem 3.1 and Theorem 3.3. Thus, we can directly see that the solution phbp_{h}^{b} of (2.12) is well-posed in the second step of the decoupled algorithm by the Babuška theory (cf. [7, 11, 47]). Since the well-posedness of the solution phcp_{h}^{c} in the first step to solve is well-known, we can easily conclude that the solution php_{h} of (2.10) for the EPG method is well-posed. By the Babuška theory (cf. [7, 11, 47]) again, the following two inf-sup conditions for the bilinear form a(ph,qh)a(p_{h},q_{h}) are satisfied:

supph0a(ph,qh)phVh1CqhVh2,qhVh2,\displaystyle\mathop{sup}\limits_{p_{h}\neq 0}\frac{a(p_{h},q_{h})}{\interleave p_{h}\interleave_{V_{h}^{1}}}\geq C\interleave q_{h}\interleave_{V_{h}^{2}},\quad\forall q_{h}\in V_{h}^{2},
(3.15) supqh0a(ph,qh)qhVh2CphVh1,phVh1.\displaystyle\mathop{sup}\limits_{q_{h}\neq 0}\frac{a(p_{h},q_{h})}{\interleave q_{h}\interleave_{V_{h}^{2}}}\geq C\interleave p_{h}\interleave_{V_{h}^{1}},\quad\forall p_{h}\in V_{h}^{1}.

3.3. Convergence analysis

We now introduce several necessary interpolations, which will be used in the analysis of convergence. Firstly, let Ihc:L1(Ω)M0k(𝒯h)I_{h}^{c}:L^{1}(\Omega)\rightarrow M_{0}^{k}(\mathcal{T}_{h}) be the Clément interpolation operator [17]. The interpolation error estimates of IhcI_{h}^{c} have been well-known in the literature (cf. [17]) as follows: for any vHs(Ω)v\in H^{s}(\Omega), s>1s>1, there hold

(3.16) vIhcv0,𝒯hChs|v|s,Ω,\displaystyle\|v-I_{h}^{c}v\|_{0,\mathcal{T}_{h}}\leq Ch^{s}|v|_{s,\Omega},
(3.17) |vIhcv|1,𝒯hChs1|v|s,Ω.\displaystyle|v-I_{h}^{c}v|_{1,\mathcal{T}_{h}}\leq Ch^{s-1}|v|_{s,\Omega}.

Secondly, let Ihb:L2(Ω)Mb(𝒯h)I_{h}^{b}:L^{2}(\Omega)\rightarrow M^{b}(\mathcal{T}_{h}) be the linear projection that satisfies the constraint as follows:

T(Ihbφφ)𝑑x=0,T𝒯h,φL2(Ω).\displaystyle\int_{T}(I_{h}^{b}\varphi-\varphi)dx=0,\quad T\in\mathcal{T}_{h},\ \forall\varphi\in L^{2}(\Omega).

The estimates for IhbI_{h}^{b} can be guaranteed (cf. [6]) as follows:

(3.18) Ihbφ0,𝒯hCφ0,Ω,φL2(Ω),\displaystyle\|I_{h}^{b}\varphi\|_{0,\mathcal{T}_{h}}\leq C\|\varphi\|_{0,\Omega},\quad\forall\varphi\in L^{2}(\Omega),
(3.19) |Ihb(φIhcφ)|1,𝒯hChs1|φ|s,Ω,φHs(Ω),s>1.\displaystyle|I_{h}^{b}(\varphi-I_{h}^{c}\varphi)|_{1,\mathcal{T}_{h}}\leq Ch^{s-1}|\varphi|_{s,\Omega},\quad\forall\varphi\in H^{s}(\Omega),s>1.

Finally, we define a new interpolation operator Ih:L2(Ω)Vh1I_{h}:L^{2}(\Omega)\rightarrow V_{h}^{1} as follows: for any vL2(Ω)v\in L^{2}(\Omega),

(3.20) Ihv:=Ihcv+Ihb(vIhcv),\displaystyle I_{h}v:=I_{h}^{c}v+I_{h}^{b}(v-I_{h}^{c}v),

which combines IhcI_{h}^{c} and IhbI_{h}^{b} together. It is exactly the interpolation projecting into the trial space Vh1V_{h}^{1}. Next we will show the error estimates for the interpolation IhI_{h} defined in (3.20).

Lemma 3.4.

The interpolation IhI_{h} defined in (3.20) satisfies the error estimates as follows: for vHs(Ω)v\in H^{s}(\Omega), there hold

(3.21) vIhv0,𝒯hChs|v|s,Ω,\displaystyle\|v-I_{h}v\|_{0,\mathcal{T}_{h}}\leq Ch^{s}|v|_{s,\Omega},
(3.22) |vIhv|1,𝒯hChs1|v|s,Ω,\displaystyle|v-I_{h}v|_{1,\mathcal{T}_{h}}\leq Ch^{s-1}|v|_{s,\Omega},
(3.23) vIhvVh1Chs1|v|s,Ω,\displaystyle\interleave v-I_{h}v\interleave_{V_{h}^{1}}\leq Ch^{s-1}|v|_{s,\Omega},

where C>0C>0 is a constant independent of the mesh size hh.

Proof.

Firstly, we will consider the estimate of vIhv0,𝒯h\|v-I_{h}v\|_{0,\mathcal{T}_{h}}. By the triangle inequality, (3.16) and (3.18), we have

vIhv0,𝒯hvIhcv0,𝒯h+Ihb(vIhcv)0,𝒯hCvIhcv0,𝒯hChs|v|s,Ω,\displaystyle\|v-I_{h}v\|_{0,\mathcal{T}_{h}}\leq\|v-I_{h}^{c}v\|_{0,\mathcal{T}_{h}}+\|I_{h}^{b}(v-I_{h}^{c}v)\|_{0,\mathcal{T}_{h}}\leq C\|v-I_{h}^{c}v\|_{0,\mathcal{T}_{h}}\leq Ch^{s}|v|_{s,\Omega},

which yields the estimate (3.21).

Secondly, we will estimate |vIhv|1,𝒯h|v-I_{h}v|_{1,\mathcal{T}_{h}}. Following the triangle inequality, (3.17) and (3.19), we directly obtain

|vIhv|1,𝒯h|vIhcv|1,𝒯h+|Ihb(vIhcv)|1,𝒯hChs1|v|s,Ω,\displaystyle|v-I_{h}v|_{1,\mathcal{T}_{h}}\leq|v-I_{h}^{c}v|_{1,\mathcal{T}_{h}}+|I_{h}^{b}(v-I_{h}^{c}v)|_{1,\mathcal{T}_{h}}\leq Ch^{s-1}|v|_{s,\Omega},

which yields the estimate (3.22).

Finally, we will take vIhvVh1\interleave v-I_{h}v\interleave_{V_{h}^{1}} into consideration. For convenience, we denote vIhvv-I_{h}v by eve_{v}. By the trace inequality, (3.21) and (3.22), we have

evVh12\displaystyle\interleave e_{v}\interleave_{V_{h}^{1}}^{2} =K1/2ev0,𝒯h2+eΓh,D1he[ev]0,e2\displaystyle=\|K^{1/2}\nabla e_{v}\|_{0,\mathcal{T}_{h}}^{2}+\sum\limits_{e\in\Gamma_{h,D}}\frac{1}{h_{e}}\|[e_{v}]\|_{0,e}^{2}
Cev0,𝒯h2+CT𝒯h1hT(hT1ev0,T2+hTev0,T2)\displaystyle\leq C\|\nabla e_{v}\|_{0,\mathcal{T}_{h}}^{2}+C\sum\limits_{T\in\mathcal{T}_{h}}\frac{1}{h_{T}}\left(h_{T}^{-1}\|e_{v}\|_{0,T}^{2}+h_{T}\|\nabla e_{v}\|_{0,T}^{2}\right)
Ch2s2|v|s,Ω2,\displaystyle\leq Ch^{2s-2}|v|_{s,\Omega}^{2},

which yields the estimate (3.23). Now we complete the proof. ∎

Theorem 3.5.

Let pp be the solution of the problem (2.1)-(2.3) and php_{h} be the solution of the EPG method (2.10). We assume that pHs(Ω)p\in H^{s}(\Omega), where s>32s>\frac{3}{2}. Then there exists a constant C>0C>0 independent of the mesh size hh such that

(3.24) pphVh1Chs1|p|s,Ω.\displaystyle\interleave p-p_{h}\interleave_{V_{h}^{1}}\leq Ch^{s-1}|p|_{s,\Omega}.
Proof.

For any qhVh2q_{h}\in V_{h}^{2}, we have a(p,qh)=l(qh)a(p,q_{h})=l(q_{h}) and a(ph,qh)=l(qh),a(p_{h},q_{h})=l(q_{h}), which directly yield that

a(pph,qh)=0.a(p-p_{h},q_{h})=0.

Following (3.1), (3.15) and the above orthogonality property, we have

(3.25) CphIhpVh1\displaystyle C\interleave p_{h}-I_{h}p\interleave_{V_{h}^{1}} supqh0a(phIhp,qh)qhVh2\displaystyle\leq\mathop{sup}\limits_{q_{h}\neq 0}\frac{a(p_{h}-I_{h}p,q_{h})}{\interleave q_{h}\interleave_{V_{h}^{2}}}
supqh0a(pIhp,qh)qhVh2\displaystyle\leq\mathop{sup}\limits_{q_{h}\neq 0}\frac{a(p-I_{h}p,q_{h})}{\interleave q_{h}\interleave_{V_{h}^{2}}}
CpIhpVh1.\displaystyle\leq C\interleave p-I_{h}p\interleave_{V_{h}^{1}}.

Therefore, by the triangle inequality, (3.23) and (3.25), we have

pphVh1\displaystyle\interleave p-p_{h}\interleave_{V_{h}^{1}} pIhpVh1+IhpphVh1\displaystyle\leq\interleave p-I_{h}p\interleave_{V_{h}^{1}}+\interleave I_{h}p-p_{h}\interleave_{V_{h}^{1}}
CpIhpVh1\displaystyle\leq C\interleave p-I_{h}p\interleave_{V_{h}^{1}}
Chs1|p|s,Ω,\displaystyle\leq Ch^{s-1}|p|_{s,\Omega},

which yields the desired estimate (3.24). ∎

4. Local mass conservation and application to the species transport system

After the discrete solution of pressure in the EPG method is obtained by the decoupled algorithm, the velocity uh\textit{{u}}_{h} can be recovered as follows:

(4.1) uh=K(phc+phb),\displaystyle\textit{{u}}_{h}=-K\nabla(p_{h}^{c}+p_{h}^{b}),\quad xT,T𝒯h,\displaystyle x\in T,\quad T\in\mathcal{T}_{h},
(4.2) uhn=gN,\displaystyle\textit{{u}}_{h}\cdot\textit{{n}}=g_{N},\quad xΓh,N,\displaystyle x\in\Gamma_{h,N},
(4.3) uhn={K(phc+phb)n}|eΓh,\displaystyle\textit{{u}}_{h}\cdot\textit{{n}}=-\{K\nabla(p_{h}^{c}+p_{h}^{b})\cdot\textit{{n}}\}|_{e\in\Gamma_{h}},\quad xΓh,\displaystyle x\in\Gamma_{h},
(4.4) uhn=(K(phc+phb)n)|eΓh,D,\displaystyle\textit{{u}}_{h}\cdot\textit{{n}}=-(K\nabla(p_{h}^{c}+p_{h}^{b})\cdot\textit{{n}})|_{e\in\Gamma_{h,D}},\quad xΓh,D.\displaystyle x\in\Gamma_{h,D}.
Theorem 4.1.

Let u be the velocity of the Darcy flow in (2.1) and uh\textit{{u}}_{h} be the discrete velocity solution defined as in (4.1)-(4.4). If all the assumptions in Theorem 3.5 hold, then there exists a constant C>0C>0 independent of the mesh size hh such that

(4.5) uuh0,𝒯hChs1|p|s,Ω,\displaystyle\|\textit{{u}}-\textit{{u}}_{h}\|_{0,\mathcal{T}_{h}}\leq Ch^{s-1}|p|_{s,\Omega},
(4.6) unuhn0,ΓhΓh,DChs32|p|s,Ω.\displaystyle\|\textit{{u}}\cdot\textit{{n}}-\textit{{u}}_{h}\cdot\textit{{n}}\|_{0,\Gamma_{h}\cup\Gamma_{h,D}}\leq Ch^{s-\frac{3}{2}}|p|_{s,\Omega}.
Proof.

Firstly, by (3.24), we directly obtain

uuh0,𝒯h2CpphVh12Ch2s2|p|s,Ω2,\displaystyle\|\textit{{u}}-\textit{{u}}_{h}\|_{0,\mathcal{T}_{h}}^{2}\leq C\interleave p-p_{h}\interleave_{V_{h}^{1}}^{2}\leq Ch^{2s-2}|p|_{s,\Omega}^{2},

which yields the error estimate (4.5). Next, in order to estimate the error on the interior faces or edges, we let p¯=IhpVh1\overline{p}=I_{h}p\in V_{h}^{1} be an interpolation of pp and u¯=Kp¯\overline{\textit{{u}}}=-K\nabla\overline{p} be the corresponding velocity within each element. On the interface e=TiTjΓhe=\partial T_{i}\cap\partial T_{j}\in\Gamma_{h}, u¯\overline{\textit{{u}}} is defined as follows:

u¯|e:={u¯}=u¯|Ti+u¯|Tj2.\displaystyle\overline{\textit{{u}}}|_{e}:=\{\overline{\textit{{u}}}\}=\frac{\overline{\textit{{u}}}|_{T_{i}}+\overline{\textit{{u}}}|_{T_{j}}}{2}.

We easily have

(4.7) eΓhuneuhne0,e22eΓhuneu¯ne0,e2+2eΓhu¯neuhne0,e2.\displaystyle\sum\limits_{e\in\Gamma_{h}}\|\textit{{u}}\cdot\textit{{n}}_{e}-\textit{{u}}_{h}\cdot\textit{{n}}_{e}\|_{0,e}^{2}\leq 2\sum\limits_{e\in\Gamma_{h}}\|\textit{{u}}\cdot\textit{{n}}_{e}-\overline{\textit{{u}}}\cdot\textit{{n}}_{e}\|_{0,e}^{2}+2\sum\limits_{e\in\Gamma_{h}}\|\overline{\textit{{u}}}\cdot\textit{{n}}_{e}-\textit{{u}}_{h}\cdot\textit{{n}}_{e}\|_{0,e}^{2}.

For the right-hand side of (4.7), the two terms will be analyzed respectively. The first term can be bounded by the trace inequality and (3.22) as follows:

(4.8) eΓhuneu¯ne0,e2CT𝒯h1hTuu¯0,T2Ch2s3|p|s,Ω2.\displaystyle\sum\limits_{e\in\Gamma_{h}}\|\textit{{u}}\cdot\textit{{n}}_{e}-\overline{\textit{{u}}}\cdot\textit{{n}}_{e}\|_{0,e}^{2}\leq C\sum\limits_{T\in\mathcal{T}_{h}}\frac{1}{h_{T}}\|\textit{{u}}-\overline{\textit{{u}}}\|_{0,T}^{2}\leq Ch^{2s-3}|p|_{s,\Omega}^{2}.

Then we can estimate the second term by the trace inequality as follows:

(4.9) eΓhu¯neuhne0,e2\displaystyle\sum\limits_{e\in\Gamma_{h}}\|\overline{\textit{{u}}}\cdot\textit{{n}}_{e}-\textit{{u}}_{h}\cdot\textit{{n}}_{e}\|_{0,e}^{2} CTiTj=eΓh(u¯|Tiuh|Ti0,e2+u¯|Tjuh|Tj0,e2)\displaystyle\leq C\sum\limits_{\partial T_{i}\cap\partial T_{j}=e\in\Gamma_{h}}\left(\left\|\overline{\textit{{u}}}|_{T_{i}}-\textit{{u}}_{h}|_{T_{i}}\right\|_{0,e}^{2}+\left\|\overline{\textit{{u}}}|_{T_{j}}-\textit{{u}}_{h}|_{T_{j}}\right\|_{0,e}^{2}\right)
CT𝒯h1hTuhu¯0,T2.\displaystyle\leq C\sum\limits_{T\in\mathcal{T}_{h}}\frac{1}{h_{T}}\|\textit{{u}}_{h}-\overline{\textit{{u}}}\|_{0,T}^{2}.

By (3.22) and (4.5), the right-hand side of (4.9) can be bounded as follows:

(4.10) T𝒯h1hTuhu¯0,T2CT𝒯h1hTuhu0,T2+CT𝒯h1hTuu¯0,T2Ch2s3|p|s,Ω2.\displaystyle\sum\limits_{T\in\mathcal{T}_{h}}\frac{1}{h_{T}}\|\textit{{u}}_{h}-\overline{\textit{{u}}}\|_{0,T}^{2}\leq C\sum\limits_{T\in\mathcal{T}_{h}}\frac{1}{h_{T}}\|\textit{{u}}_{h}-\textit{{u}}\|_{0,T}^{2}+C\sum\limits_{T\in\mathcal{T}_{h}}\frac{1}{h_{T}}\|\textit{{u}}-\overline{\textit{{u}}}\|_{0,T}^{2}\leq Ch^{2s-3}|p|_{s,\Omega}^{2}.

By (4.8) and (4.10), we complete the error estimate (4.6) on the interior faces or edges. Besides, the error estimate on Dirichlet boundaries could be obtained similarly and we complete the proof. ∎

We note that the local mass conservation is an important property which is significant in numerous applications. The velocity uh\textit{{u}}_{h} recovered by the EPG method is locally mass-conservative, which will be shown in the following.

Theorem 4.2.

The velocity uh\textit{{u}}_{h} defined in (4.1)-(4.4) is locally mass-conservative, which means

(4.11) Tuhn𝑑σ=Tf𝑑x,T𝒯h.\displaystyle\int_{\partial T}\textit{{u}}_{h}\cdot\textit{{n}}d\sigma=\int_{T}fdx,\quad\forall T\in\mathcal{T}_{h}.
Proof.

We take a local element T𝒯hT\in\mathcal{T}_{h} into consideration. For the weak formulation (2.10), the test function qhq_{h} is chosen as follows:

qh:={1,xT,0,else,\displaystyle q_{h}:=\begin{cases}&1,\quad x\in T,\\ &0,\quad else,\end{cases}

which directly yields (4.11). This completes the proof. ∎

Next we take the recovered velocity uh\textit{{u}}_{h} into (2.4) to simulate the concentration in porous media. The scheme used to discrete the time derivative term could be explicit or implicit and the finite element space for concentration is chosen as M0(𝒯h)M^{0}(\mathcal{T}_{h}).

For the species transport equation, we introduce two fully discrete schemes by choosing different time discrete schemes as follows: Given chn1M0(𝒯h)c^{n-1}_{h}\in M^{0}(\mathcal{T}_{h}), find chnM0(𝒯h)c^{n}_{h}\in M^{0}(\mathcal{T}_{h}) such that

(4.12) T𝒯hTϕchnchn1Δtqh𝑑x\displaystyle\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}\phi\frac{c_{h}^{n}-c_{h}^{n-1}}{\Delta t}q_{h}dx +eΓhechn1,uhne[qh]𝑑σ\displaystyle+\sum\limits_{e\in\Gamma_{h}}\int_{e}c_{h}^{n-1,*}\textit{{u}}_{h}\cdot\textit{{n}}_{e}[q_{h}]d\sigma
+eΓinecIuhneqh𝑑σ\displaystyle+\sum\limits_{e\in\Gamma_{in}}\int_{e}c_{I}\textit{{u}}_{h}\cdot\textit{{n}}_{e}q_{h}d\sigma +eΓoutechn1uhneqh𝑑σ=T𝒯hTf^qh𝑑x,qhM0(𝒯h),\displaystyle+\sum\limits_{e\in\Gamma_{out}}\int_{e}c_{h}^{n-1}\textit{{u}}_{h}\cdot\textit{{n}}_{e}q_{h}d\sigma=\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}\widehat{f}q_{h}dx,\quad\forall q_{h}\in M^{0}(\mathcal{T}_{h}),

or

(4.13) T𝒯hTϕchnchn1Δtqh𝑑x\displaystyle\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}\phi\frac{c_{h}^{n}-c_{h}^{n-1}}{\Delta t}q_{h}dx +eΓhechn,uhne[qh]𝑑σ\displaystyle+\sum\limits_{e\in\Gamma_{h}}\int_{e}c_{h}^{n,*}\textit{{u}}_{h}\cdot\textit{{n}}_{e}[q_{h}]d\sigma
+eΓinecIuhneqh𝑑σ\displaystyle+\sum\limits_{e\in\Gamma_{in}}\int_{e}c_{I}\textit{{u}}_{h}\cdot\textit{{n}}_{e}q_{h}d\sigma +eΓoutechnuhneqh𝑑σ=T𝒯hTf^qh𝑑x,qhM0(𝒯h),\displaystyle+\sum\limits_{e\in\Gamma_{out}}\int_{e}c_{h}^{n}\textit{{u}}_{h}\cdot\textit{{n}}_{e}q_{h}d\sigma=\sum\limits_{T\in\mathcal{T}_{h}}\int_{T}\widehat{f}q_{h}dx,\quad\forall q_{h}\in M^{0}(\mathcal{T}_{h}),

where Δt\Delta t is the time step size. Here, (4.12) corresponds to the explicit scheme while (4.13) corresponds to the implicit scheme. In fact, when the discrete solution of velocity is locally mass-conservative, the discrete solution of concentration for the transport equation can hold the physical properties which will be shown in the following two theorems.

Theorem 4.3.

If the time step size Δt\Delta t is small enough, the solution of concentration of the transport equation (2.4)-(2.6) approximated by the explicit scheme (4.12) has the positive and upper bound preserving properties, which means

(4.14) chn0,ifchn10,\displaystyle c_{h}^{n}\geq 0,\qquad{\rm if}\ c_{h}^{n-1}\geq 0,
(4.15) chn1,ifchn11.\displaystyle c_{h}^{n}\leq 1,\qquad{\rm if}\ c_{h}^{n-1}\leq 1.
Proof.

It suffices to consider the case in a local element TT. For simplicity, we assume that the source/sink term equals to zero and all the faces (d=3d=3) or edges (d=2d=2) of TT are in Γh\Gamma_{h}. We denote the inflow and outflow interior faces or edges sets of T\partial T as follows:

(4.16) 1T:={eT:uhne0},\displaystyle\mathcal{E}^{T}_{1}:=\{e\in\partial T:\textit{{u}}_{h}\cdot\textit{{n}}_{e}\geq 0\},
(4.17) 2T:={eT:uhne<0},\displaystyle\mathcal{E}^{T}_{2}:=\{e\in\partial T:\textit{{u}}_{h}\cdot\textit{{n}}_{e}<0\},

where TΩ\partial T\cap\partial\Omega\neq\emptyset. The local mass conservation on this element TT is described as follows:

(4.18) e1Teuhne𝑑σ+e2Teuhne𝑑σ=0.\displaystyle\sum\limits_{e\in\mathcal{E}^{T}_{1}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma=0.

Let qh|T=1q_{h}|_{T}=1 and qh=0q_{h}=0 on other elements in (4.12), we have

(4.19) Tϕchnchn1Δt𝑑x+e1Techn1uhne𝑑σ+e2Techn1,outuhne𝑑σ=0,\displaystyle\int_{T}\phi\frac{c_{h}^{n}-c_{h}^{n-1}}{\Delta t}dx+\sum\limits_{e\in\mathcal{E}^{T}_{1}}\int_{e}c_{h}^{n-1}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}c_{h}^{n-1,out}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma=0,

where chn1,outc_{h}^{n-1,out} denotes the concentration on the outflow faces or edges. Since the approximation space for the concentration is M0(𝒯h)M^{0}(\mathcal{T}_{h}), following (4.19) we obtain

chn\displaystyle c_{h}^{n} =chn1+Δt|T|ϕ(e1Techn1uhne𝑑σe2Techn1,outuhne𝑑σ)\displaystyle=c_{h}^{n-1}+\frac{\Delta t}{|T|\phi}\left(-\sum\limits_{e\in\mathcal{E}^{T}_{1}}\int_{e}c_{h}^{n-1}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma-\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}c_{h}^{n-1,out}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma\right)
chn1Δt|T|ϕe1Techn1uhne𝑑σ\displaystyle\geq c_{h}^{n-1}-\frac{\Delta t}{|T|\phi}\sum\limits_{e\in\mathcal{E}^{T}_{1}}\int_{e}c_{h}^{n-1}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma
=(1Δt|T|ϕe1Teuhne𝑑σ)chn1,\displaystyle=\left(1-\frac{\Delta t}{|T|\phi}\sum\limits_{e\in\mathcal{E}^{T}_{1}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma\right)c_{h}^{n-1},

where |T||T| denotes the volume (d=3d=3) or the area (d=2d=2) of TT. Thus, for any T𝒯h(TΩ=)T\in\mathcal{T}_{h}\ (\partial T\cap\partial\Omega=\emptyset) , if we assume that the time step size Δt\Delta t satisfies the restriction as follows:

(4.20) Δt<|T|ϕe1Teuhne𝑑σ,,\displaystyle\Delta t<\frac{|T|\phi}{\sum\limits_{e\in\mathcal{E}^{T}_{1}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma},,

then this completes the proof of the positive-preserving property (4.14) if chn1|T>0c_{h}^{n-1}|_{T}>0.

Next, by (4.18), (4.19) and (4.20), we have

1chn\displaystyle 1-c_{h}^{n} =1chn1+Δt|T|ϕ(chn1e2Teuhne𝑑σ+e2Techn1,outuhne𝑑σ)\displaystyle=1-c_{h}^{n-1}+\frac{\Delta t}{|T|\phi}\left(-c_{h}^{n-1}\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}c_{h}^{n-1,out}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma\right)
=1chn1+Δt|T|ϕ((1chn1)e2Teuhne𝑑σ+e2Te(chn1,out1)uhne𝑑σ)\displaystyle=1-c_{h}^{n-1}+\frac{\Delta t}{|T|\phi}\left((1-c_{h}^{n-1})\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}(c_{h}^{n-1,out}-1)\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma\right)
1chn1+Δt|T|ϕ(1chn1)e2Teuhne𝑑σ\displaystyle\geq 1-c_{h}^{n-1}+\frac{\Delta t}{|T|\phi}(1-c_{h}^{n-1})\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma
=(1chn1)(1+Δt|T|ϕe2Teuhne𝑑σ)\displaystyle=(1-c_{h}^{n-1})\left(1+\frac{\Delta t}{|T|\phi}\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma\right)
=(1chn1)(1Δt|T|ϕe1Teuhne𝑑σ)0,\displaystyle=(1-c_{h}^{n-1})\left(1-\frac{\Delta t}{|T|\phi}\sum\limits_{e\in\mathcal{E}^{T}_{1}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma\right)\geq 0,

which completes the proof of the upper bound preserving property (4.15) if chn1|T1c_{h}^{n-1}|_{T}\leq 1.

For the case of T𝒯hT\in\mathcal{T}_{h}, TΩ\partial T\cap\partial\Omega\neq\emptyset, we can similarly derive (4.14) and (4.15) under the similar restriction of the time step size. ∎

Theorem 4.4.

The solution of concentration of the transport equation (2.4)-(2.6) approximated by the implicit scheme (4.13) has the positive and upper bound preserving properties, which means

(4.21) chn0,ifchn10,\displaystyle c_{h}^{n}\geq 0,\qquad{\rm if}\ c_{h}^{n-1}\geq 0,
(4.22) chn1,ifchn11.\displaystyle c_{h}^{n}\leq 1,\qquad{\rm if}\ c_{h}^{n-1}\leq 1.
Proof.

For simplicity, we assume that the source/sink term is zero. Now we consider the case in a local element TT. Similar to the definitions of (4.16) and (4.17), we denote the inflow and outflow interior faces or edges sets of T\partial T as follows:

1T:={eTΓh:uhne0},\displaystyle\mathcal{E}^{T}_{1}:=\{e\in\partial T\cap\Gamma_{h}:\textit{{u}}_{h}\cdot\textit{{n}}_{e}\geq 0\},
2T:={eTΓh:uhne<0}.\displaystyle\mathcal{E}^{T}_{2}:=\{e\in\partial T\cap\Gamma_{h}:\textit{{u}}_{h}\cdot\textit{{n}}_{e}<0\}.

Besides, we denote the faces or edges sets of T\partial T on the boundaries as follows:

3T:={eTΓout:uhne0},\displaystyle\mathcal{E}^{T}_{3}:=\{e\in\partial T\cap\Gamma_{out}:\textit{{u}}_{h}\cdot\textit{{n}}_{e}\geq 0\},
4T:={eTΓin:uhne<0}.\displaystyle\mathcal{E}^{T}_{4}:=\{e\in\partial T\cap\Gamma_{in}:\textit{{u}}_{h}\cdot\textit{{n}}_{e}<0\}.

The local mass conservation on the element TT is described as follows:

(4.23) e1Teuhne𝑑σ+e2Teuhne𝑑σ+e3Teuhne𝑑σ+e4Teuhne𝑑σ=0.\displaystyle\sum\limits_{e\in\mathcal{E}^{T}_{1}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{3}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{4}}\int_{e}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma=0.

Let qh|T=1q_{h}|_{T}=1 and qh=0q_{h}=0 on other elements in (4.13), we obtain

(4.24) Tϕchnchn1Δt𝑑x\displaystyle\int_{T}\phi\frac{c_{h}^{n}-c_{h}^{n-1}}{\Delta t}dx +e1Technuhne𝑑σ+e2Techn,outuhne𝑑σ\displaystyle+\sum\limits_{e\in\mathcal{E}^{T}_{1}}\int_{e}c_{h}^{n}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}c_{h}^{n,out}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma
+e4TecIuhne𝑑σ+e3Technuhne𝑑σ:=I1+I2+I3+I4+I5=0,\displaystyle+\sum\limits_{e\in\mathcal{E}^{T}_{4}}\int_{e}c_{I}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{3}}\int_{e}c_{h}^{n}\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma:=I_{1}+I_{2}+I_{3}+I_{4}+I_{5}=0,

where chn,outc_{h}^{n,out} denotes the concentration on the outflow interior faces or edges. By (4.24) we consider all the elements T𝒯hT\in\mathcal{T}_{h} and then we get the linear system MhChn=FhM_{h}C^{n}_{h}=F_{h} for the solution of concentration in (4.13) where ChnC^{n}_{h} denotes the column vector of the concentration chnc_{h}^{n} on all the elements. The term concerning chn1c^{n-1}_{h} in I1I_{1} and I4I_{4} in (4.24) is assembled on the right-hand side as FhF_{h}, which yields that the elements in FhF_{h} is always non-negative.

For the coefficient matrix MhM_{h} which is obviously an LL-matrix (cf. [9]), we will observe the jj-th column of MhM_{h} without loss of generality. The jj-th diagonal element of MhM_{h} is obtained from the term concerning chnc^{n}_{h} in I1I_{1}, I2I_{2} and I5I_{5} in (4.24), which means the positive coefficient on the jj-th element. Besides, there might be some negative terms in the column vector if I20I_{2}\neq 0, whose absolute value is equal to part of the jj-th diagonal element of MhM_{h} while the sign of each value is opposite. This indicates that the coefficient matrix MhM_{h} is a column strictly diagonally dominant matrix. By the Gershgorin circle theorem (cf. [38]), all the real part of eigenvalues of MhM_{h} are positive, which directly yields that MhM_{h} is a MM-matrix (cf. [9]). By the property of MM-matrix that the inverse of MhM_{h} is non-negative, we can conclude that the solution ChnC^{n}_{h} of the above linear system is nonnegative, which completes the proof of the positive preserving property (4.21) if chn10c_{h}^{n-1}\geq 0.

Besides, by (4.23) and (4.24), we directly have

Tϕ(1chn)(1chn1)Δt𝑑x\displaystyle\int_{T}\phi\frac{(1-c_{h}^{n})-(1-c_{h}^{n-1})}{\Delta t}dx +e1Te(1chn)uhne𝑑σ+e2Te(1chn,out)uhne𝑑σ\displaystyle+\sum\limits_{e\in\mathcal{E}^{T}_{1}}\int_{e}(1-c_{h}^{n})\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{2}}\int_{e}(1-c_{h}^{n,out})\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma
+e4Te(1cI)uhne𝑑σ+e3Te(1chn)uhne𝑑σ\displaystyle+\sum\limits_{e\in\mathcal{E}^{T}_{4}}\int_{e}(1-c_{I})\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma+\sum\limits_{e\in\mathcal{E}^{T}_{3}}\int_{e}(1-c_{h}^{n})\textit{{u}}_{h}\cdot\textit{{n}}_{e}d\sigma
:=J1+J2+J3+J4+J5=0.\displaystyle:=J_{1}+J_{2}+J_{3}+J_{4}+J_{5}=0.

We can also create the linear system for the solution of 1chn1-c^{n}_{h} and the analysis for the upper bound preserving property (4.22) can be similarly derived if chn11c_{h}^{n-1}\leq 1. ∎

We note that in the explicit scheme (4.12), the time step size Δt\Delta t needs to satisfy the restriction (4.20) on all the elements T𝒯hT\in\mathcal{T}_{h}. For the implicit scheme (4.13), one needs to solve a linear system to get the solution. However, no restriction of Δt\Delta t occurs in the implicit scheme (4.13).

5. Numerical experiments

In this section, we present several numerical examples in two dimensions to demonstrate the performance of our proposed EPG method. We consider a coupled problem of the Darcy flow and the species transport. The Darcy flow is solved by the CG and EPG methods while the transport equation is solved by the DG method with a piecewise constant approximation. The implicit discrete scheme (4.13) with uniform time step size is used for the simulation of the species transport. Since the scheme (4.13) is implicit, the time step size does not need to be small enough. In the following examples, the CG method is implemented for piecewise linear (P1-CG), piecewise quadratic (P2-CG), and piecewise cubic (P3-CG) continuous finite element spaces, and the EPG method is implemented for piecewise linear (P1-EPG), piecewise quadratic (P2-EPG), and piecewise cubic (P3-EPG) continuous finite element spaces coupled with the piecewise bubble functions and the piecewise constant functions as the trial and test spaces. We provide the results of convergence of the methods if the example has an exact solution. Moreover, for the transport problem in each example, the porosity ϕ\phi is 0.2, the inflow concentration cIc_{I} is one and the initial concentration c0c_{0} is zero. Besides, the total number of iterative steps for the implicit scheme (4.13) is chosen as 100.

Example 5.1.

In this example, we firstly consider the Darcy flow with an exact solution in the unit square domain Ω=[0,1]2\Omega=[0,1]^{2} and the conductivity 𝑲\boldsymbol{K} is a diagonal tensor with its entry being 1 in the entire domain. The exact pressure is denoted by p=(1x)y(1y)cosxp=(1-x)y(1-y)\cos{x} and the Dirichlet condition is imposed on the boundary.

The solutions of the pressure and the velocity are shown in Figure 5.1. Here the problem is simulated on a triangular mesh with 512 elements. Furthermore, the convergence results of the pressure and the velocity are displayed in Figure 5.2 to verify the results in Theorem 3.5 and Theorem 4.1. Here we use a log-log scale with xx-axis meaning the number of degrees of freedom and yy-axis meaning the relative error. The optimal convergence of the CG and EPG methods can be both observed from Figure 5.2.

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Figure 5.1. (Example 5.1) The solutions of pressure and Darcy velocity. Top-left: P1-CG. Top-middle: P2-CG. Top-right: P3-CG. Bottom-left: P1-EPG. Bottom-middle: P2-EPG. Bottom-right: P3-EPG.
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Figure 5.2. (Example 5.1) Relative errors. Top-bottom: P1, P2 and P3. Left: Energy error of pressure. Middle: L2L^{2} error of velocity. Right: L2L^{2} error of the normal component of velocity on the trace.

We further compute the local mass conservation residual in Figure 5.3, which is defined as follows:

(5.1) Rloc:=Tuhn𝑑σTf𝑑x.\displaystyle R_{loc}:=\int_{\partial T}\textit{{u}}_{h}\cdot\textit{{n}}d\sigma-\int_{T}fdx.

Here the number of elements on the triangluar mesh is 32768. From Figure 5.3, we can observe the local mass conservation of the EPG method in this example is in the order of 101710^{-17}, which is close to machine precision. However, the local mass conservation residual for the CG method is relatively large in the order of 10510^{-5}. Then we use the respective velocities from the CG and EPG methods to compute the concentration in the transport equation. The time step size is chosen to be 0.05. Figure 5.4 shows the simulations of the concentration at the time 4.5 based on the velocity from the CG method while Figure 5.5 is presented to show the simulations of the concentration at the time 0.2, 0.4 and 0.8 based on the velocity from the EPG method. Since the simulating results for the concentration based on the velocity from P1-EPG, P2-EPG and P3-EPG are almost the same, we also only show the simulating results for the concentration based on the velocity from P3-EPG in the following examples. The maximum concentrations of the transport equation based on the velocity from the CG and EPG methods are shown in Figure 5.6. From the above Figures, we can conclude that the concentration will not overshoot if the velocity based on the EPG method is used for the solution of transport equation. However, the concentration will overshoot if the velocity based on the CG method is used.

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Figure 5.3. (Example 5.1) Local mass conservation residual. Top-left: P1-CG. Top-middle: P2-CG. Top-right: P3-CG. Bottom-left: P1-EPG. Bottom-middle: P2-EPG. Bottom-right: P3-EPG.
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Figure 5.4. (Example 5.1) Simulations of concentration at time 4.5 based on the velocity from the CG method. Left: P1-CG. Middle: P2-CG. Right: P3-CG.
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Figure 5.5. (Example 5.1) Simulations of concentration based on the velocity from P3-EPG. Left-right: Simulations at time 0.2, 0.4 and 0.8.
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Figure 5.6. (Example 5.1) Maximum concentrations based on the velocity from the CG and EPG methods. Left-right: P1, P2 and P3.
Example 5.2.

Next we consider a ten-shaped domain Ω\Omega, which consists of five unit square subdomains and the central point is (32,32\frac{3}{2},\frac{3}{2}). The central subdomain Ωc=[54,74]2\Omega_{c}=[\frac{5}{4},\frac{7}{4}]^{2}. The conductivity 𝑲\boldsymbol{K} is still a diagonal tensor with its entry being 10210^{-2} in Ωc\Omega_{c} and 1 elsewhere. The boundary conditions for the Darcy flow are imposed as follows:

p=1,on{0}×(1,2),\displaystyle p=1,\quad{\rm on}\ \{0\}\times(1,2),
p=0,on{3}×(1,2),(1,2)×{0},(1,2)×{3},\displaystyle p=0,\quad{\rm on}\ \{3\}\times(1,2),\quad(1,2)\times\{0\},\quad(1,2)\times\{3\},
un=0,elsewhere.\displaystyle\textit{{u}}\cdot\textit{{n}}=0,\qquad{\rm elsewhere}.

The pressure and the velocity are shown in Figure 5.7 with 640 elements. Figure 5.8 describing the local mass conservation indicates that the residual (5.1) for the CG method is larger than that for the EPG method beside Ωc\Omega_{c}. Here we test the problem on a triangular mesh with 40960 elements. Moreover, we numerically compute the concentration. The time step size is chosen to be 0.03. It is clear that the phenomenon of overshooting based on velocity from the CG method is still obvious while the concentration will not overshoot based on velocity from the EPG method in this example, which are displayed in Figures 5.9 - 5.11. By comparison, it can be concluded that the local mass-conservation preserving property of the EPG method is really important.

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Figure 5.7. (Example 5.2) The solutions of pressure and Darcy velocity. Top-left: P1-CG. Top-middle: P2-CG. Top-right: P3-CG. Bottom-left: P1-EPG. Bottom-middle: P2-EPG. Bottom-right: P3-EPG.
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Figure 5.8. (Example 5.2) Local mass conservation residual. Top-left: P1-CG. Top-middle: P2-CG. Top-right: P3-CG. Bottom-left: P1-EPG. Bottom-middle: P2-EPG. Bottom-right: P3-EPG.
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Figure 5.9. (Example 5.2) Simulations of concentration at time 2.7 based on the velocity from the CG method. Left: P1-CG. Middle: P2-CG. Right: P3-CG.
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Figure 5.10. (Example 5.2) Simulations of concentration based on the velocity from P3-EPG. Left-right: Simulations at time 0.3, 1.5 and 2.7.
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Figure 5.11. (Example 5.2) Maximum concentrations based on the velocity from the CG and EPG methods. Left-right: P1, P2 and P3.
Example 5.3.

In the final example, we consider the L-shaped domain Ω=[0,2]2[0,1]2\Omega=[0,2]^{2}\setminus[0,1]^{2}. There exist two small square subdomains Ωc1=[14,34]2\Omega_{c_{1}}=[\frac{1}{4},\frac{3}{4}]^{2} and Ωc2=[14,34]×[54,74]\Omega_{c_{2}}=[\frac{1}{4},\frac{3}{4}]\times[\frac{5}{4},\frac{7}{4}]. We denote Ωc:=Ωc1Ωc2\Omega_{c}:=\Omega_{c_{1}}\cup\Omega_{c_{2}}, which represents the poorly permeable part. Similarly, the diagonal entry of 𝑲\boldsymbol{K} is defined with its entry 10210^{-2} in Ωc\Omega_{c} and 1 elsewhere. The boundary conditions for the Darcy flow are imposed as follows:

p=1,on{0}×(1,2),p=0,on{2}×(0,1),un=0,elsewhere.p=1,\quad{\rm on}\ \{0\}\times(1,2),\qquad p=0,\quad{\rm on}\ \{2\}\times(0,1),\qquad\textit{{u}}\cdot\textit{{n}}=0,\quad{\rm elsewhere}.

The pressure and the velocity are displayed in Figure 5.12 with 384 elements. We can see from Figure 5.13 that the residual (5.1) computed by the CG method is particularly larger than that computed by the EPG method at the vertices of Ωc1\Omega_{c_{1}} and Ωc2\Omega_{c_{2}}. The number of elements on the mesh we test is 24576. Thus the performance of the local mass conservation property of the EPG method is robust. Furthermore, we test the transport equation numerically. The time step size is chosen to be 0.01. It can be demonstrated that the robustness of the EPG method in terms of the upper bound preserving property for the transport can also be guaranteed while the concentration for the CG method still overshoots, as shown in Figures 5.14 - 5.16.

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Figure 5.12. (Example 5.3) The solutions of pressure and Darcy velocity. Top-left: P1-CG. Top-middle: P2-CG. Top-right: P3-CG. Bottom-left: P1-EPG. Bottom-middle: P2-EPG. Bottom-right: P3-EPG.
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Figure 5.13. (Example 5.3) Local mass conservation residual. Top-left: P1-CG. Top-middle: P2-CG. Top-right: P3-CG. Bottom-left: P1-EPG. Bottom-middle: P2-EPG. Bottom-right: P3-EPG.
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Figure 5.14. (Example 5.3) Simulations of concentration at time 0.9 based on the velocity from the CG method. Left: P1-CG. Middle: P2-CG. Right: P3-CG.
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Figure 5.15. (Example 5.3) Simulations of concentration based on the velocity from P3-EPG. Left-right: Simulations at time 0.1, 0.5 and 0.9.
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Figure 5.16. (Example 5.3) Maximum concentrations based on the velocity from the CG and EPG methods. Left-right: P1, P2 and P3.

From the above three examples, we have the following observations: Firstly, for the Darcy flow with an exact solution such as Example 5.1, we test and verify the optimal convergence in Figure 5.2. The results indicate that our proposed EPG method performs almost identical to the CG method in terms of the optimal convergence. Secondly, we test the local mass conservation of the CG and EPG methods according to (5.1). The computation is based on the Darcy flow and uh\textit{{u}}_{h} here means the recovered velocity. From the Figures 5.2, 5.8 and 5.13, we can see that the results obtained by calculating the maximum of locally mass-conservative residual for the CG method are much larger than those obtained for the EPG method. This confirms that the EPG method has the local mass conservation property that the CG method does not possess. Thirdly, we substitute the velocity computed from the Darcy flow into the species transport to numerically solve the concentration. We have already demonstrated the upper bound preserving property of the concentration in Theorem 4.4, which utilizes the local mass conservation of the velocity. To verify the upper bound preserving property, we observe the values of the maximum concentration at different iteration steps. The numerical results above show that the concentration computed based on the velocity from the CG method instead of from the EPG method typically overshoots.

6. Conclusion

In this paper we focus on the EPG method for the Darcy flow in porous media. The corresponding weak formulation we provide does not require any penalty term. Besides, the theoretical analysis and numerical experiments presented in this work have demonstrated various features of the EPG method, especially its efficiency and accuracy, as well as its preservation of the local mass conservation, as applied to the coupled flow and transport. We believe that our proposed method can also be extended to the flow problems in fractured porous media, which is our future investigation.

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