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. 2022 Feb 3;24(2):236. doi: 10.3390/e24020236

Finite Element Iterative Methods for the Stationary Double-Diffusive Natural Convection Model

Yaxin Wei 1, Pengzhan Huang 1,*
Editor: Mikhail Sheremet1
PMCID: PMC8871032  PMID: 35205529

Abstract

In this paper, we consider the stationary double-diffusive natural convection model, which can model heat and mass transfer phenomena. Based on the fixed point theorem, the existence and uniqueness of the considered model are proved. Moreover, we design three finite element iterative methods for the considered problem. Under the uniqueness condition of a weak solution, iterative method I is stable. Compared with iterative method I, iterative method II is stable with a stronger condition. Moreover, iterative method III is stable with the strongest condition. From the perspective of viscosity, iterative method I displays well in the case of a low viscosity number, iterative method II runs well with slightly low viscosity, and iterative method III can deal with high viscosity. Finally, some numerical experiments are presented for testing the correctness of the theoretic analysis.

Keywords: double-diffusive natural convection, finite element discretization, iterative methods, viscosity, uniqueness condition

1. Introduction

The double-diffusive natural convection model, which does not only incorporate the velocity vector field as well as the pressure field, but also contains the temperature field and the concentration field, has been widely used in scientific, engineering and industrial applications such as nuclear design, cooling of electronic equipment, aircraft cabins, insulation with double pane windows, and so on. For greater understanding of the physical background, authors can refer to [1,2,3]. In recent years, the impact of nanofluid on free convection heat transfer was investigated by researchers in [4]. The free convective flow of a Nano-Encapsulated Phase Change Material (NEPCM) suspension in an eccentric annulus was investigated numerically in [5]. The authors obtained that the volume fraction of the NEPCM particles and Stefan number effect the thermal and hydrodynamic characteristics of the suspension. The effect of the arrangement of the tubes in a multi-tube heat exchanger during the solidification process was considered in [6], which focused on the natural convection effect in phase change material in this research.

Let ΩR2 be a open bounded domain with a Lipschitz continuous boundary Ω and Γ is a subset of Ω, u=(u1,u2) denotes the velocity field, p is the fluid pressure, T is the temperature, C is the concentration, g=(0,1) is the gravitational acceleration vector, fi is the forcing function, i=1,2. Moreover, n represents the outer normal vector, ν>0 is the viscosity, Da is the Darcy number, γ>0 is the heat diffusivity, Dc is the mass diffusivity, βT and βC are the thermal and solutal expansion coefficients.

The governing equations of this double-diffusive natural convection model are presented as follows [7].

ν2u1x2+2u1y2+u1u1x+u2u1y=Da1u1px,inΩ,ν2u2x2+2u2y2+u1u2x+u2u2y=βTT+βCCDa1u2py,inΩ,u1x+u2y=0,inΩ,γ2Tx2+2Ty2+u1Tx+u2Ty=f2inΩ,Dc2Cx2+2Cy2+u1Tx+u2Ty=f2inΩ,u=0,onΩ,T=0,C=0,onΓ,Tn=Cn=0,onΩ\Γ. (1)

Many numerical studies were made concerning the double-diffusive natural convection model. A projection-based stabilized finite element method for steady-state natural convection problem was considered in [8]. A stabilized finite element error analysis for the Darcy–Brinkman model of double-diffusive convection in a porous medium was discussed in [9]. An efficient two-step algorithm for the steady-state natural convection problem was presented in [10]. The melting process of a nano-enhanced phase change material in a square cavity was investigated in [11]. In numerical test, the author used the Galerkin finite element method to solve the dimensionless partial differential equations. Based on the idea of curvature stabilization, Çıbık et al. [12] discussed a family of second order time stepping methods for the Darcy–Brinkman equations. A decoupled finite element method called the modified characteristics method was considered in [13]. Rajabi et al. performed the detailed uncertainty propagation analysis and variance-based global sensitivity analysis on the widely adopted double-diffuse convection benchmark problem of a square porous cavity with horizontal temperature and concentration gradients in [14]. In [15], the mixed convection heat transfer of AL2O3 nanofuid in a horizontal channel subjected with two heat sources was considered. In [16], the curvature-based stabilization method was considered for double-diffusive natural convection flows in the presence of a magnetic field and unconditionally stable and optimally accurate second order approximations were obtained. There are several works devoted to the efficient numerical methods for the treatment of nonlinear problems. For example, several iterative methods for the 2D steady penalty Navier–Stokes equations were presented and discussed in [17]. He et al. [18] discussed a combination of two-level methods and iterative methods for solving the 2D/3D steady Navier–Stokes equations. Some iterative finite element methods for steady Navier–Stokes equations with different viscosities were discussed in [19]. Furthermore, the authors refer to the Oseen method [20], the Newton method [21] and the Euler implicit-explicit methods [22]. Recently, Huang et al. [23] have considered and analyzed the Oseen, Newton and Stokes iterative methods for the 2D steady Navier–Stokes equations. He et al. [24] considered and analyzed three iterative methods for the 3D steady MHD equations.

The main work in this paper is to design, analyze, and compare three iteration methods to solve nonlinear equations based on the finite element discretization. Then, we will show the performance of these numerical methods in both theoretical analysis and numerical experiments. By setting σ=mα2ν2N(γ1f11+Dc1f21)+mα2ν1N¯(γ2f11+Dc2f21), we obtain the conclusion that the three iterative methods are stable and convergent as σ(0,14). Iterative method I and II are valid as σ[14,13) and only iterative method I runs well as σ[13,1).

In this paper, by developing some techniques and using some ideas in [7], we prove the existence and uniqueness with a different method, then we obtain a different uniqueness condition. Furthermore, we propose and analyze iterative methods I and III. In addition to this, we use iterative method II to computer a smaller viscosity than them in numerical experiments. Compared with He et al. [24], although the iterative methods are the same, the considered problems are different.

The paper is organized as follows. In Section 2, we describe the considered problem and some mathematical preliminaries. In the next section, we prove the existence and uniqueness of the weak solution to the considered equations. Then, we analyze stability and iterative error estimates of three iterative methods in Section 4. In Section 5, we show some numerical experiments to verify the correctness of theoretical results. In the last section, conclusions are presented.

2. Preliminaries

In this section, we present some basic notations and properties for the stationary double-diffusive natural convection problem. First, for 1q and mN+, we use standard notations for Sobolev space Wm,q(Ω) and Lebegue space Lq(Ω). In particular, L2(Ω) norm and its inner product are denoted by ·0 and (·,·). Moreover, for f, an element in the dual space of H1(Ω), its norm is defined by

f1=supψH1(Ω)|(f,ψ)|ψ0.

Next, we introduce the functional spaces associated with the velocity, the pressure, the temperature, and the concentration:

X={uH1(Ω)2:u|Ω=0},W={ψH1(Ω):ψ|Γ=0},Q={sH1(Ω):s|Γ=0},M=qL2(Ω):Ωqdx=0.

Then, we define the following particular subspace of the velocity space X

V=vX:ΩqdivvdΩ=0,qM.

Moreover, define several continuous bilinear forms a0(·,·),a1(·,·),a2(·,·) and d(·,·) on X×X,W×W,Q×Q and X×M, respectively,

a0(u,v)=ν(u,v),u,vX,a1(T,ψ)=γ(T,ψ),T,ψW,a2(C,s)=Dc(C,s),C,sQ,d(q,v)=(q,divv),vX,qM.

Further, denote three skew-symmetric trilinear forms:

c0(u,v,w)=((u·)v,w)+12((divu)v,w)=12((u·)v,w)12((u·)w,v),u,w,vX,c1(u,T,ψ)=((u·)T,ψ)+12((divu)T,ψ)=12((u·)T,ψ)12((u·)ψ,T),uX,T,ψW,c2(u,C,s)=((u·)C,s)+12((divu)C,s)=12((u·)C,s)12((u·)s,C),uX,C,sQ.

Please note that the bilinear form d(·,·) is continuous on X×M and satisfies the inf-sup condition [25]: there exists a positive constant β0 such that

supvV|d(q,v)|v0β0q0,qM.

The trilinear forms [18] satisfy

c0(u,v,w)=c0(u,w,v),|c0(u,v,w)|N0u0v0w0, (2)

and

c1(u,T,ψ)=c1(u,ψ,T),c2(u,C,s)=c2(u,s,C),|c1(u,T,ψ)|N1u0T0ψ0,|c2(u,C,s)|N2u0C0s0, (3)

where Ni>0,i=0,1,2, are three constants defined as N0=supu,v,wX|c0(u,v,w)|u0v0w0, N1=supuX,T,ψW|c1(u,T,ψ)|u0T0ψ0, and N2=supuX,C,sQ|c2(u,C,s)|u0C0s0.

Furthermore, we recall the Poincaré inequality [25]

u0αu0,uH1(Ω), (4)

where α is a positive constant depending on Ω.

The variational form of the model (1) is presented as follows: find (u,p,T,C)X×M×W×Q such that for all (v,q,ψ,s)X×M×W×Q

a0(u,v)+c0(u,u,v)+Da1(u,v)d(p,v)+d(q,u)=(βTTg+βCCg,v),a1(T,ψ)+c1(u,T,ψ)=(f1,ψ),a2(C,s)+c2(u,C,s)=(f2,s). (5)

3. Existence and Uniqueness

This section gives the existence and uniqueness of (5), which is crucial to consider the discrete scheme.

Theorem 1.

There exists at least a solution pair (u,p,T,C)X×M×W×Q which satisfies (5) and

T0γ1f11,C0Dc1f21,u0ν1mα2(γ1f11+Dc1f21). (6)

Proof

First, for uX, it is easy to see that a1(·,·)+c1(u,·,·) and a2(·,·)+c2(u,·,·) are continuous, elliptic bilinear forms of W×W and Q×Q, respectively. Hence, according to the Lax–Milgram theorem, there exists a unique solution TW to the second equation of (5), and a unique solution CQ to the third equation of (5). The theorem will be proved if we can show that there is at least a solution uX in the first equation of (5).

Secondly, a0(·,·) is a continuous and elliptic bilinear form on X×X. Using (2) and (4) we obtain

|c0(u,u,v)+(βTTg+βCCg,v)|N0u02+mα2(T0+C0)v0,

where m=|g|max{|βT|,|βC|}. Then, we define a mapping A:XX by A(u)=w1 where

a0(w1,v)+Da1(w1,v)=c0(u,u,v)+(βTTg+βCCg,v),vV. (7)

Clearly, u is a solution of the first equation of (5) with vV, if it is a solution of A(u)=u. Using the Leray-Schauder Principle [26], A(u)=u has at least one solution uX, if (a) A is completely continuous; (b) there exists M1>0 such that for every λ[0,1] and vX with λAv=v,v satisfies the bound v0M1.

Assume u1,u2X and subtract the equations obtained from (7) with u=u1 and u=u2. Then, set w=A(u2)A(u1) and choose v=w to yield

a0(w,w)+Da1(w,w)=c0(u2u1,u2,w)c0(u1,u2u1,w)+(βT(T2T1)g+βC(C2C1)g,w). (8)

Moreover, in order to estimate (T2T1)0 and (C2C1)0, we substitute T1 and T2 in the second equation of (5) and subtract the ensuing equations to obtain

a1(T2T1,ψ)=c1(u2u1,T2,ψ)c1(u1,T2T1,ψ).

Taking ψ=T2T1 and using (3) we obtain

(T2T1)0γ1N1(u2u1)0T20. (9)

Analogously, we have

(C2C1)0Dc1N2(u2u1)0C20. (10)

Further, combining (9) and (10), we obtain the bound of (8) as follows

w0ν1N0u10+N0u20+mα2(γ1N1T20+Dc1N2C20)(u2u1)0.

Hence, A is completely continuous.

Now, we prove (b). If λ=0, then v=0 and v0=0. Assume λ(0,1] and vX satisfies λAv=v. Then, from (7), we have

λ1a0(v,v)+λ1Da1(v,v)=c0(v,v,v)+(βTTg+βCCg,v).

Using (2) and (4), we arrive at

v0ν1λmα2(T0+C0).

Thirdly, setting ψ=T in the second equation of (5), we have

γT02+c1(u,T,T)f11T0.

Thus, applying (3) leads to

T0γ1f11.

Similarly, taking s=C in the third equation of (5), we obtain

C0Dc1f21.

Moreover, choosing v=u in the first equation of (5) and using (4), we arrive at

νu02+c0(u,u,u)mα2(T0+C0)u0,

which combines with the above two equations to give

u0ν1mα2(γ1f11+Dc1f21).

The proof is completed. □

Theorem 2.

Assume that (u,p,T,C)X×M×W×Q is a solution pair of (5). If ν, Dc, γ, C and T satisfy the following uniqueness condition

0<σ:=mα2ν2N0(γ1f11+Dc1f21)+mα2ν1(γ2N1f11+Dc2N2f21)<1,

then (u,p,T,C) is unique solution pair of (5).

Proof. 

Suppose (u1,p1,T1,C1) is also a solution pair of (5) and u1u,p1p,T1T,C1C, then

a0(u1,v)+c0(u1,u1,v)+Da1(u1,v)d(p1,v)+d(q,u1)=(βTT1g+βCC1g,v),a0(u,v)+c0(u,u,v)+Da1(u,v)d(p,v)+d(q,u)=(βTTg+βCCg,v), (11)

for all (v,q)X×M.

Now, choosing v=uu1 and q=pp1, we obtain

a0(uu1,uu1)+Da1(uu1,uu1)=c0(uu1,u,uu1)+(βT(TT1)g+βC(CC1)g,uu1).

Hence, applying (4), (9), (10), Theorem 1 and the uniqueness condition, we have

ν(uu1)02N0u0+mα2(γ1N1T0+Dc1N2C0)(uu1)02<ν(uu1)02,

a contradiction. Hence, u1=u,T1=T,C1=C.  □

4. Several Iterative Methods Based on the Finite Element Discretization

In this section, we propose three iterative methods for the double-diffusive natural convection model. Then the stability and convergence of these iterative methods are considered. First, let 0<h<1 denote the mesh size which is a real positive parameter and Kh={K:KΩK¯=Ω¯} be a uniform partition of Ω¯ into non-overlapping triangles. Next, given a Kh, we consider the finite element spaces Xh,Mh, Wh and Qh

Vh={vhVC0(Ω¯)2:vh|KP2(K)2,KKh},Mh={qhMC0(Ω¯):qh|KP1(K),KKh},Wh={ψhWC0(Ω¯):ψh|KP2(K),KKh},Qh={shQC0(Ω¯):sh|KP2(K),KKh},

where Pi(K) represents the space of the order polynomial on the set Kh, i=1,2. Please note that the Taylor-Hood element Xh×Mh satisfies the following discret inf-sup condition

supvXh|d(q,v)|v0βq0,qMh,

where the constant β>0 is independent of h.

With the above notations, the finite element scheme for the natural convection problem is defined as follows: find (uh,ph,Th,Ch)X×M×W×Q such that

a0(uh,v)+c0(uh,uh,v)+Da1(uh,v)d(ph,v)+d(q,uh)=(βTThg+βCChg,v),a1(Th,ψ)+c1(uh,Th,ψ)=(f1,ψ),a2(Ch,s)+c2(uh,Ch,s)=(f2,s), (12)

for all (v,q,ψ,s)Xh×Mh×Wh×Qh. The following stability and convergence results of the numerical solutions to (12) are showed.

Theorem 3.

([7,8,26,27]) Let (u,p,T,C)(H3(Ω)2X)×(H2(Ω)M)×(H3(Ω)W)×(H3(Ω)Q). Under the assumption of Theorem 2, the numerical solution pair (uh,ph,Th,Ch) to (12) satisfies

Th0γ1f11,Ch0Dc1f21,

and

uh0ν1mα(γ1f11+Dc1f21).

Moreover, the following error estimate holds

(uuh)0+(pph)0+(TTh)0+(CCh)0ch2(u3+p2+T3+C3),

where c is a positive constant depending on h.

In the following part of this section, we propose and analyse three iterative methods.

Iterative method I. Find (uhn,phn,Thn,Chn)Xh×Mh×Wh×Qh such that

a0(uhn,v)+c0(uhn1,uhn,v)+Da1(uhn,v)d(phn,v)+d(q,uhn)=(βTThng+βCChng,v),a1(Thn,ψ)+c1(uhn1,Thn,ψ)=(f1,ψ),a2(Chn,s)+c2(uhn1,Chn,s)=(f2,s), (13)

for all (vh,q,ψ,s)Xh×Mh×Wh×Qh.

Iterative method II. Find (uhn,phn,Thn,Chn)Xh×Mh×Wh×Qh such that

a0(uhn,v)+c0(uhn1,uhn,v)+c0(uhn,uhn1,v)c0(uhn1,uhn1,v)+Da1(uhn,v)d(v,phn)+d(uhn,q)=(βTThng+βCChng,v),a1(Thn,ψ)+c1(uhn1,Thn,ψ)+c1(uhn,Thn1,ψ)c1(uhn1,Thn1,ψ)=(f1,ψ),a2(Chn,s)+c2(uhn1,Chn,s)+c2(uhn,Chn1,s)c2(uhn1,Chn1,s)=(f2,s), (14)

for all (v,q,ψ,s)Xh×Mh×Wh×Qh.

Iterative method III. Find (uhn,phn,Thn,Chn)Xh×Mh×Wh×Qh such that

a0(uhn,v)+c0(uhn1,uhn1,v)+Da1(uhn,v)d(phn,v)+d(q,uhn)=(βTThng+βCChng,v),a1(Thn,ψ)+c1(uhn1,Thn1,ψ)=(f1,ψ),a2(Chn,s)+c2(uhn1,Chn1,s)=(f2,s), (15)

for all (v,q,ψ,s)Xh×Mh×Wh×Qh.

For the above three iterative methods, the initial guess (uh0,ph0,Th0,Ch0)Xh×Mh×Wh×Qh is defined by solving the following equations

a0(uh0,v)+Da1(uh0,v)d(ph0,v)+d(q,uh0)=(βTTh0g+βCCh0g,v),a1(Th0,ψ)=(f1,ψ),a2(Ch0,s)=(f2,s), (16)

for all (v,q,ψ,s)Xh×Mh×Wh×Qh.

Now, we will establish the stability and iterative error estimates of the presented iterative methods for the double-diffusive natural convection model. For the sake of simplicity, let (en,ηn,ξn,δn)=(uhuhn,phphn,ThThn,ChChn).

Theorem 4.

Under the assumptions of Theorem 3, (uhn,phn,Thn,Chn) defined by iterative method I satisfies

uhn0ν1mα2(γ1f11+Dc1f21),Thn0γ1f11,Chn0Dc1f21, (17)

for all n0. Furthermore, the following iterative error bounds hold

en0σnν1mα2(γ1f11+Dc1f21),ηn04β1σnmα2(γ1f11+Dc1f21),ξn0σnγ1f11,δn0σnDc1f21, (18)

for all n0.

Proof. 

First, the induction method is used to consider the stability of iterative method I. Setting (v,q,ψ,s)=(uh0,ph0,Th0,Ch0) in (16) leads to

Th00γ1f11,Ch00Dc1f21,uh00ν1mα2(Th00+Ch00)ν1mα2(γ1f11+Dc1f21). (19)

which shows that (17) holds for n=0.

Next, assuming that it holds for n=k, we prove that it is valid for n=k+1. Taking (v,q,ψ,s)=(uhk+1,phk+1,Thk+1,Chk+1) in (13) with n=k+1 and applying (2), (3) and (4) yield

Thk+10γ1f11,Chk+10Dc1f21,uhk+10ν1mα2(Thk+10+Chk+10).

Hence, we finish the induction method.

Moreover, we consider the iterative error estimates of iterative method I. Making use of (12) and (13) yields the error equations

a0(en,v)+c0(uhn1,en,v)+c0(en1,uh,v)+Da1(en,v)d(ηn,v)+d(q,en)=(βTξng+βCδng,v),a1(ξn,ψ)+c1(uhn1,ξn,ψ)+c1(en1,Th,ψ)=0,a2(δn,s)+c2(uhn1,δn,s)+c2(en1,Ch,s)=0. (20)

Setting ψ=ξn, s=δn in the second and the third equation of (20) and using (3), (17), and Theorem 3, we obtain

ξn0N1γ2f11en10,n1,δn0N2Dc2f21en10,n1. (21)

Then, taking (v,q)=(en,ηn) in the first equation of (20) and using (2), (4), (17), (21) and Theorem 3, we arrive at

νen0N0en10uh0+mα2(ξn0+δn0)N0en10ν1mα2(γ1f11+Dc1f21)+mα2(N1γ2f11+N2Dc2f21)en10.

Hence, using uniqueness condition, we have

en0σen10σne00,n1. (22)

Furthermore, subtracting (16) from (12), we obtain

a0(e0,v)+c0(uh,uh,v)+Da1(e0,v)d(η0,v)+d(q,e0)=(βTξ0g+βCδ0g,v),a1(ξ0,ψ)+c1(uh,Th,ψ)=0,a2(δ0,s)+c2(uh,Ch,s)=0.

Applying (4), the Theorem 2 and the Theorem 3, we obtain

ξ00N1γ2ν1mα2(γ1f11+Dc1f21)f11γ1f11,δ00N2Dc2ν1mα2(γ1f11+Dc1f21)f21Dc1f21,e00N0ν3m2α4(γ1f11+Dc1f21)2+N1γ2ν1m2α4(γ1f11+Dc1f21)f11+N2Dc2ν1m2α4(γ1f11+Dc1f21)f21,ν1mα(γ1f11+Dc1f21), (23)

which combines with (21) and (22), we arrive at

en0σnν1mα2(γ1f11+Dc1f21),ξn0N1γ2f11σn1ν1mα2(γ1f11+Dc1f21)σnγ1f11,δn0N2Dc2f21σn1ν1mα2(γ1f11+Dc1f21),σnDc1f21,

for all n0.

Finally, applying the discrete inf-sup condition, from the first equation of (20) with q=0, the error estimate of the pressure can be stated as follows.

ηn0β1νen0+N0uhn10en0+N0en10uh0+β1mα2(ξn0+δn0)β1(σnmα2(γ1f11+Dc1f21)+N0ν2m2α4(σn+σn1)(γ1f11+Dc1f21)2+mα2σn(γ1f11+Dc1f21))4β1σnmα2(γ1f11+Dc1f21),

for all n0.  □

Theorem 5.

Under the assumptions of Theorem 3, suppose that the following condition (the strong uniqueness condition)

0<σ<13, (24)

holds. Then (uhn,phn,Thn,Chn) generated by iterative method II satisfies

Thn043γ1f11,Chn043Dc1f21,uhn043ν1mα2(γ1f11+Dc1f21), (25)

for all n0. Furthermore, the following iterative error bounds hold

en095σ2n1ν1mα2(γ1f11+Dc1f21),ηn011945β195σ2n1mα2(γ1f11+Dc1f21),ξn095σ2n1γ1f11,δn095σ2n1Dc1f21, (26)

for all n0.

Proof. 

Combining with (19) and (23), it is found that (25) and (26) hold for n=0. Supposing that (25) and (26) hold for n=k, we shall prove that they are valid for n=k+1.

Subtracting (14) from (12), we obtain the error equations

a0(en,v)+c0(uhn1,en,v)+c0(en,uhn1,v)+c0(en1,en1,v)+Da1(en,v)d(v,ηn)+d(en,q)=(βTξng+βCδng,v),a1(ξn,ψ)+c1(uhn1,ξn,ψ)+c1(en,Thn1,ψ)+c1(en1,ξn1,ψ)=0,a2(σn,s)+c2(uhn1,δn,s)+c2(en,Chn1,s)+c2(en1,δn1,s)=0. (27)

Setting (v,q,ψ,s)=(ehn,ηhn,ξhn,δhn) in (27) with n=k+1 and applying (2), (3), (4) and the assumptions on n=k, we have

ξk+10N1γ1ek+10Thk0+N1γ1ek0ξk043N1γ2f11ek+10+N1γ1ek0ξk0,δk+10N2Dc1ek+10Chk0+N2Dc1ek0δk043N2Dc2f21ek+10+N2Dc1ek0δk0, (28)

and

νek+10N0uhk0ek+10+N0ek02+mα2(ξk+10+δk+10)43N0ν1mα2(γ1f11+Dc1f21)ek+10+Nek02+mα2(43N1γ2f11ek+10+N1γ1ek0ξk0)+mα2(43N2Dc2f21ek+10+N2Dc1ek0δk0). (29)

Moreover, imply the strong uniqueness condition (24) on (29), we obtain

ek+1095N0ν195σ2k+12ν2m2α4(γ1f11+Dc1f21)2+95ν1mα2N195σ2k+12ν1mα2γ2(γ1f11+Dc1f21)f11+95ν1mα2N295σ2k+12ν1mα2Dc2(γ1f11+Dc1f21)f2195σ2k+11ν1mα2(γ1f11+Dc1f21). (30)

Hence, making use of (30), we rewrite (28) as

ξk+1043N1γ2f1195σ2k+11ν1mα(γ1f11+Dc1f21)+N1γ195σ2k+12ν1mα(γ1f11+Dc1f21)γ1f1195σ2k+11γ1f11.δk+1043N2Dc2f2195σ2k+11ν1mα(γ1f11+Dc1f21)+N2Dc195σ2k+12ν1mα(γ1f11+Dc1f21)Dc1f2195σ2k+11Dc1f21. (31)

Combining the first equation of (27) with n=k+1 and q=0 and the discrete inf-sup condition, we have

ηk+10β1(νek+10+N0ek+10uhk0+N0ek02)+β1mα2(ξk+10+δk+10)β1(ν95σ2k+11ν1mα2(γ1f11+Dc1f21)+N095σ2k+11ν1mα2(γ1f11+Dc1f21)×43ν1mα2(γ1f11+Dc1f21)+N095σ2k+12ν2m2α4(γ1f11+Dc1f21)2+mα295σ2k+11γ1f11+95σ2k+11Dc1f21)11945β195σ2k+11mα2(γ1f11+Dc1f21). (32)

Furthermore, subtracting (16) from (14) with n=1 that

a0(uh1uh0,v)+c0(uh0,uh1uh0,v)+c0(uh1,uh0,v)+Da1(uh1uh0,v)d(v,ph1ph0)+d(uh1uh0,q)=(βT(Th1Th0)g+βC(Ch1Ch0)g,v),a1(Th1Th0,ψ)+c1(uh0,Th1Th0,ψ)+c1(uh1,Th0,ψ)=0,a2(Ch1Ch0,s)+c2(uh0,Ch1Ch0,s)+c2(uh1,Ch0,s)=0. (33)

Then, taking ψ=Th1Th0 in the second equation of (33), we observe that

(Th1Th0)0N1γ1uh10Th00,

and

(Ch1Ch0)0N2Dc1uh10Ch00.

Moreover, setting v=uh1uh0 in the first equation of (33), we obtain

(uh1uh0)0ν1N0uh10uh00+ν1mα2((Th1Th0)0+(Ch1Ch0)0)N0ν2mα2(γ1f11+Dc1f21)uh10+ν1mα2(N1γ2f11+N2Dc2f21)uh10σuh10. (34)

Combining (14) with n=1 and using (34), we obtain

Th10γ1N1(uh1uh0)0Th00+γ1f11γ2N1σf11uh10+γ1f11,Ch10Dc1N2(uh1uh0)0Ch00+Dc1f21Dc2N2σf21uh10+Dc1f21,uh10ν1N0(uh1uh0)0uh00+ν1mα2(Th10+Ch10)ν2N0σuh10mα2(γ1f11+Dc1f21)+ν1mα2(γ2N1σf11uh10+γ1f11+Dc2N2σf21uh10+Dc1f21)σ2uh10+ν1mα2(γ1f11+Dc1f21).

In view of the strong uniqueness condition (24), we arrive at

uh1098ν1mα2(γ1f11+Dc1f21),Th1098γ1f11,Ch1098Dc1f21.

Next, taking (v,q,ψ,s)=(uhn,phn,Thn,Chn) in (14) with n2, and using (2), (3) and (26), we obtain

Thn0γ1c1(uhnuhn1,Thn1Thn,ψ)+γ1f11γ1N1(en1en)0(ξn1ξn)0+γ1f11γ1N195σ3+95σ2ν1mα2(γ1f11+Dc1f21)γ1f11+γ1f11γ1N1353+352ν1mα2(γ1f11+Dc1f21)γ1f11+γ1f1143γ1f11.

Similarly, we obtain

Chn043Dc1f21.

Finally, it has

uhn0ν1N0(en1en)02+ν1mα2(Thn0+Chn0)ν1N0(en1en)02+ν1mα2(γ1N1(en1en)0(ξn1ξn)0+γ1f11)+ν1mα2(Dc1N2(en1en)0(δn1δn)0+Dc1f21)ν1N0353+352ν2m2α4(γ1f11+Dc1f2)1)2+ν1mα2(γ1N1353+352ν1mα2(γ1f11+Dc1f21)γ1f11+γ1f11)+ν1mα2(Dc1N2353+352ν1mα2(γ1f11+Dc1f21)Dc1f21+Dc1f21)43ν1mα2(γ1f11+Dc1f21).

The proof is completed. □

Theorem 6.

Under the assumptions of Theorem 3, suppose that the following condition (the stronger uniqueness condition),

0<σ<14, (35)

holds. Then (uhn,phn,Thn,Chn) defined by the iterative method III satisfies

uhn02ν1mα2(γ1f11+Dc1f21),Thn02γ1f11,Chn02Dc1f21, (36)

for all n0. Furthermore, the following iterative error bounds hold

en0(3σ)nν1mα2(γ1f11+Dc1f21),ηn05β1(3σ)nmα2(γ1f11+Dc1f21),ξn0(3σ)nγ1f11,δn0(3σ)nDc1f21, (37)

for all n0.

Proof. 

From (19) and (23), it is obvious that (36) and (37) hold for n=0. Supposing that (36) and (37) hold for n=k, we shall prove that they are valid for n=k+1.

Setting (v,q,ψ,s)=(uhn,phn,Thn,Chn) in (15) with n=k+1 and using (2), (3), (4) and (36), we obtain that

Thk+10γ1N1uhk0Thk0+γ1f11γ1N12ν1mα2(γ1f11+Dc1f21)2γ1f11+γ1f112γ1f11,Chk+10Dc1N2uhk0Chk0+Dc1f11Dc1N22ν1mα2(γ1f11+Dc1f21)2Dc1f21+Dc1f212Dc1f21,uhk+10ν1N0uhk02+ν1mα2(Thk+10+Chk+10)ν1N0uhk02+ν1mα2(γ1N1uhm0Thk0+γ1f11)+ν1mα2(Dc1N2uhk0Chk0+Dc1f11)ν1N04ν2m2α4(γ1f11+Dc1f21)2+4ν2γ2m2α4N1(γ1f11+Dc1f21)f11+ν1mα2γ1f11+ν1mα2Dc1f21+4ν2Dc2m2α4N2(γ1f11+Dc1f21)f212ν1mα2(γ1f11+Dc1f21).

Hence, (36) is valid for n=k+1. Consequently, subtracting (15) from (12) yields

a0(en,v)+c0(uhn1,en1,v)+c0(en1,uh,v)+Da1(en,v)d(ηn,v)+d(q,en)=(βTξng+βCδng,v),a1(ξn,ψ)+c1(uhn1,ξn1,ψ)+c1(en1,Th,ψ)=0,a2(δn,s)+c2(uhn1,δn1,s)+c2(en1,Ch,s)=0. (38)

Now, choosing ψ=ξn, in the second equation of (38) and using (3), (36), (37) and Theorem 3, we can deduce that

ξn02N1γ1ν1mα2(γ1f11+Dc1f21)ξn10+N1γ2f11en102N1γ1ν1mα2(γ1f11+Dc1f21)(3σ)n1γ1f11+N1γ2f11(3σ)n1ν1mα2(γ1f11+Dc1f21)(3σ)nγ1f11,n1. (39)

Similarly, one has

δn02N2Dc1ν1mα2(γ1f11+Dc1f21)δn10+N2Dc2f21en102N2Dc1ν1mα2(γ1f11+Dc1f21)(3σ)n1Dc1f21+N2Dc2f21(3σ)n1ν1mα2(γ1f11+Dc1f21)(3σ)nDc1f21,n1. (40)

Moreover, taking (v,q)=(en,ηn) in the first equation of (38) and using (2), (4), (36), (37) and the Theorem 3, we find that

en0ν1N0ν1mα2(γ1f11+Dc1f21)en10+2ν1N0en10(ν1mα2(γ1f11+Dc1f21)+mα2ν1(2γ1ν1mα2(γ1N1f11+Dc1N2f21)ξn10+N1γ2f11en10)+mα2ν1(2Dc1ν1mα2(γ1N1f11+Dc1N2f21)δn10+N2Dc2f21en10)3ν1N0(3σ)n1ν2m2α4(γ1f11+Dc1f21)2+mα2ν1(N1γ2f11(3σ)n1ν1mα2(γ1f11+Dc1f21)+2γ1ν1mα2(γ1N1f11+Dc1N2f21)(3σ)n1γ1f11)+mα2ν1(N2Dc2f21(3σ)n1ν1mα2(γ1f11+Dc1f21)+2Dc1ν1mα2(γ1N1f11+Dc1N2f21)(3σ)n1Dc1f21)(3σ)nν1mα2(γ1f11+Dc1f21),n1. (41)

Finally, combining the first equation of (38) with q=0 and the discrete inf-sup condition, the error estimate for the pressure can be stated as follows

ηn0β1(νen0+N0uhn10en10+N0en10uh0+mα2(ξn0+δn0))β1(ν(3σ)nν1mα2(γ1f11+Dc1f21)+N0(3σ)n1ν1mα2(γ1f11+Dc1f21)2ν1mα2(γ1f11+Dc1f21)+N0(3σ)n1ν1mα2(γ1f11+Dc1f21)mα2(γ1f11+Dc1f21)+mα2(3σ)n(γ1f11+Dc1f21))5β1(3σ)nmα2(γ1f11+Dc1f21).

5. Numerical Experiments

In this section, several numerical experiments are presented to compare these iterative methods for the considered equations. We use the public finite element software FreeFem++ [28].

5.1. An Analytical Solution Problem

For numerical implementations, the iterative tolerance is 1.0×105. The first issue to be considered here is to compare these iterative methods for the stationary double-diffusive natural convection in the case of Ω=[0,1]×[0,1]R2, to reveal the relationship between the iterative methods and the viscosity. We consider the following exact solutions.

p(x,y)=cos(πx)cos(πy),u1(x,y)=2πsin2(πx)sin(πy)cos(πy),u2(x,y)=2πsin(πx)sin2(πy)cos(πx),T(x,y)=u1(x,y)+u2(x,y),C(x,y)=u1(x,y)u2(x,y). (42)

Set the Darcy number Da=1, the thermal expansion coefficient βT=1, the solutal expansion coefficient βC=1, the heat diffusivity γ=1, the mass diffusivity Dc=1 and ui=0, T=0, C=0 on Ω,i=1,2. The forcing function fi can be calculated using (42), i = 1,2. We use a fixed value of mesh size h=164, and perform tests for the values of the viscosity coefficients going from ν=1 to ν=1.0×104.

We compare the numbers of iteration and the computational time in Table 1. This table shows that all iterative methods run well in the case of ν=1. When the viscosity number increases to ν=1.0×102, iterative method III is divergent. Finally, iterative methods II and III can not export the data with ν=1.0×104, iterative method I is still convergent. From a computational point of view, the calculation time of iterative method I and iterative method II is similar. However, iterative method II saves about 30% of calculation time compared iterative method III when ν=1. Iterative method II saves about 35% of calculation time compared with iterative method I when ν=1.0×102. We can conclude that iterative method III is the simplest method for a high viscosity number. The iterative method II is a fast and high accuracy method for a slightly lower viscosity number. Iterative method I is stable under uniqueness condition of weak solutions in the case of the lowest viscosity number. For three iterative methods, the relative error estimates are presented in Table 2, Table 3 and Table 4.

Table 1.

CPU-time in second (iterative step) needed to reach the convergence tolerance.

Scheme ν =1 ν=1.0×102 ν=1.0×104
I 50.696 (4) 174.857 (14) 424.661  (41)
II 49.432 (4) 112.317 (6)
III 78.703 (7)

Table 2.

Comparison of three iterative methods using P2P1P2P2 (h=164 and ν=1).

Scheme (uuhn)0u0 pphn0p0 (TThn)0T0 (CChn)0C0
I 0.000717912 0.000206301 0.000359132 0.00094964
II 0.000717912 0.000206303 0.000359132 0.00094964
III 0.000717912 0.000206251 0.000359145 0.000949645

Table 3.

Comparison of three iterative methods using P2P1P2P2 (h=164 and ν=1.0×102).

Scheme (uuhn)0u0 pphn0p0 (TThn)0T0 (CChn)0C0
I 0.000738137 0.000200965 0.000359132 0.00094964
II 0.000738136 0.00020096 0.000359132 0.00094964
III

Table 4.

Comparison of three iterative methods using P2P1P2P2 (h=164 and ν=1.0×104).

Scheme (uuhn)0u0 pphn0p0 (TThn)0T0 (CChn)0C0
I 0.00759437 0.000203286 0.000359133 0.000949641
II
III

5.2. The Cavity Problem

In this numerical experiment, we assume that the boundary conditions satisfy [7,9]

T=1,C=1,u=0atx1=0,T=1,C=1,u=0atx1=1,Tn=0,Cn=0,u=0atx2=0,Tn=0,Cn=0,u=0atx2=1, (43)

and set Da=1, βT=1, βC=1, γ=0.1, Dc=0.01, fi=0 and the mesh size h=164, i=1,2. Moreover, the convergence tolerance is set to equal 1.0×106. The domain with its boundary conditions is illustrated in Figure 1. We present the velocity streamlines, the pressure isobars, the isotherms and the isoconcentration lines for different values of the viscosity coefficients ν=1.0, ν=1.0×103, ν=1.0×104.

Figure 1.

Figure 1

Figure 1

Velocity streamlines of iteration method I (the first line), iteration method II (the second line) and iteration method III (the third line) with different viscosity coefficients 1.0 (the first column), 1.0×103 (the second column) and 1.0×104 (the third column). Da=1, βT=1, βC=1, γ=0.1, Dc=0.01.

Then, we show numerical velocity streamlines, isobars of pressure, isotherms, and isoconcentration lines obtained by three iterative methods with different viscosity numbers. We plot these results in Figure 2, Figure 3, Figure 4 and Figure 5. From these graphs, we obtain that the values of viscosity not only heavily impact on the velocity streamlines and the isobars, but also affect the isotherms and the isoconcentration lines. In fact, three iterations run well with ν=1.0. However, iterative method III cannot run with ν=1.0×103 while iterative method II cannot export the data with ν=1.0×104.

Figure 2.

Figure 2

Figure 2

Pressure isobars of iteration method I (the first line), iteration method II (the second line) and iteration method III (the third line) with different viscosity coefficients 1.0 (the first column), 1.0×103 (the second column) and 1.0×104 (the third column). Da=1, βT=1, βC=1, γ=0.1, Dc=0.01.

Figure 3.

Figure 3

Isotherms of iteration method I (the first line), iteration method II (the second line) and iteration method III (the third line) with different viscosity coefficients 1.0 (the first column), 1.0×103 (the second column) and 1.0×104 (the third column). Da=1, βT=1, βC=1, γ=0.1, Dc=0.01.

Figure 4.

Figure 4

The computational domain with its boundary conditions.

Figure 5.

Figure 5

Figure 5

Isotherms of iteration method I (the first line), iteration method II (the second line), iteration method III (the third line) with different viscosity coefficients 1.0 (the first column), 1.0×103 (the second column) and 1.0×104 (the third column). Da=1, βT=1, βC=1, γ=0.1, Dc=0.01.

To consider the independency of mesh in a square cavity, we use iterative method I to calculate the model (1) under different mesh sizes. The results are presented in Figure 6. We can see that there is no difference in the calculation results under different mesh sizes, so we can verify the independence of the mesh size.

Figure 6.

Figure 6

Velocity streamlines (the first line) and pressure isobars (the second line) of iteration method I with different mesh size h=116 (the first column), h=132 (the second column) and h=164 (the third column). ν=1, Da=0.01, βT=100, βC=100, γ=0.1, Dc=0.1.

6. Conclusions

In conclusion, for solving stationary double-diffusive natural convection equations, three iterative methods have their own advantages under different viscosity numbers. In the case of 0<σ<14, all methods can export data. Moreover, in the case of 14σ<13, iterative method I and II can run well. Finally, in the case of 13σ<1, only iterative method I can export data.

From the perspective of physical applications, these finite element iterative methods can be used to simulate different double-diffusive natural convection models, such as the aluminum oxide nanofluid natural convection heat transfer, the natural convection flow of a suspension containing nano-encapsulated. Furthermore, some different boundary conditions of these models with some different calculation areas should be considered, such as the T-geometry enclosure porous cavity, L-geometry cavity, and porous cavity.

Acknowledgments

The authors sincerely thank the editor and anonymous reviewers for their valuable comments and suggestions which led to a large improvement of the paper.

Abbreviations

a bilinear form w mapping difference
A a mapping W temperature space
c trilinear form x dimensionless coordinate
C concentration X velocity space
Da Darcy number y dimensionless coordinate
Dc mass diffusivity Greeksymbols
e iterative error of velocity βT thermal expansion coefficient
f forcing function βC solutal expansion coefficient
g gravitational acceleration vector β positive constant
h mesh size γ heat diffusivity
H dual space ψ test function for temperature
k iterative step σ uniqueness condition
K triangular region λ constant[0,1]
L Lebegue space ν viscosity
m m=|g|max{|βT|,|βC|} α Poincaré constant
M pressure space η iterative error of pressure
n iterative step δ iterative error of concentration
N constant ξ iterative error of temperature
p fluid pressure Subscript
P polynomial i 1,2
q test function for pressure h finite element discretization
Q concentration space
s test function for concentration
T temperature
u velocity field
v test function for velocity
V subspace of the velocity space

Author Contributions

Investigation, Y.W. and P.H.; Supervision, P.H.; Writing—original draft, Y.W.; Writing—review and editing, P.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Natural Science Foundation of Xinjiang Province grant number 2021D01E11.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data sharing not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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