This paper provides a modified characteristics projection finite element method for the unsteady incompressible magnetohydrodynamics(MHD) equations. In this method, modified characteristics finite element method and the projection method will be combined for solving the unsteady incompressible MHD equations. Both the stability and the optimal error estimates both in L2 and H1 norms for the modified characteristics projection finite element method will be shown. In order to demonstrate the effectiveness of our method, we will present some numerical results at the end.
1.
Introduction
Magnetohydrodynamics(MHD) is a subject that studies the motion of conductive fluids in magnetic fields. It is mainly used in astrophysics, controlled thermonuclear reactions and industry. The system of MHD equations is a coupled equation system of Navier-Stokes equations of fluid mechanics and Maxwell's equations of electrodynamics (see[1,2]). In this paper, we consider the unsteady incompressible MHD equations as follows:
where u is velocity, ν kinematic viscosity, μ magnetic permeability, p hydrodynamic pressure, B magnetic field, f body force, and g applied current. The coefficients are the magnetic Reynolds number Rm. As in [3], we assume that Ω is a convex domain in Rd, d=2,3 and t∈[0,T]. Here, ut=∂u∂t, Bt=∂B∂t. The term u×B explains the effect of hydrodynamic flow on current. The magnetic Reynolds number Rm is moderate or low (from 10−2 to 1) (see[4]). For the purposes of simplicity, we choose Rm=1 in our numerical analysis.
System (1.1) is considered in conjunction with the following initial boundary conditions
where n denotes the outer unit normal of ∂Ω.
Over that last few decades, there has been a lot of works devoted on the numerical solution of MHD flows. In [5], some mathematical equations related to the MHD equations have been studied. In [6], a weighted regularization approach was applied to incompressible MHD problems. Reference [7,8] decoupled the linear MHD problem involving conducting and insulating regions. A mixed finite element method for stationary incompressible MHD equations was given in [9]. In order to avoid in-sup condition, Gerbeau [10] presented a stabilized finite element method and Salah et al. [11] proposed a Galerkin least-square method. In [12], a two-level finite element method with a stabilizing sub-grid for the incompressible MHD equations has been shown.
Recently, a convergence analysis of three finite element iterative methods for 2D/3D stationary incompressible MHD equations has been given by Dong and He (see[13]). In order to continue the in-depth explore of three-dimensional incompressible MHD system, an unconditional convergence of the Euler semi-implicit scheme for the three-dimensional incompressible MHD equations was studied by He [14]. In [15], a two-level Newton iteration method for 2D/3D steady incompressible MHD equation was proposed by Dong and He. In addition, Yuksel and Ingram have discussed the full discretization of Grank-Nicolson scheme at small magnetic Reynolds numbers (see[16]). The defect correction finite element method for the MHD equations was shown by Si et. al. [17,18,19]. In [20], a decoupling penalty finite element method for the stationary incompressible MHD equation was presented. To further study this method, we can refer to [21,22,23].
In this paper, a modified characteristics projection finite element method for the unsteady incompressible magnetohydrodynamics(MHD) equations will be given. In this method, modified characteristics finite element method and the projection method will be combined for solving the incompressible MHD equations. Both the stability and the optimal error estimates both in L2 and H1 norms for the modified characteristics projection finite element method will be derived. In order to demonstrate the effectiveness of our method, we will present some numerical results at the end of the manuscript. The contents of this paper are divided into sections as follows. To obtain the unconditional stability and optimal error estimates, in section 2, we introduce some notations and present a modified characteristics projection algorithm for the MHD equations. Then, in section 3, we give stability and error analysis and show that this method has optimal convergence order by mathematical induction. In order to demonstrate the effectiveness of our method, some numerical results are presented in the last section.
2.
Notation and preliminaries
In this section, we introduce some notations. We employ the standard Sobolev spaces Hk(Ω)=Wk,2, for nonnegative k with norm ‖v‖k=(∑k|β|=0‖Dβv‖20)1/2. For vector-value function, we use the Sobolev spaces Hk(Ω)=(Hk(Ω))d with norm ‖v‖k=(∑di=1‖vi‖2k)1/2(see [24,25]). For simplicity, we set:
which are equipped with the norms
In this paper, we will use the following equality
Then, we recall the following Poincaré-Friedrichs inequality in W: there holds
with a constant C>0 solely depending on the domain Ω; (see[26]). Here, we define the following trilinear form a1(⋅,⋅,⋅) as follows, for all u∈V, w,v∈X,
and the properties of the trilinear form a1(⋅,⋅,⋅) [27] are helpful in our analysis
where N>0 is a constant, γ0 (only dependent on Ω) is a positive constant, and C0 (only dependent on Ω) is an embedding constant of H1(Ω)↪L4(Ω) (↪ denotes the continuous embedding).
Furthermore, we define the Stokes operator A:D(A)⟶˜H such that A=−P△, where D(A)=H2(Ω)d∩X0 and P is an L2-projection from L2(Ω)d to ˜H={v∈L2(Ω)d;∇⋅v=0,v⋅n|∂Ω=0}.
Next, we recall a discrete version of Gronwall's inequality established in [14].
Lemma 2.1 Let C0,an,bn and dn, for integers n≥0, be the non-negative numbers such that
Then
Throughout this paper, we make the following assumptions on the prescribed date for the problem (1.1), which satisfies the regularity of the data needed for our main results.
Assumption (A1)(see[27,28]): Assume that the boundary of Ω is smooth so that the unique solution (v,q) of the steady Stokes problem
for prescribed f∈L2(Ω)3 satisfies
and Maxwell's equations
for the prescribed g∈L2(Ω)3 admits a unique solution B∈W0 which satisfies
Assumption (A2): The initial data u0,B0,f satisfy
Assumption (A3): We assume that the MHD problem admits a unique local strong solution (u,p,B) on (0,T) such that
Let 0=t0<t1<⋯<tN=T be a uniform partition of the time interval [0,T] with tn=nτ, and N being a positive integer. Set un=(⋅,tn), For any sequence of functions {fn}Nn=0, we define
At the initial time step, we start with U0=˜U0=u0,B0=˜B0=b0 and an arbitrary P0∈M∩H1(Ω). Then, we can give
Then, we give the algorithm as follows
Algorithm 2.1 (Time-discrete modified characteristics projection finite element method)
Step 1. Solve Bn+1, for instance
where
Step 2. Find ˜Un+1, such that
Step 3. Calculate (Un+1,Pn+1), for example
The corresponding weak form is
Step 1. Solve Bn+1, for instance
Step 2. Find ˜Un+1, such that
Step 3. Calculate (Un+1,Pn+1), for example
Remark 2.1 As we all know (Bn×curlBn+1,v)=(Bn⋅∇v,Bn+1)−(v⋅∇Bn,Bn+1). In order to improve our algorithm, we change it as (Bn⋅∇v,Bn+1)−(v⋅∇Bn,Bn).
We denote Th be a regular and quasi-uniform partition of the domain Ω into the triangles for d=2 or tetrahedra for d=3 with diameters by a real positive parameter h(h→0). The finite element pair (Xh,Mh,Wh) is constructed based on Th.
Let Wh0n=Xh×Wh. There exits a constant β0>0 (only dependent on Ω) such that
There exits a mapping rh∈L(H2(Ω)2∩V,Xh) satisfying
and a L2-projection operator ρh:M→Mh satisfying
and a mapping Rh∈L(H2(Ω)2∩Vn,Wh) satisfying
Here, we define the discrete Stokes operator Ah=−Ph△h and △h (see [15] and the references therein) defined by
Meanwhile, we define the discrete operator A1hBh=R1h(∇h×∇×Bh+∇h∇⋅Bh)∈Wh (see [15]) as follows
We define the Stokes projection (Rh(u,p),Qh(u,P)):(X,M)→(Xh,Mh) by
By classical FEM theory ([25,29,30]), we have the following results.
Lemma 2.2 Assume that u∈H10(Ω)d∩Hr+1(Ω)d and p∈L20(Ω)∩Hr(Ω). Then,
and
Lemma 2.3 If (u,p)∈W2,k(Ω)d×W1,k(Ω) for k>d,
Algorithm 2.2 (The fully discrete modified characteristics projection finite element method)
Step 1. Solve Bn+1h, for instance
where
Step 2. Find ˜Un+1, such that
Step 3. Calculate (un+1h,pn+1h), for example
3.
Unconditional stability and convergence
3.1. Error estimation for the time-discrete method
Here, we make use of the following notation:
Lemma 3.1 (see[31]). Assume that g1,g2,ρ are three functions defined in Ω and ρ|∂Ω=0. If
then
where 1/q1+1/q2=1/q,1<q<∞.
The following theorem gives insight on the error estimate between the time-discrete solution and the solution of the time-dependent MHD system (1.1).
Theorem 3.1 Suppose that assumption A2–A3 are satisfied, there exists a positive C>0 such that
Proof. Firstly, we prove the following inequality
by mathematical induction for m=0,1,...,N.
Since U0=u0,B0=b0 the above inequality hold for m=0.
We assume that (3.1) and (3.2) hold for m≤n for some integer n≥0. By Sobolev embedding theory, we get
and
when τ≤τ1 for some positive constant τ1.
To prove (3.1) and (3.2) for m=n+1, we rewrite (1.1) by
where un+1=U(tn+1),bn+1=B(tn+1), and
and
define the truncation error. We can refer to ([31]), there holds that
The corresponding weak form is
Combining (2.13) and (2.14), we obtain
Then, we rewrite (3.14) and (2.12) as
and
Subtracting (3.15) and (3.16) from (3.11) and (3.13), respectively, leads to
and
Testing (2.9) by τen+1, since ∇⋅en+1=0, we arrive at
Testing (2.9) by τen, we get
Subtracting (3.20) from (3.19), we can obtain
Let v=2τ˜en+1 in (3.17), we obtain
Let ψ=2μτεn+1 in (3.18), we get
Taking sum of (3.22) and (3.23) yields
From (2.9), we have
Then, we can obtain
On the other hand, using Lemma 3.1, we deduce that
Substituting these above inequality into (3.24), we obtain
Taking sum of the (3.25) for n from 0 to m≤N and using discrete Gronwall's inequality Lemma 2.1, we get
Owing to (3.21), we have
To acquire the H1 estimates, we take v=2τDτen+1 in (3.17) to get
Then, we take ψ=2μτDτεn+1 in (3.18) to get
Combining (3.28) and (3.29), we obtain
Similarly, by Lemma 3.1, we have
Substituting these above inequality into (3.30), we obtain
Taking sum of the (3.31) for n from 0 to m≤N and using discrete Gronwall's inequality Lemma 2.1, we arrive at
Furthermore, the standard result for (3.17) and (3.18) with p=2, respectively, leads to
Thanks to (3.19), we can obtain
Then, we have
From (3.35), we can arrive at
From (2.7) and (2.5), we have
and
By (2.9), we have
Considering the identity ∇2˜Un+1=∇∇⋅˜Un+1−∇×∇טUn+1 and (3.46), we can obtain
Now, the standard result for the Stokes system (3.17) and (3.18) with p=d∗>2, respectively, leads to
By (3.48) and (3.49), we get
Thus, we can obtain
The proof is complete.
3.2. Error estimation for the fully discrete method
For the sake of simplicity, we denote Rnh=Rh(Un,Pn),Qnh=Qh(Un,Pn),R0h=R0hBn,n=1,2,...,N, and enh=unh−Rnh,˜enh=˜unh−Rnh,εnh=Bnh−Rn0h,n=1,2,...,N, where R0h:L2(Ω)3→Wh is the L2-orthogonal projection, where
Theorem 3.2 Suppose that assumption A2–A3 are satisfied, there exists a positive C>0 such that
Proof. We prove following estimates
by mathematical induction for m=0,1,...,N.
When m=0,u0h=u0,B0h=B0. It is obvious (3.56) holds at the initial time step. We assume that (3.56) holds for 0≤m≤n for some integer n≥0. By (2.20), (2.21), (3.54), (3.55), Theorem 3.1 and inverse inequality, we infer
and
Combining (2.23) and (2.24), we obtain
When m=n+1, letting vh=2τ˜un+1h in (3.61), we can obtain
Letting vh=τun+1h in (2.24), since ∇⋅un+1h=0, it follows that
Taking vh=τunh in (2.24), we get
Subtracting (3.64) from (3.63), we can obtain
Using 2(a−b,a)=‖a‖20−‖b‖20+‖a−b‖20, leads to
Taking vh=∇pn+1h in (2.24), we deduce
When m=n+1, letting ψh=2μτBn+1h in (2.22), we can obtain
Using 2(a−b,a)=‖a‖20−‖b‖20+‖a−b‖20, we have
Taking sum of (3.66) and (3.69) yields
Then, we can obtain
Substituting these above estimates into (3.70), we obtain
Taking sum of the (3.71) for n from 0 to m≤N and using discrete Gronwall's inequality Lemma 2.1, we get
Letting vh=2τAun+1h in (3.61), we obtain
From (3.63), we arrive at
Using 2(a−b,a)=‖a‖20−‖b‖20+‖a−b‖20, leads to
Letting ψh=2μτcurlcurlBn+1h in (2.22), we can obtain
Taking sum of (3.73) and (3.74) yields
Then, we get
Substituting these above estimates into (3.75), we obtain
Taking sum of the (3.76) for n from 0 to m≤N and using discrete Gronwall's inequality Lemma 2.1, we get
Then, we rewrite (3.61) and (2.22) as
and
Subtracting (3.15) and (3.16) from (3.77) and (3.78), respectively, leads to
and
Taking vh=2τen+1h in (2.24), we can obtain
Let θn=Un−Rnh,ηn=Bn−Rn0h. By taking vh=2τen+1h in (3.79), we deduce
By taking ψh=2μτεn+1h in (3.80), we have
Combining (3.81) and (3.82), we obtain
Due to (2.19) and Theorem 3.1, we can get ‖θn‖0≤Ch2(‖Un‖2+‖Pn‖1)≤Ch2, ‖ηn‖0≤Ch2‖Bn‖2. By Lemma 3.1, there holds that
Substituting these above estimates into (3.83), we obtain
Taking the sum of the (3.76) for n from 0 to m≤N and using the discrete Gronwall's inequality Lemma 2.1, we get
Then, we can deduce
Thus, all the results in Theorem 3.2 have been proved.
4.
Numerical results
In order to show the effect of our method, we present some numerical results. Here, we consider the
The boundary conditions and the forcing terms are given by the exact solution. The finite element spaces are chosen as P1b-P1-P1b finite element spaces. Here, we choose τ=h2 and h=1/n, n=8,16,24,32,40,48. Different Reynolds number Re and magnetic Reynolds number Rm are chosen to show the effect of our method, the numerical results were shown in Tables 1–6. Here, we use the software package FreeFEM++ [32] for our program.
Tables 1 and 2 give the numerical results for Re=1.0 and Rm=1.0. In order to show the effect of our method for high Reynolds number, we give the numerical results for Re=100.0, 1000.0 and Rm=100.0, 1000.0. Tables 3 and 4 give the numerical results for Re=100.0 and Rm=100.0. Tables 5 and 6 give the numerical results for Re=1000.0 and Rm=1000.0. It shows that our method is effect for high Reynolds numbers. It shows that the errors are goes small as the space step goes small and the convergence orders are optimal. We can see that |∫Ω∇⋅Bdx| and |∫Ω∇⋅udx| are small, which means that our method can conserve the Gauss's law very well.
5.
Conclusions
In this paper, we have given a modified characteristics projection finite element method for the unsteady incompressible magnetohydrodynamics(MHD) equations. In this method, the modified characteristics finite element method and the projection method were combined for solving the incompressible MHD equations. Both the stability and the optimal error estimates in L2 and H1 norms for the modified characteristics projection finite element method have been given. In order to demonstrate the effectiveness of our method, some numerical results were given at the end of the manuscript.
Acknowledgments
The authors would like to thank the anonymous referees for their valuable suggestions and comments, which helped to improve the quality of the paper. This work is supported in part by National Natural Science Foundation of China (No. 11971152), China Postdoctoral Science Foundation (No. 2018M630907) and the Key scientific research projects Henan Colleges and Universities (No. 19B110007).
Conflict of interest
The authors declare there is no conflict of interest in this paper.