Abstract
In this article, a mixed finite element method for thermally coupled, stationary incompressible MHD problems with physical parameters dependent on temperature in the Lipschitz domain is considered. Due to the variable coefficients of the MHD model, the nonlinearity of the system is increased. A stationary discrete scheme based on the coefficients dependent temperature is proposed, in which the magnetic equation is approximated by Nédélec edge elements, and the thermal and Navier–Stokes equations are approximated by the mixed finite elements. We rigorously establish the optimal error estimates for velocity, pressure, temperature, magnetic induction and Lagrange multiplier with the hypothesis of a low regularity for the exact solution. Finally, a numerical experiment is provided to illustrate the performance and convergence rates of our numerical scheme.
1. Introduction
In this paper, we develop a steady-state magnetohydrodynamics (MHD) system coupling thermal problem with the physical parameters dependent on temperature in [1,2,3], as follows:
where is the outer unit normal of , and is a bounded domain with a Lipschitz boundary ; (, p, , r, ) denote the velocity field, pressure, magnetic induction, scalar fuction and temperature; (, , , , ) denote the kinematic viscosity, electric conductivity, coupling number, thermal conductivity and thermal expansion coefficient; (, , ) denote a given heat source, a forcing term for magnetic induction and the known applied current with . In fact, the scalar function r is a virtual function. The purpose of adding r is related to the constraint [4,5].
Many numerical methods for incompressible MHD problems have been widely studied. According to our investigation, a considerable number of scholars in the literature use continuous Lagrange finite elements to approximate velocity and magnetic induction unknowns, see, e.g., [6,7,8,9,10]. However, it is well known that using continuous elements to approximate magnetic induction may lead to an inaccurate approximation when the regularity of the magnetic unknown is lower than , cf. [11,12], which may often be encountered in non-convex polyhedral or with a non- boundary. A novel method to overcome these shortcomings was put forward in [13] by using Nédélec finite elements to approximate the magnetic unknown B. This seems attractive and has been used in [14,15,16,17] and the references therein. In addition, the authors had proposed different formulas to keep the magnetic solutions divergence-free in the numerical schemes in the papers [18,19].
Because of the movement of the fluid with viscosity, viscosity will produce heat. Under the action of the external magnetic field, the incompressible MHD problem is usually coupled with the thermal system through the famous Boussinesq approximation. For example, Meir et al. [20,21] studied the mixed finite element method for the thermally coupled MHD equation by adopting continuous elements to approximate the unknowns of magnetic, fluid and thermal problems, which is pioneering work. Coupling fluid systems or electromagnetic models with coefficients dependent on temperature face the mathematical challenge of solving strongly nonlinear partial differential equations, as studied by some physicists and mathematicians, see, e.g., [22,23,24,25,26,27,28,29] and the references therein. In addition, in many practical applications of the MHD system, the change in temperature will lead to a change in the coefficients in the fluid field and electromagnetic field. For the coupling MHD problem whose coefficients depend on temperature, it is important to study its reliable finite element method.
In this paper, we aim to give a rigorous well-posed analysis of the solution to the continuous problem and error estimates for the MHD system with variable coefficients by the finite element method. The fluid field was approximated by Taylor–Hood-type finite elements, and the thermal system was approximated by Lagrange finite elements. Considering the highly nonlinearity brought by the physical parameters dependent on temperature and the Lorentz terms in the magnetic equation, as well as a possible non-convex domain or a non- boundary, we choose -conforming Nédélec edge elements to approximate the magnetic equation to capture the physical solutions. The optimal error estimates of velocity, pressure, temperature, magnetic induction and Lagrange multiplier are established. As far as we know, there still lacks rigorous analysis in the literature for the error estimate of the stationary MHD thermally coupled model with temperature-dependent coefficients.
The remaining parts of this paper are organized as follows. In Section 2, we introduce some notations and basic finite element estimation used in the discussion and show the uniqueness of the solution to the continuous system. In Section 3, we propose a discrete finite element method for the variable coefficient system consisting of Equations (1)–(6). In Section 4, we give the convergence of all variables under the slightly smooth regularity assumption. In Section 5, we verify the effectiveness of the proposed numerical method through a numerical experiment.
2. Notations for the Variable Coefficients Model
Firstly, we introduce some symbols that will be used throughout this article. For all , , let denote the standard Sobolev space, and when , it can be written as . The notation is expressed as an inner product, namely , and the norm in defined by . Vector-valued quantities will be denoted in boldface notations, such as and . We use C and c to denote generic positive constants independent of the mesh size h, and it may adopt different values in different places.
To simplify, we define the following Sobolev spaces
The norm of the following types still need to be defined:
We then set
and , which is equipped with the following norm:
To facilitate our analysis, the following embedding results (see, e.g., Proposition 3.7 of [30] or [31]) are introduced here, which are also valid for the Lipschitz polyhedron domain.
Lemma 1.
There exists a parameter such that the embedding is compact.
In order to better demonstrate the stability of energy, the following trilinear terms are denoted
for any and .
Next, the definition of the weak solution to the magneto-heat coupling system with variable coefficients (Equations (1)–(6)) is given.
Definition 1.
Remark 1.
Owing to for any , by selecting in Equation (8), it can be derived . Therefore, the Lagrange multiplier in the sense of a weak formulation. In this case, the corresponding orthogonal decomposition is , see [32,33].
Remark 2.
Uniqueness of Continuous Problems
Throughout the paper, we set that , , and are Lipschitz continuous and satisfy , , and .
Before proving the uniqueness of continuous problems, we first introduce some basic knowledge.
Lemma 2.
For the convenience of the subsequent analysis, setting
The norms are defined as:
It is well known that (cf. [31,35]) both and satisfy the corresponding inf-sup conditions, namely,
and
where the generic constant C only depends on .
Before we begin the proof, the following assumptions should be given:
- ,
- ,
- ,
where is the Lipschitz constant.
Now, we are going to prove that the solution of the continuous problem is unique.
Theorem 1.
Proof.
Taking in Equation (9), we can deduce that
this implies
Setting in Equations (7) and (8), we have
combining with Equation (13), there holds
which implies that
Then, the following estimation is valid
Now, we start to demonstrate the uniqueness of the solution for the problem in Equations (7)–(9). Suppose that and are two arbitrary solution of Equations (7)–(9), for any such that
and
By subtracting Equation (17) from Equation (16), we obtain
Taking , applying , there hold
which means that
Thus, if satisfies
where , we can deduce , and it is easy to check .
3. Finite Element Analysis for Magneto-Heat Coupling System
In this section, we introduce a mixed finite element approximation of the MHD system coupled thermal problem in Equations (7)–(9). The approximation is based on the Nédélec first family of elements for the discretization of the magnetic induction.
Throughout, the domain is partitioned into a finite number of open non-overlapping subdomains with regular and quasi-uniform meshes of mesh-size h that partition into tetrahedra K. Each tetrahedron K is supposed to be the image of a reference tetrahedron under an affine map . and represent the space of polynomials of the total degree at most and homogeneous polynomials k on K, respectively.
Given the generalized Taylor–Hood element with , where is the k order vectorial Lagrange finite element subspace of , and is the order scalar Lagrange finite element subspace of Q. For , the velocity and pressure pair can be approximated by the well-known stable mini-elements, cf. [31,35,36]. Furthermore, is the k order scalar Lagrange finite element subspace of Y, refer to [31,35].
For , it denotes the polynomials in that satisfy on K. Define the following space
where . Using Nédélec -conforming finite element space (see [33,37])
to approximate the magnetic induction.
Setting , and we can define the following weakly divergent space
In addition, the following discrete Poincaré–Friedrichs inequality is established
with a constant independent of the mesh size h.
The link between the spaces and is accomplished by the Hodge mapping (refer to [12]), where such that
Furthermore, there exists ,
In addition, the discrete kernel space of the divergence operator is given by
On a quasi-uniform mesh, there holds (see Theorem 3.2.6 of [38])
where is a generic constant independent of the mesh size h, ı and m are two real numbers with , and p and q are two integers with .
The following discrete inf-sup conditions (see Chapter 2 of [36] or [12]) are founded
where is a generic positive constant depending on the domain .
For , our goal is to find , ∀ such that
Remark 3.
Remark 4.
For all , by selecting in Equation (27), it can be derived . Thus, for a solenoidal source term , it is natural to deduce .
In order to estimate the error in the next section, the stability of the numerical scheme in Equations (25)–(28) should be given here.
Proof.
The proof is parallel to that of Theorem 1. □
4. Convergence Analysis of the Magneto-Heat Coupling Problem
In this section, the convergence of the MHD system coupled the heat equation with variable coefficients is considered by employing the finite element method. We strictly establish optimal error estimates of velocity, pressure, temperature, magnetic induction and Lagrange multiplier under the assumption that the exact solution has low regularity.
Here, it is necessary to make the following regularity assumptions for the weak solution of Equations (7)–(9), which will facilitate the error estimate of the discrete solution.
Assumption 1.
Assum that the solution satisfies the following regularity:
where the exponent depends on Ω.
For the convenience of the subsequent analysis, we will assume there exists a constant depending on , , and such that
Let , for and , with the help of [31,40], then we have the following approximation properties:
where k and s are the order index of the finite element spaces and the regularity of the exact solution, respectively.
Let . A combination of Equations (7)–(9) and Equations (25)–(28) yields the following truncation error equations:
With the preparations of the above work, we now begin to study the optimal error estimation of each variable.
Theorem 3.
Proof.
As a first step, the test functions of the momentum and magnetic equations are constrained in the discrete kernel space. Let . Using the orthogonality property, with Equation (32), we have
According to Lemma 1 and the property of Hodge mapping (Equation (21)), by setting , it is easy to see that
and similarly
As a consequence of the previous calculation, we can estimate Equation (36) as follows
Since belongs to kernel space , we deduce for any . The right-hand side of Equation (36) has the following estimate
Using Equation (33), we can arrive at
The left-hand side of Equation (39) has the following estimate
The right-hand side of Equation (39) has the following estimate
Using Equation (34), we derive
The left-hand side of Equation (42) has the following estimate
Since belongs to the kernel space , we have for any . The right-hand side of Equation (42) has the following estimate
Combining Equations (37), (40), (43), (38), (41) and (44), together with (32)–(34), it can be checked that
Since
this means that
By the triangle inequality, there holds
for all belongs to the discrete kernel space , , and .
In the next step, let be arbitrary. Suppose that is a solution of
for any .
In addition, by using the inf-sup condition (Equation (23)), we obtain the following estimates for pressure and the Lagrange multiplier.
Theorem 4.
Proof.
With the help of (31), the following theorem draws the conclusion of this paper.
Theorem 5.
Suppose that Assumption 1, Theorem 3 and Theorem 4 are satisfied. With , we have
5. Numerical Experiment
In this section, we consider a numerical experiment to test the convergence rate of the numerical scheme proposed in Section 3. The parallel code is developed based on the finite element package Parallel Hierarchical Grids (PHG), cf. [41,42]. The computations are carried out on the LSSC-IV Cluster of the State Key Laboratory of Scientific and Engineering Computing, Chinese Academy of Sciences. The domain is , and the finite element mesh is obtained by a uniform tetrahedral partition. Let be four successively refined meshes listed in Table 1.
Table 1.
Numbers of DOFs on four successively refined meshes.
Example 1.
This example is to verify the convergence rate of the finite element solution. Given , and . The exact solution is selected as
From Table 2 and Table 3, we find that the convergence rates for and are given by
Table 2.
Convergence rates in energy norms.
Table 3.
Convergence rates in —norms.
Here, the velocity and the temperature θ are discretized by using the continuous finite elements, the pressure p is discretized by using the continuous finite elements and the magnetic induction is discretized by using the first-order edge elements method. This means that optimal convergence rates are obtained for all variables.
Author Contributions
Supervision, S.M.; Visualization, X.L.; Writing—original draft, Q.D. All authors have read and agreed to the published version of the manuscript.
Funding
The first author was supported by the Shandong Province Natural Science Foundation ZR2021QA054 and the China Postdoctoral Science Foundation 2021M691951. The third author was supported by the National Natural Science Foundation of China (Nos 11871467, 12161141017).
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
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