Mixed finite element methods for the ferrofluid model with magnetization paralleled to the magnetic field
Abstract.
Mixed finite element methods are considered for a ferrofluid flow model with magnetization paralleled to the magnetic field. The ferrofluid model is a coupled system of the Maxwell equations and the incompressible Navier-Stokes equations. By skillfully introducing some new variables, the model is rewritten as several decoupled subsystems that can be solved independently. Mixed finite element formulations are given to discretize the decoupled systems with proper finite element spaces. Existence and uniqueness of the mixed finite element solutions are shown, and optimal order error estimates are obtained under some reasonable assumptions. Numerical experiments confirm the theoretical results.
Key words and phrases:
ferrofluid flow, decoupled system, mixed finite element method, error estimate2010 Mathematics Subject Classification:
65N55; 65F10; 65N22; 65N30;1. Introduction
Ferrofluids are colloidal liquids consisting of non-conductive nanoscale ferromagnetic or ferrimagnetic particles suspended in carrier fluids, and have extensive applications in many technology and biomedicine fields [22, 31]. There are two main ferrohydrodynamics (FHD) models which treat ferrofluids as homogeneous monophase fluids: the Rosensweig’s model [24, 23] and the Shliomis’ model [25, 26]. The main difference between these two models lies in that the former one considers the internal rotation of the nanoparticles, while the latter deals with the rotation as a magnetic torque. We refer to [1, 4, 2, 3, 21] for some existence results of solutions to the two FHD models.
The FHD models are coupled nonlinear systems of the Maxwell equations and the incompressible Navier-Stokes equations. There are limited works in the literature on the numerical analysis of the FHD models. In [27, 17, 16, 30], several numerical schemes were applied to solve reduced two dimensional FHD models where some nonlinear terms of the original models are dropped. Nochetto et al. [20] showed the energy stability of the Rosensweig’s model, proposed an energy-stable numerical scheme using finite element methods, and gave the existence and convergence of the numerical solutions. Recently, Wu and Xie [29] developed a class of energy-preserving mixed finite element methods for the Shliomis’ FHD model, and derived optimal error estimates for both the the semi- and fully discrete schemes. We also note that in [32] an unconditionally energy-stable fully discrete finite element method was presented for a two-phase FHD model.
In this paper, we consider the Shliomis’ FHD model with the assumption that the magnetization field is parallel to the magnetic field. Under this assumption, the magnetization equation in the Shliomis’ model degenerates to the Langevin magnetization law [17, 24, 23]. We introduce some new variables to transform the model into two main decoupled subsystems, i.e., a nonlinear elliptic equation and the incompressible Navier-Stokes equations. We apply proper finite element spaces to discretize the nonlinear decoupled systems, prove the existence and, under some reasonable assumptions, uniqueness of the finite element solutions, and derive optimal error estimates. We also show that our scheme preserves the ferrofluids’ nonconductive property exactly.
The rest of this paper is organized as follows. In section 2, we introduce several Sobolev spaces, give the governing equation of the FHD model with magnetization paralleled to magnetic field, reform the FHD model equivalently, and construct the weak formulations. In section 3, we recall the finite element spaces, show the existence and uniqueness of solutions for the constructed finite element methods, and give the optimal order error estimates. In section 4, some numerical experiments will be given to verify our theoretical results.
2. Preliminary
In this section, we introduce several Sobolev spaces, give the governing equations of the FHD model with magnetization paralleled to magnetic field, derive the equivalent decoupled systems, and present the weak formulations.
2.1. Sobolev spaces
Let () be a bounded and simply connected convex domain with Lipschitz boundary , and be the unit outward normal vector on .
For any , we denote by the space of all power- integrable functions on with norm . For any nonnegative integer , denote by the usual -th order Sobolev space with norm and semi-norm . In particular, denotes the space of square integrable functions on , with the inner product and norm . For the vector spaces and , we use the same notations of norm, semi-norm and inner product as those for the scalar cases.
We further introduce the Sobolev spaces
and
and set
where
and and are the Cartesian coordinates in two and three dimensions, respectively.
For any Sobolev space with norm , we use to denote the dual space of , and to denote the dual product between and . For any , the operator norm of is defined as .
2.2. Governing equations of the ferrofluid flow
We consider the domain filled with ferrofluid flow. On the macroscopic level, the mathematical model for describing the interactions between magnetic fields and ferrofluids consists of the Maxwell’s equations and the Navier-Stokes equations [23, 24, 25, 26]. Since the ferrofluid flow is nonconductive, the corresponding Maxwell’s equations read as:
(1) | ||||
(2) |
with the magnetic field and the magnetic induction satisfying the relation
(3) |
where is the permeability constant, is the magnetization, and is the known external magnetic field that satisfies on .
Under the assumption that the magnetization of the ferrofluid flow is parallel to the magnetic field , it follows the nonlinear Langevin magnetization law [23, 24, 17], i.e.,
(4) |
with the saturation magnetization , the Lagevin parameter , the initial susceptibility , , and .
The hydrodynamic properties of the ferrofluid flow are described by the incompressible Navier-Stokes equations
(5) | ||||
(6) |
where denotes the fluid density, the velocity field of the flow, the dynamic viscosity, and the known volume force.
Using the fact that
and the Langevin magnetization law (4), we have
(8) |
where . Denote
(9) |
and introduce two variables
(10) |
and
(11) |
then equation (5) becomes
(12) |
Equation (1) and the boundary condition in (7) imply that (cf. [6]) there exists with
(13) |
then combining (2), (3) and (4) leads to
(14) |
with
(15) |
The above equivalence transformation shows that the FHD model (1) - (6) with the boundary conditions (7) can be equivalently written as follows: Find , , , , , , and such that
(16) |
Remark 2.1.
The system (16) is a decoupled system. Firstly, we can solve the first nonlinear elliptic equation of (16) to get , and solve the Navier-Stokes equations, i.e. the fourth and fifth equations, to get and . Secondly, we can get from the second equation of (16). Finally, we can obtain , , and from the third, the sixth, and the seventh equations, respectively.
2.3. Preliminary estimates for nonlinear functions
Notice that the decoupled system (16) involves the nonlinear functions and defined in (15) and (9), respectively. The following basic estimates of these two functions will be used in later analysis.
Lemma 2.2.
-
(i)
There exist a positive constants and such that for any , there hold
-
(ii)
For any , there holds
Proof.
(i) We first show On one hand, the L’Hopital law implies that
which, together with the fact that
shows
Therefore,
On the other hand, we easily see that
which, together the continuity of for , indicate that there exists a positive constant such that
Second, let us show It is easy to get
The L’Hopital law implies that
Since is continuous for , we know that there exists a positive constant such that
As a result, the conclusions of (i) follow.
(ii) It is easy to find that
with . The L’Hopital law implies that
The fact that
implies that is a monotonically increasing function on the interval . We conclude that
This finishes the proof. ∎
2.4. Weak formulations
Based on the FHD model (16) and Remark 2.1, we consider the following weak formulations: Find , , and such that
(17) | ||||
(18) | ||||
(19) | ||||
(20) |
where is defined by
Remark 2.3.
In what follows, we discuss the existence and uniqueness of the solutions to the weak formulations (17) - (20).
We first consider the nonlinear equation (17). It is easy to see that, for any given , is a bilinear form on . Recall that the Poincaré inequality
with being a constant depending only on , means that the semi-norm is also a norm on . Then, from Lemma 2.2 (i), we easily obtain the following uniform coercivity and continuity results for :
Lemma 2.4.
For any and , we have
and
We have the following wellposedness results for equation (17).
Theorem 2.5.
Proof.
For equation (18), we have the following conclusion:
Theorem 2.6.
For any given , equation (18) admits a unique solution , which means
3. Finite element methods
3.1. Finite element spaces
Let be a quasi-uniform simplicial decomposition of with mesh size , where denotes the diameter of for any .
For an integer , let denote the set of polynomials, defined on , of degree no more than . We introduce the following finite element spaces:
-
•
is the Lagrange element space [13, 9, 14] for the velocity , with for any . In particular, for the nonconforming case that , each is required to satisfy the following conditions:
-
(i)
vanishes at all the nodes on ;
-
(ii)
is a norm.
Note that the classical nonconforming Crouzeix-Raviart (CR) finite element [12] is corresponding to the nonconforming case with . In the nonconforming case, the gradient and divergence operators, and , in the finite element scheme (28) - (29) will be understood as and , respectively, which denote respectively the piecewise gradient and divergence operators acting on element by element in .
-
(i)
-
•
is the piecewise polynomial space for the ‘pressure’ variable , with for any .
-
•
is the Lagrange element space [11] for the new variable , with for any .
- •
In addition, we make the following assumptions for the above finite element spaces.
-
(A1)
There holds the inf-sup condition
(23) where is a constant independent of ;
-
(A2)
The diagram
(24) is a commutative sequence. Here and are the classical interpolation operators, and denotes the gradient operator. Note that the diagram (24) also indicates that
We recall the following inverse inequality:
(25) |
where is a constant independent of .
Remark 3.1.
Remark 3.2.
In this paper, we consider the conforming finite element spaces for the Navier-Stokes equation for simply of notations. In fact the nonconforming finite element spaces which satisfying the inf-sup condition (A1), with replace the global differential operators to element wise, are also work for the Navier-Stokes equations. For example the - finite element spaces are work for the Navier-Stokes equations.
3.2. Finite element scheme
In view of (17)-(20), we consider the following finite element scheme for the FHD model: Find , , and , such that
(26) | |||||
(27) | |||||
(28) | |||||
(29) |
where the trilinear form is defined by
Remark 3.3.
Similar to (17)-(20), the finite element scheme (26) - (29) is a decoupled system. We can first solve the nonlinear equation (26) to get , and solve the Navier-Stokes system (28) - (29) to get and . Then we can get from (27). Finally, we can get , the approximation of the magnetization , from
(30) |
with , get , the approximation of , from
(31) |
and get , the approximation of the pressure , from
(32) |
Remark 3.4.
It is easy to see that the trilinear form is skew-symmetric with respect to the last two variables, i.e.,
(33) |
and that
(34) |
As a result, the following two relations hold:
(35) |
(36) |
Theorem 3.5.
Proof.
Define an operator by
and define by
where is given by
(40) |
Thus, (26) is equivalent to the equation
Lemma 2.4 implies
The definition (40) and the Cauchy-Schwarz inequality imply
Therefore, we have
For any given and , denote . Then for any satisfying , by Lemmas 2.2 and 2.4 we have
This means that is continuous on the set . Notice that Lemma 2.4 implies is continuous at the point . Hence, is continuous on .
Theorem 3.6.
For any given , equation (27) admits a unique solution , which means
Proof.
For any given , assumption (A2) on the finite element spaces implies that . Thus, taking in (27) yields ∎
3.3. Error analysis
In this subsection, we will give some error estimates for the finite element scheme (26) - (29), under some rational assumptions.
Firstly, we have the following error estimate for the discrete solution .
Theorem 3.8.
Proof.
Let be the classical interpolation of , satisfying the estimate
(42) |
where is a constant independent of and .
In light of Theorems 2.6 and 3.6, we know that
Thus, by Theorem 3.8, we immediately get the following error estimate for the discrete solution of (27).
Theorem 3.9.
Theorem 3.10.
As shown in Remark 3.3, for the the magnetization , the new variable , and the pressure , we can obtain their approximations and from (30), (31) and (32), respectively. In view of Theorems 3.9 and 3.10, we easily get the following error estimates for these three approximation solutions.
Corollary 3.11.
Proof.
Equation (30) implies that
where is the orthogonal projection operator. Using the Langevin law (4), we have
Thus, by Lemma 2.2 (i), the boundedness of projection , and the relation , we get
which, together with Theorem 3.9 and the standard error estimation of the projection, gives the desired estimate for .
4. Numerical experiments
This section is devoted to three numerical examples to verify the performance of the mixed finite element methods. In all the examples, we solve the nonlinear system (26) - (32) by using the iFEM package [10] and Algorithm 4.1.
Algorithm 4.1.
Given and , find , , , , , , and through five steps:
Remark 4.2.
From the convergence theory of Newton-type methods [15, 28], we know that the iterative solution of Algorithm 4.1 will converge to the exact solution, provided that the iteration number is big enough and the initial guess is nearby the exact solution. In fact, in all the subsequent numerical examples we choose the initial guess as the corresponding finite element solution of the Poisson equation
with the same boundary condition as that of the exact solution , and choose the initial guess as the corresponding finite element solution of the Stokes equations
with the same boundary condition as that of the exact solution . In so doing, the choice works well in the algorithm.

Example 4.3.
This is a 2D test. We take , and use uniform triangular mesh (cf. Figure 1) with . The exact solution of the FHD model (16) is given by
with the parameters , , , and all being chosen as .
We use the conforming linear () element to discretize the variable , the lowest order edge element to discretize the variables and , the (nonconforming-) element to discretize the variables , and the piecewise constant () element to discretize the variables , and . Note that such a combination of finite element spaces corresponds to , then we easily see from Theorems 3.8 - 3.10 and Corollary 3.11 that the theoretical accuracy of the scheme is . Numerical results are listed in Table 1.
order | – |

The other two experiments, Examples 4.4 and 4.5, are 3D tests, with and use uniform tetrahedral meshes (cf. Figure 2) with .
Example 4.4 (The lowest order approximation).
In this 3D test, the exact solution of the FHD model (16) is given by
with the parameters , , and all being choosen as and .
We use the the conforming -element to discretize the variable , the lowest order Nédélec finite element space [18, 19] to discretize the variables and , the nonconforming element [12] to discretize the variable , and the piecewise constant element to discretize the variables , and . With these settings, from Theorems 3.8 - 3.10 and Corollary 3.11 we see that the theoretical accuracy of the scheme is . Numerical results are given in Table 2.
order |
Example 4.5 (A higher order approximation).
In this 3D test, the exact solution of the FHD model (16) is given by
where the parameters , , , and are all choosen as .
We use the conforming quadratic () element to discretize the variable , the first order Nédélec edge element [18, 19] to discretize the variables and , the Taylor-Hood - element to discretize the variables and , and the continuous linear () element to discretize the variables and . With these settings, we see that the theoretical accuracy of the scheme is . We list numerical results in Table 3.
order |
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