The Effects of Chemical Reaction, Hall, and Ion-Slip Currents on MHD Micropolar Fluid Flow with Thermal Diffusivity Using a Novel Numerical Technique

Abstract

The problem of magnetomicropolar fluid flow, heat, and mass transfer with suction through a porous medium is numerically analyzed. The problem was studied under the effects of chemical reaction, Hall, ion-slip currents, and variable thermal diffusivity. The governing fundamental conservation equations of mass, momentum, angular momentum, energy, and concentration are converted into a system of nonlinear ordinary differential equations by means of similarity transformation. The resulting system of coupled nonlinear ordinary differential equations is the then solved using a fairly new technique known as the successive linearization method together with the Chebyshev collocation method. A parametric study illustrating the influence of the magnetic strength, Hall and ion-slip currents, Eckert number, chemical reaction and permeability on the Nusselt and Sherwood numbers, skin friction coefficients, velocities, temperature, and concentration was carried out.

1. Introduction

Eringen [1] proposed the theory of micropolar fluids, which shows microrotation effects as well as microinertia, as these flow properties cannot be described by the classical Navier-Stokes theory. Since the pioneering work by Eringen, the theory of micropolar fluid has generated a lot of interest. Extension has been done, to include studies of magneto-micropolar fluid with Hall current and ion-slip currents with heat transfer due to vast possible engineering applications in areas like power generators, MHD accelerators, refrigeration coils, electric transformers, and heating elements. MHD flows of a viscous and incompressible fluid have been extensively studied with the effect of Hall current by Chamkha [2], Seddeek [3], Takhar et al. [4], Shateyi et al. [5, 6], Salem and Abd El-aziz [7], among others.

The momentum, heat, and mass transport on stretching sheet has several applications in polymer processing as well as in electrochemistry. The heat transfer problem associated with the boundary layer micropolar fluid under different physical conditions has been studied by several authors. Takhar et al. [8] considered diffusion of a chemical reactive species from a stretching sheet. Muthucumaraswamy and Ganesan [9] studied diffusion and first-order chemical reaction on impulsively started infinite vertical plate with variable temperature. Shateyi [10] investigated thermal radiation and buoyancy effects on heat and mass transfer over a semi-infinite stretching sheet with suction and blowing. Shateyi and Motsa [11] numerically investigated the unsteady heat, mass, and fluid transfer over a horizontal stretching sheet.

The porous media heat and mass transfer problems have several practical engineering applications such as geothermal systems, crude oil extraction, and ground-water pollution. The study of chemical reaction heat transfer in porous medium has important applications such as in tabular reactors, oxidation of solid materials, and synthesis of ceramic materials. Elgazery [12] numerically analyzed the effects of chemical reaction, Hall, ion-slip currents, variable viscosity and variable thermal diffusivity on the problem of magnetomicropolar fluid flow, heat and mass transfer with suction and blowing through a porous medium. Srinivasacharya and RamReddy [13] presented natural convection heat and mass transfer along a vertical plate embedded in a doubly stratified micropolar fluid saturated non-Darcy porous medium. Ishak et al. [14] investigated the unsteady boundary layer flow over a stretching permeable surface.

Elshehawey et al. [15] applied the Chebyshev finite-difference method to investigate the effects of Hall and ion-slip currents on magneto-hydrodynamic flow with variable thermal conductivity. Seddeek and Salama [16]. studied effects of chemical reaction and variable viscosity on hydromagnetic mixed convection heat and mass transfer for Hiemenz flow through porous media with radiation. Shateyi and Motsa [17] analyzed numerically the problem of magnetohydrodynamic flow and heat transfer of a viscous, incompressible and electrically conducting fluid past a semi-infinite unsteady stretching sheet with Hall currents, variable viscosity and thermal diffusivity. Mahmoud and Waheed [18] performed a theoretical analysis to study heat transfer characteristics of magnetohydrodynamic mixed convection flow of a micropolar fluid past a stretching surface with slip velocity at the surface and heat generation/absorption.

The aim of this work is to analyze the effects of chemical reaction, Hall and ion-slip currents on the MHD flow of a micropolar fluid through a porous medium using the successive linearization method (SLM). The SLM is based on a novel idea of iteratively linearizing the underlying governing nonlinear equations, which are written in similarity form, and solving the resulting equations using spectral methods. This approach has been successfully applied to different flow problem (see, e.g., Makukula et al. [19–22]; Shateyi and Motsa [17]; Motsa and Shateyi [23, 24]). The influences of the governing parameters on the flow characteristics are illustrated graphically and using tables.

2. Problem Formulation

We consider a steady, incompressible, magneto-micropolar and electrically conducting viscous fluid flowing over a horizontal plate in the -direction under the influence of mass transfer with chemical reaction through a porous medium. We let the reaction of a species, say with be the first order homogeneous chemical reaction with a constant rate, . We also assume that the concentration of dissolved is small enough and physical properties and are virtually constant throughout the fluid. The flow under consideration is also subjected to a strong transverse magnetic field with a constant intensity along the -axis (see Figure 1).

Figure 1 

The physical configuration and coordinate system for the boundary layer flow.

Generally, an electrically conducting fluid is affected by Hall and ion-slip currents in the presence of a magnetic field. The effect of Hall current gives rise to a force in the -direction, which induces a cross-flow in the -direction and hence the flow becomes three-dimensional.

Following Elgazery [12], the generalized Ohms law including Hall currents is given bywhere is the electrical conductivity, is the electric current vector, is the velocity vector, is the intensity of the electric field, is the magnetic induction vector, is the Hall factor, is the Hall parameter, is the density number of the electrons, is the charge of electron, is the electron-atom collision frequency and exceeds the collision frequency. The electric magnetic field can force both the ions and electrons to produce a relative drift between them and neutral particles, when the ratio, becomes very large. The drift is called “ion-slip” and is however negligible for highly ionized gases.

We assume that all the fluid properties are isotropic and constant. The velocity component on a stretching sheet is proportional to its distance from the slit. Under the usual boundary layer and Boussinesq approximations, the governing equation in -coordinate for the problem under consideration can be written as follows: The boundary conditions are Here are the fluid velocity components in the -directions, respectively. is the fluid density, is the dynamic viscosity, the specific heat at constant pressure, the coefficient of thermal expansion, the coefficient of concentration expansion, , and the fluid free stream velocity, temperature, and concentration, respectively, is the component of microrotation of the fluid, is the vortex viscosity, is the spin gradient viscosity. and permeability of the porous medium. and are respectively, the Hall parameter and the ion-slip parameter, where . is a constant with dimension . is the surface velocity and is suction/injection velocity, is the kinematic viscosity, is the chemical molecular diffusivity, is the thermal diffusivity, is the chemical reaction, and is the magnetic field of constant strength.

The governing differential equations (2.2)–(2.7) together with the boundary conditions (2.8) are non-dimensionalised using the following similarity transformations: where and are the dimensionless stream function and microrotation functions, temperature, and concentration distributions functions, respectively. is the similarity variable. The variation of thermal diffusivity with the dimensionless temperature is written in the form: where is parameter depending on the nature of the fluid, and is the thermal diffusivity of the fluid at temperature . Then introducing the relations (2.9) into the equations (2.3)–(2.7) respectively, we obtain the following local similarity equations: where the primes denote differentiation with respect to is the magnetic parameter, is the coupling constant parameter, is the microrotation parameter, is the Prandtl number, is the Schmidt number, is the Eckert number, is the permeability parameter, , is the Reynolds number, is the nondimensional chemical reaction parameter. In view of the similarity transformations, the boundary conditions transform into: where is the mass transfer coefficient such that indicates suction and indicates blowing at the surface.

For practical applications, quantities of interest include the velocity components and , temperature and concentration, the local skin friction coefficients and , the local Nusselt number , and the local Sherwood number , where and are the shear stress at the wall. By using (2.9), these quantities can be expressed as:

3. Generalization of the Successive Linearisation Method (SLM)

In this section we describe the basic idea behind the proposed method of successive linearisation method (SLM) and we derive formulas that can be used to implement the generalized SLM in any system of nonlinear boundary value problems. We consider a general -order nonlinear system of ordinary differential equations which is represented by the nonlinear boundary value problem of the form where is a vector of unknown functions, is an independent variable, and the primes denote ordinary differentiation with respect to . The functions and are vector functions which represent the linear and nonlinear components of the governing system of equations, respectively, defined by where are the unknown functions. We define an initial guess of the solution of (3.1) as For illustrative purposes, we assume that (3.1) is to be solved for subject to the boundary conditions where and are given constants. In previous implementation of the SLM (see, e.g., [19–25]) an appropriate initial guess was considered to be functions that satisfy the governing boundary conditions of (3.1). The general approach proposed in this study assumes that the initial approximation is a solution of the equation which is solved subject to the underlying problem’s boundary conditions.

Define a function to represent the vertical difference between and the initial guess , that is, For example, the vertical displacement between the variable and its corresponding initial guess is . This is shown in Figure 2.

Figure 2 

Geometric representation of the function .

Substituting (3.6) in (3.1) gives Since is an known function, solving (3.7) would yield an exact solution for . However, since the equation is nonlinear, it may not be possible to find an exact solution. We therefore look for an approximate solution which is obtained by solving the linear part of the equation assuming that and its derivatives are small. This assumption enables us to use the Taylor series method to linearise the equation. If is the solution of the full equation (3.7) we let denote the solution of the linearised version of (3.7). Expanding (3.7) using Taylor series (assuming ) and neglecting higher order terms gives The partial derivatives inside square brackets in (3.8) represent Jacobian matrices of size , defined as where and is the order of the derivatives.

Since the right hand side of (3.8) is known and the left hand side is linear, the equation can be solved for . Assuming that the solution of the linear part (3.8) is close to the solution of (3.7), that is, , the current estimate (1st order) of the solution is To improve on this solution, we define a slack function, , which when added to gives (see, e.g., Figure 3), that is Since is now known (as a solution of (3.8) ), we substitute (3.11) in (3.7) to obtain Solving (3.12) would result in an exact solution for . But since the equation is nonlinear, it may not be possible to find an exact solution. We therefore linearise the equation using Taylor series expansion and solve the resulting linear equation. We denote the solution of the linear version of (3.12) by , such that . Setting and expanding (3.12), for small and its derivatives gives where the partial derivatives inside square brackets in (3.13) represent Jacobian matrices defined as in (3.9) with .

Figure 3 

Geometric representation of the functions .

After solving (3.13), the current (2nd-order) estimate of the solution is Next we define (see Figure 4) such that Equation (3.15) is substituted in the nonlinear (3.12) and the linearisation process described above is repeated. This process is repeated for . In general, we have Thus, is obtained as The procedure for obtaining each is illustrated in Figures 2, 3, and 4, respectively, for .

Figure 4 

Geometric representation of the functions .

We note that when becomes large, becomes increasingly smaller. Thus, for large , we can approximate the th-order solution of by Starting from a known initial guess , the solutions for can be obtained by successively linearising the governing equation (3.1) and solving the resulting linear equation for given that the previous guess is known. The general form of the linearised equation that is successively solved for is given by where

4. Numerical Solution

In this section we solve the governing (2.11)–(2.15) using the SLM method described in the last section. We note that (2.11)–(2.13) can be solved independently of equations (2.14)–(2.15). We begin by using the SLM approach to solve for and . We write the governing equations (2.11)–(2.13) as a sum of the linear and nonlinear components as where the primes denote differentiation with respect to and Using (3.19), the general equation to be solved for , where is subject to the boundary conditions where and the sums in (4.6) denote . Once each solution for , , () has been found from iteratively solving equations (4.4)–(4.5), the approximate solutions for , , and are obtained as where is the order of SLM approximation. Since the coefficient parameters and the right hand side of (4.4)), for , are known (from previous iterations). The equation system is solved using the Chebyshev spectral collocation method. This method is based on approximating the unknown functions by the Chebyshev interpolating polynomials in such a way that they are collocated at the Gauss-Lobatto points defined as where is the number of collocation points used (see, e.g., [26–28]). In order to implement the method, the physical region is transformed into the region using the domain truncation technique in which the problem is solved on the interval instead of . This leads to the mapping where is the scaling parameter used to invoke the boundary condition at infinity. The unknown functions , and are approximated at the collocation points by where is the th Chebyshev polynomial defined as The derivatives of the variables at the collocation points are represented as where is the order of differentiation and with being the Chebyshev spectral differentiation matrix (see, e.g., [26, 28]). Substituting (4.9)–(4.12) in (4.4))–((4.5) leads to the matrix equation given as subject to the boundary conditions where and and are column vectors defined by where In the above definitions, , () are now diagonal matrices of size and the superscript is the transpose.