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Journal of Engineering
Volume 2014, Article ID 137426, 6 pages
http://dx.doi.org/10.1155/2014/137426
Research Article

Free Convection in Heat Transfer Flow over a Moving Sheet in Alumina Water Nanofluid

Department of Mathematics, Statistics and Computer Science, G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand 263145, India

Received 24 May 2014; Accepted 4 October 2014; Published 2 November 2014

Academic Editor: Oronzio Manca

Copyright © 2014 Padam Singh and Manoj Kumar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The present paper deals with study of free convection in two-dimensional magnetohydrodynamic (MHD) boundary layer flow of an incompressible, viscous, electrically conducting, and steady nanofluid. The governing equations representing fluid flow are transformed into a set of simultaneous ordinary differential equations by using appropriate similarity transformation. The equations thus obtained have been solved numerically using adaptive Runge-Kutta method with shooting technique. The effects of physical parameters like magnetic parameter, temperature buoyancy parameter on relative velocity and temperature distribution profile, shear stress profile, and temperature gradient profile were depicted graphically and analyzed. Significant changes were observed due to these parameters in velocity and temperature profiles.

1. Introduction

Applications of heat transfer through moving material in a moving fluid medium have wide range of applications in real world. Various researchers studied the concepts of moving sheet in a flowing fluid medium. Numerical and analytical solution for momentum and energy in laminar boundary layer flow over continuously moving sheet was discussed by Zheng and Zhang [1]. The authors found that the effect of velocity ratio parameter and other parameters on heat transfer were significant. Al-Sanea [2] studied the flow and thermal characteristic of a moving vertical sheet of extruded material close to and far downstream from the extrusion slot. Regimes of forced, mixed, and natural convection have been delineated, in buoyancy flow, as a function of Reynolds and thermal Grashof numbers for various values of Prandtl number and buoyancy parameter. Seddeek [3] analyzed the effect of magnetic field on the flow of micropolar fluid past a continuously moving plate. Patel et al. [4] suggested a new model for thermal conductivity of nanofluids which is found to agree excellently with a wide range of experimental published data. The momentum and heat transfer flow of an incompressible laminar fluid past a moving sheet based on composite reference velocity was studied by Cortell [5]. The author found that the direction of the wall shear stress changes in such an interval and an increase of the relative velocity parameter yields an increase in temperature. Ishak et al. [6] studied the magnetohydrodynamic boundary layer flow due to a moving extensible surface. It was found that the dual solutions exist for the flow near -axis, where the velocity profiles show a reversed flow. Bachok et al. [7] investigated steady, laminar boundary layer flow of a nanofluid past a moving semi infinite flat plate. The results indicate that dual solutions exist when the plate and the free stream move in the opposite directions. Habib and El-Zahar [8] proposed a model for determining the heat transfer between a moving sheet and flowing fluid. The authors found that the heat transfer depends on the relative velocity between the moving fluid and the moving sheet to certain values. Energy conversion for conjugate convection, conduction, and radiation analysis have been performed for free convective heat transfer with radiation by Hsiao [9]. The results show that the free convection effect will produce a larger heat transfer effect better than the forced convection. Raguraman et al. [10] investigated the effects of some important design parameters for coal-water slurry in agitated vessel used in coal gasification such as stirrer speed, location of stirrer, ratio, and coal-water ratio. Confirmation test verified that the Taguchi method achieved optimization of heat transfer coefficient in agitated vessel. The objective of the present study is to analyze the effect of magnetic field and temperature buoyancy effect on the heat transfer flow between a moving sheet and moving alumina water nanofluid environment. Hsiao [11, 12] studied two-dimensional conjugate heat transfer with Ohmic dissipation mixed convection of an incompressible Maxwell fluid on a stagnation point and also investigated energy conversion problems of conjugate conduction, convection, and radiation heat and mass transfer with viscous dissipation and magnetic effects. The results have shown that it should produce greater heat transfer effect with larger values of Prandtl number, free convection parameter, and conduction-convection number. On the other hand, the Eckert number and magnetic parameter will reduce the heat transfer effect. For heat convection energy conversion aspect, some importance parameters applied to the system, such as buoyancy parameters, radiative energy parameter, boundary proportional parameter, and Prandtl number which can produce positive effects for larger values of those parameters. Idusuyi et al. [13] formulated a computational model for the heat generation and dissipation in a disk brake during braking and the following release period. The results show similarity in thermal behaviour at the contact surface for the asbestos and aramid brake pad materials with a temperature difference of 1.8 K after 10 seconds.

The objective of the present study is to analyze the effect of magnetic field and temperature buoyancy effect on the heat transfer flow between a moving sheet and moving alumina water nanofluid environment.

2. Mathematical Description

The graphical model of the problem considered has been given to depict the flow configuration and coordinate system. The system deals with two-dimensional MHD boundary layer, incompressible, viscous, electrically conducting, and steady fluid flow (Figure 1). The governing equations representing flow are the following: where and are the velocity components in and direction, respectively, , , , and are the kinematic viscosity, thermal expansion coefficient, density, electrical conductivity, and thermal diffusivity of the nanofluid. is the gravitational acceleration and , , and are the temperature of the nanofluid inside the thermal boundary layer, the plate temperature, and the nanofluid temperature at free stream, respectively. denotes the magnetic field imposed in the transverse direction to the fluid.

137426.fig.001
Figure 1: Flow configuration and coordinate system.

The appropriate boundary conditions for the abovementioned problem are as follows (Table 1):

tab1
Table 1: Nanofluid properties.

3. Method for Solution

To solve the governing equations (1), (2), and (3) with the boundary conditions (4), the following similarity transformation has been introduced: Here and are free stream velocity and moving sheet velocity, respectively. is the stream function which satisfies (1) with and . Thus, (5) gives Now using (5) and (6) in (2) and (3), we get the following nonlinear differential equations: the boundary conditions (4) will become where represent the state of moving surface in stationary fluid and is the condition of moving surface in moving fluid with . The dimensionless parameters introduced in (7) are defined as follows.

is the magnetic parameter, is the local temperature Grashof number, is the local Reynolds number, is the temperature buoyancy parameter, is the Prandtl number, and is the relative velocity parameter.

To solve the set of nonlinear differential equations (7) with subject to the boundary conditions (8), adaptive Runge-Kutta method with shooting technique has been applied. This method is based on the discretization of the problem domain and the calculation of unknown boundary conditions. The domain of the problem is discretized and the boundary conditions for are replaced by , and where is sufficiently large value of comparing to step size at which the boundary conditions (8) for and are satisfied. On account of the consistency and to fulfill stability criteria and step size have been taken. To solve the problem the nonlinear equations (7) are first converted into first order ordinary linear differential equations as follows: There are three conditions on the boundary and two conditions at as given in (8). Shooting technique has been used to find required missing initial conditions. The value of unknowns and has been tabulated in Table 2. Adaptive Runge-Kutta method estimates the truncation error at each integration step and automatically adjusts the step size to keep the error within prescribed limits. The formula used to measure the actual conservative error is defined by ; here is the measure of error in the dependent variable . Per-step error control is achieved by adjusting the increment by ,  , so that it is approximately equal to the prescribed tolerance . The assumed initial step size is .

tab2
Table 2: Values of and for and obtained by shooting method.

4. Result and Discussion

The computations have been made for velocity, shear stress, concentration, and concentration gradient profiles corresponding to fixed values of magnetic parameter (), α, and temperature buoyancy parameter . The value of is taken corresponding to 0.05 volume fraction of the alumina water nanofluid at 20°C. The parameter has been introduced to represent the temperature buoyancy effect on flow field. Figures 26 exhibit the velocity, shear stress, concentration, and concentration gradient profiles, respectively, for various values of magnetic parameter (i.e., , 0.2, 0.5, 1, 3). It is noticed that in Figures 2 and 3 that the velocity decreases and the shear stress decreases up to (2.93290777, −0.0311476673) and then increases with an increase in the magnetic parameter. The temperature increases with an increase in the magnetic parameter; temperature gradient increases up to (0.524497748, −0.835081441) and then decreases with an increment in the values of magnetic parameter as shown in Figures 4 and 5. Figures 6 and 7 show the effect of convection parameter on velocity, shear stress, concentration, and concentration gradient profiles, respectively, for . It has been observed that the velocity increases with an increase in the convection parameter as shown in Figure 6, and shear stress increases up to (0.433856945, −1.03343467) with an increase in the convection parameter and then decreases as shown in Figure 7. The effect of convection parameter on temperature gradient and temperature also has been studied through Figures 8 and 9. It is noticed that the temperature and temperature gradient show significant changes with an increase in the temperature buoyancy parameter.

137426.fig.002
Figure 2: Effect of magnetic parameter on velocity.
137426.fig.003
Figure 3: Effect of magnetic parameter on shear stress.
137426.fig.004
Figure 4: Effect of magnetic parameter on temperature.
137426.fig.005
Figure 5: Effect of magnetic parameter on temperature gradient.
137426.fig.006
Figure 6: Effect of temperature buoyancy parameter on velocity.
137426.fig.007
Figure 7: Effect of temperature buoyancy parameter on shear stress.
137426.fig.008
Figure 8: Effect of temperature buoyancy parameter on temperature gradient.
137426.fig.009
Figure 9: Effect of temperature buoyancy parameter on temperature.

5. Conclusion

Free convective heat transfer in an electronically conducting nanofluid over a moving sheet with magnetic field is considered. The nonlinear partial differential equations are transformed into a system of nonlinear ordinary differential equations by using similarity transformation and then solved numerically using the Runge-Kutta fifth order method along with the shooting technique. From the numerical calculations of the skin friction coefficient and wall shear stresses the following is concluded.(i)An increase in magnetic parameter decreases the velocity and wall shear stress but enhances the temperature, skin friction coefficient. The shear stress decrease up to a fixed value of magnetic parameter and after that goes to increases. For the magnetic parameter, temperature gradient shows the opposite behaviour to the shear stress.(ii)As the temperature buoyancy parameter increases, it increases the velocity, wall shear stress and decreases skin friction coefficient and temperature gradient.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

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