Abstract
We study the effect of thermophoresis on boundary layer magnetonanofluid flow over a stretching sheet. The model includes the effects of Brownian motion and crossdiffusion effects. The governing partial differential equations are transformed to a system of ordinary differential equations and solved numerically using a spectral linearisation method. The effects of the magnetic influence number, the Prandtl number, Lewis number, the Brownian motion parameter, thermophoresis parameter, the modified Dufour parameter and the Dufoursolutal Lewis number on the fluid properties as well as on the heat, regular and nano mass transfer coefficients are determined and shown graphically.
1 Introduction
Most common fluids such as water, ethylene, glycol, toluene or oil generally have poor heat transfer characteristics owing to their low thermal conductivity. A recent technique to improve the thermal conductivity of these fluids is to suspend nanosized metallic particles such as aluminum, titanium, gold, copper, iron or their oxides in the fluid to enhance its thermal properties, Choi [1]. The enhancement of thermal conductivity in nanofluids has been studied by, among others, Kakac and Pramuanjaroenkij [2], Choi et al.[3], Masuda et al.[4], Eapen et al.[5] and Fan and Wang [6]. Nield and Kuznetsov [7] analyzed the behaviour of boundary layer flow on the ChenMinkowycz problem in a porous layer saturated with a nanofluid. Nield and Kuznetsov [8] investigated thermal instability in a porous medium saturated with nanofluid using the Brinkman model. The model incorporated the effects of Brownian motion and thermophoresis of nanoparticles. They found that the critical thermal Rayleigh number can be reduced or increased by a substantial amount depending on whether the nanoparticle distribution is topheavy or bottomheavy. Aziz et al.[9] studied steady boundary layer flow past a horizontal flat plate embedded in a porous medium filled with a waterbased nanofluid containing gyrotactic microorganisms. Cheng [10] investigated the behaviour of boundary layer flow over a horizontal cylinder of elliptic cross section in a porous medium saturated with a nanofluid. Chamkha et al.[11] investigated the nonsimilar solutions for natural convective boundary layer flow over a sphere embedded in a porous medium saturated with a nanofluid.
During the last few decades, fluid flow over a stretching surface has received considerable attention because of its engineering applications such as in meltspinning, hot rolling, wire drawing, glassfiber production and the manufacture of polymer and rubber sheets, Altan and Gegel [12], Fisher [13], and Tidmore and Klein [14]. Nanofluid flow over a stretching surface has been investigated by many researchers. The first study on a stretching sheet in nanofluids was published by Khan and Pop [15]. Makinde and Aziz [16] performed a numerical study of boundary layer flow over a linear stretching sheet. Both Brownian motion and thermophoresis effects on the transport equations were presented. They reported that stronger Brownian motion and thermophoresis lead to an increase in the rate of heat transfer. However, the opposite was observed in the case of the rate of mass transfer. Recent studies in this area include those of Narayana and Sibanda [17] and Kameswaran et al.[18].
Magnetic nanofluids have numerous uses or potential applications in engineering and medicine. Using magnetic nanofluids has the potential to regulate the flow rate and heat transfer by controlling the thermomagnetic convection current and the fluid velocity (see Shima et al.[19], Ganguly et al.[20]). The effects of a magnetic field on nanofluid flow over a stretching sheet have been investigated by, among others, Bachok et al.[21] and Hanad and Ferdows [22].
The aim of this study is to analyse Dufour and Soret effects in a magnetonanofluid flow over a stretching sheet. In addition, we study Brownian motion and thermophoresis effects using a spectral linearisation method to obtain numerical solutions of the momentum, energy, concentration and mass fraction equations. The successive linearisation method (SLM) is an accurate method for solving nonlinear coupled equations (see [2325]). Recent studies such as [2628] have suggested that the SLM is accurate and converges rapidly to the numerical results when compared to other semianalytical methods such as the Adomian decomposition method, the variational iteration method and the homotopy perturbation method.
2 Mathematical formulation
Consider twodimensional nanofluid flow over a linearly stretching sheet with velocity
with the boundary conditions
where u and v are the velocity components along the x and y direction respectively, σ is the electrical conductivity,
equations (1)(5) reduce to the following nonsimilar forms where primes denote differentiation with respect to η:
subject to the boundary conditions
The parameters in equations (8)(11) are the magnetic number M, the Prandtl number Pr, the Lewis number Le, the Brownian motion parameter Nb, the thermophoresis parameter Nt, the nanofluid Lewis number Ln, the modified Dufour parameter Nd and the Dufoursolutal Lewis number Ld. These parameters are defined as
The parameters of engineering interest in heat and mass transport problems are the
local Nusselt number
Following Khan and Aziz [29], the physical parameters of interest are the reduced Nusselt Nur, the Sherwood number
3 Method of solution
The system of equations (8)(11) together with the boundary conditions (12) were solved
using the successive linearisation method (SLM) (see [25,26,30]). The unknown functions
where
subject to the boundary conditions
where coefficient parameters
and are chosen as
Starting from the initial guesses and iterating
where
We discretise the domain
where N is the number of collocation points used. The functions
where
The derivatives of the variables evaluated at the collocation points
where r is the order of differentiation and
Substituting equations (22)(26) into equations (14)(17) leads to the matrix equation
where
The functions and parameters in equation (29) are
In the definitions above, T stands for transpose,
4 Results and discussion
In this section we present solutions of equations (8)(11) along with the boundary
conditions (12) using the SLM iteration scheme. Tables 1 and 2 give a comparison between the present results and Khan and Pop [15] for the reduced Nusselt and Sherwood numbers respectively. There is a good agreement
between the two sets of results with the SLM having converged at the fourth order
up to eleven decimal places. The velocity components
Figure 1
. Effect of the magnetic fieldMon the velocity components (a)
Table 1
. Comparison of results for the reduced Nusselt number
Table 2
. Comparison of results for the reduced Sherwood number
Figures 2(a) and 2(b) show the effect of the thermophoresis parameter on the temperature and mass volume fraction profiles. The thermophoretic force generated by the temperature gradient creates a fast flow away from the stretching surface. In this way more fluid is heated away from the surface, and consequently, as Nt increases, the temperature within the boundary layer increases. The fast flow from the stretching sheet carries with it nanoparticles leading to an increase in the mass volume fraction boundary layer thickness.
Figure 2 . Effect of the thermophoresis parameterNton the temperatureθand nanoparticleϕprofiles.
Figures 3(a) and 3(b) show the effect of the Lewis number Le, and the Dufoursolutal Lewis number Ld on the species concentration in the boundary layer. The concentration profiles significantly contract as the Lewis number increases. The effect of the random motion of the nanoparticles suspended in the fluid on the temperature and nanoparticle volume fraction is shown in Figures 4(a) and 4(b). As expected, the increased Brownian motion of the nanoparticles carries with it heat and the thickness of the thermal boundary layer increases. The Brownian motion of the nanoparticles increases thermal transport which is an important mechanism for the enhancement of thermal conductivity of nanofluids. However, we note that increasing the Brownian motion parameter leads to a clustering of the nanoparticles near the stretching sheet. An increase in the Brownian motion of the nanoparticles leads to a decrease in the mass volume fraction profiles.
Figure 3 . Effect of the Lewis numberLeand the Dufoursolutal Lewis numberLdon concentration profiles.
Figure 4 . Effect of the Brownian motion parameterNbon the temperature and nanoparticle volume fraction profiles.
Figures 5(a) and 5(b) show the temperature profiles for several values of the Prandtl number Pr and mass volume fraction profile for several values of the modified Dufour number Nd. The temperature profiles decrease as the Prandtl number increases since, for high Prandtl numbers, the flow is governed by momentum and viscous diffusion rather than thermal diffusion. On the other hand, the thickness of the mass volume fraction boundary layer increases with an increase in Nd.
Figure 5 . Effect ofPrandNdon the temperatureθ, profiles respectively.
Figures 6(a) and 6(b) show the effects of the thermophoresis parameter Nt, the Lewis number Le, the magnetic field parameter M, the Prandtl number Pr and the modified Dufour number Nd on the wall heat and mass fraction transfer rates. It can be seen that the thermal boundary layer thickness increases when the thermophoresis parameter Nt increases, thus decreasing the reduced Nusselt number. However, increasing the Lewis number Le leads to a decrease in the reduced Nusselt number. On the other hand, the results show that the reduced Nusselt number increases with increasing Prandtl numbers. Increasing both the magnetic field parameter M and the modified Dufour parameter Nd leads to an increase in the thermal boundary layer thickness, thus reducing the Nusselt number.
Figure 6 . Effect ofNt,Le,Pr,NdandMon the heat transfer coefficientNur.
Figures 7(a) and 7(b) show the effects of the Dufoursolutal Lewis number Ld and the nanofluid Lewis number Ln on the reduced Nusselt number Nur as the Brownian motion parameter Nb increases. We note a decrease in the reduced Nusselt number when Ln increases, and an increase in the reduced Nusselt number when Ld increases.
Figure 7 . Effect of the Dufoursolutal Lewis numberLdand the nanofluid Lewis numberLnon the reduced Nusselt numberNur.
Figures 8(a) and 8(b) show the graphs of
Figure 8
. Effect of the Lewis numberLe, the thermophoresis parameterNtand the Brownian motion parameterNbon (a) the reduced Nusselt number
Figure 9
. Effect of the nanofluid Lewis numberLn, the thermophoresis parameterNtand the Brownian motion parameterNbon the nanofluid Sherwood number
5 Conclusions
A numerical study of the magnetonanofluid boundary layer flow over a stretching sheet was carried out. We determined the effects of various parameters on the fluid properties as well as on the heat, and the regular and nano mass transfer rates. We have shown that increasing the magnetic field parameter M tends to retard the fluid flow within the boundary layer. The effects of the Prandtl number, the Lewis number, the Brownian motion parameter, the thermophoresis parameter, the nanofluid Lewis number, the modified Dufour parameter and the Dufoursolutal Lewis number on the heat, regular and nano mass transfer coefficients and fluid flow characteristics have been studied. We have shown inter alia that:
– the thermal boundary layer thickness increases with the thermophoresis parameter;
– increasing the Lewis number reduces the heat transfer coefficient;
– the heat transfer coefficient increases in the absence of the Brownian motion and the thermophoresis parameter and decreases in the presence of Brownian motion and thermophoresis parameters.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
The work including proofreading was done by all the authors.
Acknowledgements
The authors wish to thank the University of KwaZuluNatal for financial support.
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