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Magnetite Molybdenum Disulphide Nanofluid of Grade Two: A Generalized Model with Caputo-Fabrizio Derivative

Written By

Farhad Ali, Madeha Gohar, Ilyas Khan, Nadeem Ahmad Sheikh, Syed Aftab Alam Jan and Muhammad Saqib

Submitted: 09 October 2017 Reviewed: 01 December 2017 Published: 22 August 2018

DOI: 10.5772/intechopen.72863

From the Edited Volume

Microfluidics and Nanofluidics

Edited by Mohsen Sheikholeslami Kandelousi

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Abstract

Heat and mass transfer analysis in magnetite molybdenum disulphide nanofluid of grade two is studied. MoS2 powder with each particle of nanosize is dissolved in engine oil chosen as base fluid. A generalized form of grade-two model is considered with fractional order derivatives of Caputo and Fabrizio. The fluid over vertically oscillating plate is subjected to isothermal temperate and species concentration. The problem is modeled in terms of partial differential equations with sufficient initial conditions and boundary conditions. Fractional form of Laplace transform is used and exact solutions in closed form are determined for velocity field, temperature and concentration distributions. These solutions are then plotted for embedded parameters and discussed. Results for the physical quantities of interest (skin friction coefficient, Nusselt number and Sherwood number) are computed in tables. Results obtained in this work are compared with some published results from the open literature.

Keywords

  • Caputo-Fabrizio approach
  • MHD
  • nanofluid
  • generalized second-grade fluid
  • exact solutions

1. Introduction

The idea of fractional order calculus is as old as traditional order calculus. The pioneering systematic studies are devoted to Riemann-Liouville and Leibniz [1]. The subject is growing day by day and its applications have been utilized in different fields, for example, viscoelasticity, bioengineering, biophysics and mechatronics [2]. The applications of non-integer order calculus have also been encountered in different areas of science despite mathematics and physics drastically [3, 4, 5]. In fluid dynamics, the fractional order calculus has been broadly used to describe the viscoelastic behaviour of the material. Viscoelasticity of a material is defined it deforms evince both viscous and elastic behaviour via storage of mechanical energy and simultaneous behaviour. Mainardi [6] examined the connections among fractional calculus, wave motion and viscoelasticity. It is increasingly seen as an efficient tool through which useful generalization of physical concepts can be obtained. Hayat et al. [7] studied the periodic unidirectional flows of a viscoelastic fluid with the Maxwell model (fractional). Qi and Jin [8] analyzed the unsteady rotating flows of viscoelastic fluid with the fractional Maxwell model between coaxial cylinders. Many other researchers used the idea of fractional calculus and published quite number of research papers in some reputable journals [9, 10, 11].

Several versions of fractional derivatives are now available in the literature; however, the widely used derivatives are the Riemann-Liouville fractional derivatives and Caputo/fractional derivative [12, 13]. However, the researchers were facing quite number of difficulties in using them. For example, the Riemann-Liouville derivative of a constant is not zero and the Laplace transform of Riemann-Liouville derivative contains terms without physical significance. Though the Caputo fractional derivative has eliminated the short fall of Riemann-Liouville derivative, its kernal has singularity point. Ali et al. [14] reported the conjugate effect of heat and mass transfer on time fraction convective flow of Brinkman type fluid using the Caputo approach. Shahid et al. [15] investigated the approach of Caputo fractional derivatives to study the magnetohyrodynamic (MHD) flow past over an oscillating vertical plate along with heat and mass transfer. Recently, Caputo and Fabrizio (CF) have initiated a fractional derivative with no singular kernel [16]. However, Shah and Khan [17] analyzed that heat transfer analysis in a grade-two fluid over an oscillating vertical plate by using CF derivatives. Ali et al. [18] studied the application of CF derivative to MHD free convection flow of generalized Walter’s-B fluid model. Recently, Sheikh et al. [19] applied CF derivatives to MHD flow of a regular second-grade fluid together with radiative heat transfer.

However, the idea of fractional calculus is very new in nanoscience, particularly in nanofluid also called smart fluid [20]. In this study, we have applied the fractional calculus idea more exactly, the idea of CF derivatives to a subclass of differential type fluid known as the second-grade fluid with suspended nanoparticles in spherical shape of molybdenum disulphide (MoS2). Generally, the purpose of nanoparticles when dropped in regular fluid/base fluid/host fluid is to enhance the thermal conductivity of the host fluid. The inclusion of nanomaterial not only increases the thermal conductivity but also increases the base fluid viscosity (Wu et al. [21], Wang et al. [22], Garg et al. [23] and Lee et al. [24]). For this purpose, several types of nanomaterials, such as carbides, oxides and iron, and so on, are available in the market with their specific usage/characteristics and applications. For example, nanomaterial can be used as a nanolubricants, friction reductant, anti-wear agent and additive to tribological performance. Oxides, such as copper CuO2 and titanium oxides TiO2, can be used as an additive to lubricants. The combustion of fossil fuels produces injurious gases (CO and NO) that cause air pollution and global warming. To save natural recourses and produce environment-friendly products, currently, nanomaterials are used to enhance the fuel efficiency of the oils [25].

Among the different types of nanomaterial, there is one called molybdenum disulphide nanomaterial MoS2, used very rarely in nanofluid studies. Although MoS2 nanoparticles are not focused more, they have several interesting and useful applications. Applications of molybdenum disulphide can be seen in MoS2-based lubricants such as two-stroke engines, for example, motorcycle engines, automotive CV and universal joints, bicycle coaster brakes, bullets and ski waxes [26]. Moreover, the MoS2 has a very high boiling point and many researchers have investigated it as a lubricant The first theoretical study on MoS2-based nanofluid was performed by Shafie et al. [27], where they studied the shape effect of MoS2 nanoparticles of four different shapes (platelet, cylinder, brick and blade) in convective flow of fluid in a channel filled with saturated porous medium.

By keeping in mind the importance of MoS2 nanoparticles, this chapter studies the joint analysis of heat and mass transfer in magnetite molybdenum disulphide viscoelastic nanofluid of grade two. The concept of fractional calculus has been used in formulating the generalized model of grade-two fluid. MoS2 nanoparticles of spherical shapes have been used in engine oil chosen as base fluid. The problem is formulated in fractional form and Laplace transform together. CF derivatives have been used for finding the exact solution of the problem. Results are obtained in tabular and graphical forms and discussed for rheological parameters.

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2. Solution of the problem

Let us consider heat and mass transfer analysis in magnetite molybdenum disulphide nanofluid of grade two with viscosity and elasticity effects. MoS2 nanoparticles in powder form of spherical shape are dissolved in engine oil chosen as base fluid. MoS2 nanofluid is taken over an infinite plate placed in xy-plane. The plate is chosen in vertical direction along x-axis, and y-axis is transverse to the plate. Electrically conducting fluid in the presence of uniform magnetic B0 is considered which is taken normal to the flow direction. Magnetic Reynolds number is chosen very small so that induced magnetic field can be neglected. Before the time start, both the fluid and plate are stationary with ambient temperature T and ambient concentration C. At time t = 0+, both the plate and fluid starts to oscillate in its own direction with constant amplitude U and frequency ω. Schematic diagram is shown in Figure 1.

Figure 1.

Schematic Diagram of the flow.

Under these assumptions, the problem is governed by the following system of differential equations:

ρnfut=μnf2uy2+α13uty2σnfB02u+gρβTnfTT+gρβCnfCC,E1
ρcpnfTt=knf2Ty2,E2
Ct=Dnf2Cy2,E3

where ρnf,σnf,μnfβTnf,βCnf,knf,ρCpnf,Dnf are the density, electrical conductivity, viscosity, thermal expansion coefficient, coefficient of concentration, thermal conductivity, heat capacity and mass diffusivity of nanofluid. α1 shows second two parameters, and g denotes acceleration due to gravity.

The appropriate initial and boundary conditions are

uy0=0Ty0=TCy0=Cy>0,u0t=UHtcosωtT0t=TwC0t=Cwt>0,ut=0Tt=TCt=Casy,t>0.E4

For nanofluids, the expressions for ρnf,μnf,ρβnf,ρcpnf are given by:

μnf=μf1ϕ2.5,ρnf=1ϕρf+ϕρs,ρβTnf=1ϕρβf+ϕρβs,
ρβCnf=1ϕρβf+ϕρβs,ρcpnf=1ϕρcpf+ϕρcps,σnf=σf1+3σ1ϕσ+2σ1ϕ,
σ=σsσf,knfkf=ks+2kf2ϕkfksks+2kf+ϕkfks,Dnf=1ϕDf.E4a

where ϕ describes the volume fraction of nanoparticles. The subscripts s and f stands for solid nanoparticles and base fluid, respectively. The numerical values of physical properties of nanoparticle and base fluid are mentioned in Table 1.

Modelρkgm3CpJkg1K1CpJkg1K1β×105K1
Engine oil86320480.14040.00007
MoS25.06×103397.21904.42.8424

Table 1.

Numerical values of thermophysical properties.

Introducing the following dimensional less variables

v=uU,ξ=Uνy,τ=U2νt,θ=TTTwT,Φ=CCCwC.

into Eqs. (1)(4), we get

vτ=1Re2vξ2+βa13vτξ2M1v+Grϕ2θ+Gmϕ3Φ,E5
Prϕ4λnfθτ=2θξ2,E6
∂Φτ=1a42Φξ2.E7
vξ0=0θξ0=0Φξ0=0v0τ=cosωτθ0τ=1Φ0τ=1vτ=0θτ=0Φτ=0,E8

where

Re=1ϕ2.5a1,M1=Mϕ1a1,ϕ1=1+3σ1ϕσ+2σ1,ϕ2=1ϕρf+ϕρsβTsβTf,ϕ3=1ϕρf+ϕρsβCsβCf,ϕ4=1ϕ+ϕρcpsρcpf,λnf=knfkf,a1=1ϕ+ϕρsρf,a4=Sc1ϕ,

where Re is the Reynolds number, β=α1U2ρfν2 is the non-dimensional second-grade parameter, M=σfB02νρfU2 shows the Hartmann number (magnetic parameter), Gr=gνβTfU3TwT is the thermal Grashof number, Gm=gνβCfU3CwC is the mass Grashof number, Pr=μcpfk is the Prandtl number and Sc=νDf is the Schmidt number.

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3. Exact solution

In order to develop the generalized second-grade nanofluid model, we replace the partial derivative with respect to τ by CF fractional operator of order α, and Eqs. (5)(7) can be written as

Dταvξτ=1Re2vξ2+βa1Dτα3vτξ2M1v+Grϕ2θ+Gmϕ3Φ,E9
Prϕ4λnfDταθ=2θξ2,E10
a4DταΦ=2Φξ2,E11

where Dτα (.) is known as Caputo-Fabrizio time fractional operator and is defined as:

Dταf(τ)=11α0τexp(α(τt)1α)f"(τ)dt;    for0<α<1E12

Applying Laplace transform to Eqs. (9)(11) and using the corresponding initial conditions from Eq. (8), we have:

d2θ¯ξqdξ2b1qq+γ1θ¯ξq=0,E13
d2Φ¯ξqdξ2a2qq+γ1Φ¯ξq=0,E14
d2v¯ξqdξ2M4q+M3q+d1v¯ξq=Grϕ2θ¯ξqGmϕ3Φ¯ξq.E15

where b1=Prϕ4λnfγ0, γ1=αγ0, a2=a4γ0, M4=M1+γ0d0, M3=M1γ1M1+γ0, d1=a1γ1a1+Reβγ0, γ0=11α and d0=a1+Reβγ0Rea1.

Boundary conditions are transformed to:

θ¯0q=1q,θ¯q=0,E16
Φ¯0q=1q,Φ¯q=0,E17
v¯0q=qq2+ω2,v¯q=0.E18

Upon solving Eqs. (13)(15) and using the boundary conditions from Eqs. (16)(18), we get:

θ¯ξq=1qexpξb1qq+γ1,E19
Φ¯ξq=1qexpξa2qq+γ1,E20
v¯ξq=12χ¯ξM4qM3d1+12χ¯ξM4qM3d1+Gr3χ¯ξM4q0M3d1+R0χ¯ξM4qd2M3d1+R1χ¯ξM4qd3M3d1+Gm3χ¯ξM4q0M3d1+R2χ¯ξM4qd4M3d1+R3χ¯ξM4qd5M3d1Gr3χ¯ξb1q00γ1R0χ¯ξb1qd20γ1R1χ¯ξb1qd30γ1Gm3χ¯ξa2q00d1R2χ¯ξa2qd40d1R3χ¯ξa2qd50d1,E21
χ¯ξqabc=1q+aexpξq+bq+c.E22

Eqs. (19) and (20) are written in simplified form

θ¯ξq=χ¯ξb1q00γ1,E23
Φ¯ξq=χ¯ξa2q00γ1,E24

where

Gr3=Gr2γ12d2d3,Gm3=Gm2γ12d4d5,Gr2=Gr1δ1,Gm2=Gm1δ6,R0=d22Gr2+2d2Gr2γ1Gr2γ12d2d3,
R1=d32Gr23d3Gr2γ1+Gr2γ12d2d3,R2=d42Gm2+2d4Gm2γ1Gm2γ12d4d5,
R3=d52Gm23d5Gm2γ1+Gm2γ12d4d5,d2=δ42+δ42+4δ52,d3=δ42δ42+4δ52,
d4=δ82+δ82+4δ92,d5=δ82δ82+4δ92,Gr1=Grϕ2d0,Gm1=Gmϕ3d0,δ1=b1M4,

δ2=b1d1M4γ1M4M3,δ3=M4M3γ1,δ4=δ2δ1,δ5=δ3δ1,δ6=a2M4,
δ7=a2d1M4γ1M4M3,δ8=δ7δ6,δ9=δ3δ6.

Now, inverse Laplace transform of Eqs. (21), (23) and (24) is:

vξτ=12χξM4τM3d1+12χξM4τM3d1+Gr3χξM4τ0M3d1+R0χξM4τd2M3d1+R1χξM4τd3M3d1+Gm3χξM4τ0M3d1+R2χξM4τd4M3d1+R3χξM4τd5M3d1Gr3χξb1τ00αγ0R0χξb1τd20αγ0R1χξb1τd30αγ0Gm3χξa2τ00d1R2χξa2τd0d1R3χξa2τd50d1,E25
θξτ=χξb1τ00γ1,E26
Φξτ=χξa2τ00γ1,E27

where

χ¯ξqabc=1q+aexpξq+bq+c,E28
χξτabc=eξξbc2π00τeτexpξ24uuI12(bcut)dtdu.E29

Skin friction, Nusselt number and Sherwood number.

Skin friction, Nusselt number and Sherwood number are defined as:

Cf=11ϕ2.5vξ+β2vξτξ=0,E30
Nu=θξξ=0,E31
Sh=Φξξ=0.E32

Velocity field for regular grade-two fluid without mass transfer.

For Gm=ϕ=0 in Eq. (22) reduce to the following form:

vξτ=12χξM4τM3d1+12χξM4τM3d1+Gr3χξM4τ0M3d1+R0χξM4τd2M3d1+R1χξM4τd3M3d1Gr3χξb1τ00αγ0R0χξb1τd20αγ0R1χξb1τd30αγ0,E33

where b1=Prγ0, M4=M+γ0d0, M3=Mγ1M+γ0, d1=γ1d0, d0=1+βγ0, Gr1=Grd0,

which is quite identical to the solution of Sheikh et al. [19] for 1k=R=0.

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4. Graphical discussion

A fractional model for the outflow of the second-grade fluid with nanoparticles over an isothermal vertical plate is studied. The coupled partial differential equations with Caputo-Fabrizio time-fractional derivatives are solved analytically via Laplace transform method. Furthermore, the influence of different embedded parameters such as α, ϕ, β, M, t Gr, Gm and Sc is shown graphically.

Figures 27 depict the effect of α on vξτ for two different values of time. It is clear from the figures that for smaller value of τ, when (τ = 0.2) fractional velocity is larger than classical velocity and for larger value of τ, when (τ =2) fractional velocity is less than classical velocity. Clearly, increasing values of α decrease vξτ.

Figure 2.

Velocity profile for different values of β when M=1,Gr=Gm=2,Pr=5,Sc=5andϕ=0.02.

Figure 3.

Velocity profile for different values of ϕ when M=1,Gr=Gm=2,Pr=5,Sc=5andβ=0.3.

Figure 4.

Velocity profile for different values of Gr when M=1,ϕ=0.02,Gm=2,Pr=5,Sc=5andβ=0.3.

Figure 5.

Velocity profile for different values of Gm when M=1,Gr=2,ϕ=0.02,Pr=5,Sc=5andβ=0.3.

Figure 6.

Velocity profile for different values of M when ϕ=0.02,Gr=Gm=2,Pr=5,Sc=5andβ=0.3.

Figure 7.

Velocity profile for different values of Sc when M=1,Gr=Gm=2,Pr=5,ϕ=0.02andβ=0.3.

Figure 2 represents the influence of β on both the velocity and microrotation profiles. A decreasing behaviour is observed for increasing values of β in both cases. In this figure, the comparison of second-grade fluid velocity with Newtonian fluid velocity is plotted. It is obvious that the boundary layer thickness of second-grade fluid velocity is greater as compared to boundary layer thickness of Newtonian fluid. More clearly, the velocity of second-grade fluid is smaller than Newtonian fluid.

Figure 3 shows the influence of ϕ on the flow. It was found that the velocity of fluid decreases with the increase in ϕ due to the increase in viscosity. Because by increasing volume fraction, the fluid becomes more viscous, which leads to a decrease in the fluid velocity.

Figures 4 and 5 show the influence of thermal Grashof number Gr and mass Grashof number Gm on velocity and microrotation. Increasing values of both of these parameters are responsible for the rise in buoyancy forces and reducing viscous forces, which result in an increase in fluid velocity and magnitude of microrotation.

Figure 6 depicts the MHD effect on velocity. In this type of flows, magnetic force results in achieving steady state much faster than the non-MHD flows. Moreover, increasing values of M enhances the Lorentz forces, as a result decelerates the fluid velocity. Figure 7 illustrates variations in velocity for different values of Schmidt number, Sc. It shows that velocity decreases when Sc value increases. The effect of Schmidt number on velocity is identical to that of the magnetic parameter. The influence of phase angle ωτ on the velocity profile is shown in Figure 8. The velocity is showing fluctuating behaviour.

Figure 8.

Velocity profile for different values of ω.

In order to show the effect of α,τandϕ on the temperature profile in Figure 9, it is found that temperature increasing with increasing value of ϕ. Figure 10 shows the effect of α and τ on temperature profile. This figure shows the effect of α on the temperature profile for two different values of τ. For smaller value of τ τ=0.2, classical temperature is less than fractional temperature, and for larger value, when τ=2, then the graph shows opposite behaviour. Figure 11 shows the comparison of present solution with published result of Sheikh et al. [19]. It is noted that in the absence of porosity and radiation, the present result is similar to those obtained in [19. See Figure 9], which shows the validity of our obtained results.

Figure 9.

Temperature profile for different values of ϕ when Pr=5.

Figure 10.

Temperature profile for different values of time parameter.

Figure 11.

Comparison of this study with Sheikh et al. [19], when 1k=R=0.

Variations in skin friction, Nusselt number and Sherwood number are shown in Tables 24. The effect of β,α,Gr,Gm,M,Sc,ϕ,ωτandτ on the skin friction is studied in Table 2. It is found that skin friction increases when there is an increase in α,Gr,Gm,M,Sc,ωτandτ. but it is noticed that for increasing value of β and ϕ, skin friction decreases. It is due to the fact that when ϕ increases, it gives rise to lubricancy of the oil. Table 3 represents the effect of α,ϕandτ on Nusselt number. As values of α,ϕandτ increase, Nusselt number decreases. From Table 4, it is clear that when Sc increases, Sherwood number increases, and an increase in τ decreases Sherwood number.

Table 2.

Effect of various parameters on the skin friction.

Table 3.

Effect of various parameters on the Nusselt number.

Table 4.

Effect of various parameters on the Sherwood number.

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5. Conclusion remarks

Unsteady MHD flow of generalized second-grade fluid along with nanoparticles has been analyzed. The exact solution has been obtained for velocity, temperature and concentration profile via the Laplace transform technique. The effects of various physical parameters are studied in various plots and tables with the following conclusions:

  • With increase in volume friction ϕ of nanofluid, lubricancy of the fluid increases.

  • An increase in second-grade parameter β leads to a decrease in fluid velocity.

  • The velocity profile shows different behaviour for fractional parameter for different values of time.

  • In limited cases, the obtained solutions reduced to the solution of Sheikh et al. [19].

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Written By

Farhad Ali, Madeha Gohar, Ilyas Khan, Nadeem Ahmad Sheikh, Syed Aftab Alam Jan and Muhammad Saqib

Submitted: 09 October 2017 Reviewed: 01 December 2017 Published: 22 August 2018