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. 2021 Apr 25;11(5):1107. doi: 10.3390/nano11051107

Fully Developed Opposing Mixed Convection Flow in the Inclined Channel Filled with a Hybrid Nanofluid

Xiangcheng You 1,*, Shiyuan Li 1
Editors: Hang Xu1, Gozde Tutuncuoglu1
PMCID: PMC8146417  PMID: 33922900

Abstract

This paper studies the convective heat transfer of a hybrid nanofluid in the inclined channel, whose walls are both heated by the uniform heat flux. The governing ordinary differential equations are made nondimensional and solved analytically, in which explicit distributions of velocity, temperature and pressure are obtained. The effects of flow reversal, wall skin friction and Nusselt number with the hybrid nanofluid depend on the nanoparticle volume fractions and pressure parameters. The obtained results indicate that the nanoparticle volume fractions play a key role in delaying the occurrence of the flow reversal. The hybrid nanofluids hold more delayed range than conventional nanofluids, which is about 2.5 times that of nanofluids. The calculations have been compared with the base fluid, nanofluid and two kinds of hybrid models (type II and type III). The hybrid model of type III is useful and simplified in that it omits the nonlinear terms due to the interaction of different nanoparticle volumetric fractions, with the relative error less than 3%. More results are discussed in the results section below.

Keywords: hybrid nanofluid, mixed convection, inclined channel, flow reversal

1. Introduction

Research on mixed convection inducted flow is increasingly interested in many engineering applications, such as in heat exchangers, chemical processing equipment, transport of heated or cooled fluids, solar power collectors, microelectronic cooling and so on. Furthermore, the mixed convection flow through a channel has received a great deal of attention [1,2,3,4,5] in literature. However, most of the previous studies have focused on the horizontal or vertical configuration and mixed convection in inclined geometries has been studied less. Thus, it is worthwhile to explore the flow on the inclined flat plate at various angles which is often come across in engineering devices, such as solar water heaters, inclination/acceleration sensors and so on. Bohne et al. [6] investigated superposed free and forced convection in an internally heated concentric annulus in vertical, inclined and horizontal position with experiments. Lavine [7] presented an exact solution of fully developed, laminar flow between inclined parallel plates with a uniform wall heat flux boundary condition. Wang [8] studied numerically with fully developed opposing mixed convection in an inclined channel that had discrete heating on the bottom and was insulated on the top. Barletta et al. [9] researched analytically the fully developed laminar mixed convection with viscous dissipation in an inclined channel with prescribed wall temperatures. Aydin et al. [10] investigated MHD mixed convective heat transfer flow about an inclined plate. Cimpean [11] studied the steady fully developed mixed convection flow of a nanofluid in a channel filled with a porous medium. You et al. [12] presented analysis of fully developed opposing mixed convection flow in an inclined channel filled by a nanofluid. Goyal et al. [13] examined numerically natural convective boundary layer flow of a nanofluid past a heated inclined plate in the presence of magnetic field and found that the thermal boundary layer thickness increased with strengthening the value of inclination angle parameter. Rafique et al. [14] studied numerically on micropolar nanofluid flow over an inclined surface by means of Keller-Box method. Khademi et al. [15] studied numerical analysis of mixed convection flow of nanofluid over an inclined flat plate embedded in a porous medium in the presence of a transverse magnetic field. Anuar et al. [16] presented work explored the heat transfer and boundary layer flow of a hybrid nanofluid past an inclined stretching/shrinking sheet with suction and buoyancy force effects.

It is well-known that nanofluids have been applied to problems with the thermal properties of heat transfer fluids. The nanofluids were first researched by Choi and Eastman [17]; they are kinds of suspended nanoparticles in the base fluid, such as ethylene glycol, oil or water. The properties of the nanofluids are higher than the base fluid, such as viscosity, diffusion coefficient, heat transfer rate and thermal conductivity [18,19,20,21,22]. Nanofluids can be used in microchip cooling, nuclear reactor, industrial cooling, sensing, drug delivery, nanomedicine, the oil recovery process and so on [23,24]. However, hybrid nanofluids are composed of two different nanoparticles dispersed in the base fluid, which have better thermophysical properties and rheological behavior along with improved heat transfer properties [25,26,27]. In recent years, many scientists and researchers have been attracted to investigating real-world heat transfer problems with hybrid nanofluids [28,29,30]. Obviously, it is necessary to study the mechanisms of hybrid nanofluids that contribute to the heat transfer enhancement.

Motivated and based on the literature discussed above, the main aim of this paper is to study the fully developed mixed convection flow in the inclined channel filled with a hybrid nanofluid, which employs simply homogeneous model proposed by Maïga et al. [31]. In this study, hybrid nanofluid is formed by suspending two different nanoparticles, which are copper and alumina, in the base fluid. The governing equations with boundary conditions are solved analytically that have never been reported before based on the literature survey. The model analyses the hybrid nanofluid behavior by comprising the nanoparticles solid volume fractions, which using two kinds of hybrid models (type II and type III). The result shows that the hybrid model of type III is useful and simplified that omits the nonlinear terms due to the interaction of different nanoparticle volumetric fractions. Besides, the effects of the main physical parameters are discussed respectively, such as the nondimensional pressure parameter P1,P2, the nanoparticle volume fractions ϕ1,ϕ2, the velocity profile U(Y), the temperature profile θθb, the average wall friction CfRe¯ and the average Nusselt number Nu¯; these are illustrated graphically. The hybrid nanofluids hold better thermophysical properties than conventional nanofluids based on the results.

2. Mathematical Model

Consider the steady mixed convection flow, which is driven by a buoyancy force and an external pressure gradient between two paralleled long inclined plane walls filled with a hybrid nanofluid and separated by a distance L. Figure 1 shows the sketch of system and the coordinate axes, where x and y axes are measured along the lower plane of the channel oriented in the downward direction, y axis is in the normal to the lower plane, q is the constant wall heat flux, g is the acceleration due to gravity and γ is the inclination angle of the channel. The velocity field is given in the case by v(u,0), then the continuity equation reduces to u/x=0 and implies u=u(y). Following Lavine [7] and using the hybrid nanofluid model, the momentum balance and energy equations according to the Boussinesq approximation are written by

px=(ρβ)hnf g(TT0)sinγ+μhnfd2udy2, (1)
py=(ρβ)hnf g(TT0)cosγ, (2)
uTx=αhnf2Ty2, (3)

subject to the boundary conditions

u(0)=0, u(L)=0, Tyy=0=Tyy=L=1. (4)

Figure 1.

Figure 1

Physical configuration and coordinate system.

The mass flow rate is assumed as a prescribed quantity of this channel flow study, then the following average fluid velocity in the section will be prescribed as

u¯=0Lu(y)dy. (5)

Here u is the velocity component along the x axis, u¯ is the average velocity, T is the temperature of the hybrid nanofluid, T0 is the constant reference temperature, p is the fluid thermodynamic pressure and g is the gravitational acceleration. The physical quantities in Equations (1)–(3) are ϕ1,ϕ2 is the nanoparticle volume fractions, βf,βn1,βn2 are the coefficients of thermal expansion of the base fluid and nanofluid respectively, ρf,ρn1,ρn2 are the densities of the base fluid and nanofluid, μhnf is the viscosity of the hybrid nanofluid and αhnf is the thermal diffusivity of the hybrid nanofluid, μf is the dynamic viscosity of the base fluid and its expression has been proposed by Brinkman [32], khnf is the thermal conductivity of the hybrid nanofluid, kf,kn1,kn2 are the thermal conductivities of the base fluid and nanofluid, (ρCp)hnf is the heat capacitance of the hybrid nanofluid. Note that the expression (5) is restricted to spherical nanoparticles where it does not account for other shapes of nanoparticles. The thermophysical properties of the base fluid, nanofluid and hybrid nanofluid are given in Table 1, Table 2, Table 3 and Table 4, referring to references [33,34,35,36,37].

Table 1.

Thermophysical properties of nanoparticles and water [33].

Physical Properties Cu Al2O3 H2O
ρ (kg/m3) 8933 3970 997.1
Cp (J/kg K) 385 765 4179
k (W/mK) 400 40 0.613
α×107 (m2/s) 11,163.1 131.7 1.47
β×105 (1/K) 1.67 0.85 21

Table 2.

Thermophysical properties of nanofluid (type I) [34].

Properties Nanofluid
Density ρnf=(1ϕ1)ρf+ϕ1(ρβ)n1
Thermal expansion coefficient (ρβ)nf=(1ϕ1)(ρβ)f+ϕ1(ρβ)n1
Heat capacity (ρCp)nf=(1ϕ1)(ρCp)f+ϕ1(ρCp)n1
Viscosity μnf=μf(1ϕ1)2.5
Thermal diffusivity αnf=knf(ρCp)nf
Thermal conductivity knfkf=kn1+2kf2ϕ1(kfkn1)kn1+2kf+ϕ1(kfkn1)
Electrical conductivity σnfσf=1+3σn1σf1ϕ12+σn1σfσn1σf1ϕ1

Table 3.

Thermophysical properties of hybrid nanofluid (type II) [35].

Properties Nanofluid
Density ρhnf=(1ϕ2)[(1ϕ1)ρf+ϕ1ρn1]+ϕ2ρn2
Thermal expansion coefficient (ρβ)hnf=(1ϕ2)[(1ϕ1)(ρβ)f+ϕ1(ρβ)n1]+ϕ2(ρβ)n2
Heat capacity (ρCp)hnf=(1ϕ2)[(1ϕ1)(ρCp)f+ϕ1(ρCp)n1]+ϕ2(ρCp)n2
Viscosity μhnf=μf(1ϕ1)2.5(1ϕ2)2.5
Thermal diffusivity αhnf=khnf(ρCp)hnf
Thermal conductivity khnfknf=kn2+2knf2ϕ2(knfkn2)kn2+2knf+ϕ2(knfkn2), where knfkf=kn1+2kf2ϕ1(kfkn1)kn1+2kf+ϕ1(kfkn1)
Electrical conductivity σhnfσnf=σn2+2σnf2ϕ2(σnfσn2)σn2+2σnf+ϕ2(σnfσn2), where σnfσf=σn1+2σf2ϕ1(σfσn1)σn1+2σf+ϕ1(σfσn1)

Table 4.

Thermophysical properties of hybrid nanofluid (type III) [36,37].

Properties Nanofluid
Density ρhnf=(1ϕ1ϕ2)ρf+ϕ1ρn1+ϕ2ρn2
Thermal expansion coefficient (ρβ)hnf=(1ϕ1ϕ2)(ρβ)f+ϕ1(ρβ)n1+ϕ2(ρβ)n2
Heat capacity (ρCp)hnf=(1ϕ1ϕ2)(ρCp)f+ϕ1(ρCp)n1+ϕ2(ρCp)n2
Viscosity μhnf=μf(1ϕ1ϕ2)2.5
Thermal diffusivity αhnf=khnf(ρCp)hnf
Thermal conductivity khnfknf=kn2+2knf2ϕ2(knfkn2)kn2+2knf+ϕ2(knfkn2), where knfkf=kn1+2kf2ϕ1(kfkn1)kn1+2kf+ϕ1(kfkn1)
Electrical conductivity σhnfσnf=σn2+2σnf2ϕ2(σnfσn2)σn2+2σnf+ϕ2(σnfσn2), where σnfσf=σn1+2σf2ϕ1(σfσn1)σn1+2σf+ϕ1(σfσn1)

Introduce the following dimensionless variables

X=αfx/(u¯L2), Y=y/L, U(Y)=u/u¯,θ(X,Y)=(TT0)/(qL/kf),P(X,Y)=pρfg(xsinγycosγ)/(Prρfu¯2), (6)

where αf is the thermal diffusivity of the base fluid, νf is the kinematic viscosity of the base fluid, Pr=νf/αf is the Prandtl number. Substituting variables (6) into Equations (1)–(3), the following dimensionless equations are obtained

PX=P1(ρβ)hnf(ρβ)fθ+μhnfμfd2UdY2, (7)
PY=P2(ρβ)hnf(ρβ)fθ, (8)
UθX=αhnfαf2θY2, (9)

subject to the boundary conditions

U(0)=0, U(1)=0, θYY=0=θYY=1=1, (10)

along with the mass flux conservation relation

01UdY=1. (11)

Here P1=Grsinγ/Re and P2=Grcosγ/(PrRe2) are nondimensional pressure parameters, Gr=gβfqL4/(kfνf2) is the Grashof number and Re=u¯L/νf is the Reynolds number.

Integrating Equation (9) over the channel cross-section, making use of Equation (11) and the boundary conditions (10) for temperature distribution θ, and considering the constant heat flux distribution of x-direction at the walls, the following relation can be obtained

θX=2αhnfαf. (12)

Differentiating Equation (7) with Y and Equation (8) with X respectively, and taking into account (12), then equating them, we obtain

P1(ρβ)hnf(ρβ)fθY+μhnfμfd3UdY3=2αhnfαf(ρβ)hnf(ρβ)fP2. (13)

Differentiating this equation with Y once again, we obtain

μhnfμfd4UdY4=P1(ρβ)hnf(ρβ)f2θY2. (14)

Making use of Equations (9) and (12), we finally obtain

μhnfμfd4UdY4=2P1(ρβ)hnf(ρβ)fU. (15)

This equation can be solved analytically for the velocity distribution U, the temperature distribution θ and the pressure distribution P can be determined as well. The analytical solution of Equation (15) can be obtained by using the computational softwares such as MATHEMATICA or MAPLE.

Using the software MATHEMATICA and taking account of the boundary conditions (10), the analytical solutions of the velocity distribution U, the temperature distribution θ and the pressure distribution P can be given explicitly as

U(Y)=a[sinh(mY)+sin(mY)]+b[cosh(mY)cos(mY)]+csin(mY), (16)
θ(X,Y)=2m2{a[sinh(mY)sin(mY)]+b[cosh(mY)+cos(mY)]csin(mY)}2P2P1αhnfαfY+2αhnfαfX+A, (17)
P(X,Y)=(ρβ)hnf(ρβ)f{2P2m3{a[cosh(mY)+cos(mY)]+b[sinh(mY)+sin(mY)]+ccos(mY)}+P22αhnfαfXY+AYP2P1αhnfαfY2P1(AX+αhnfαfX2)+B}, (18)

where A and B are the constants, whose values are dependent on the given values of P1 and P2, and they must satisfy the boundary conditions for θ and P. The parameters a, b, c and m are given as

a=[mc+ccos(m)][cosh(m)cos(m)]2[cosh(m)cos(m)1]+csin(m)[sinh(m)sin(m)]2[cosh(m)cos(m)1],b=[mc+ccos(m)][sinh(m)+sin(m)]2[cosh(m)cos(m)1]+csin(m)[cosh(m)cos(m)]2[cosh(m)cos(m)1],c=m12P2P1αhnfαf,m4=2P1(ρβ)hnf(ρβ)fμfμhnf. (19)

Once the values of P1 and P2 are artificially prescribed, the analytical solutions of U, θ and P can be fully determined. Note that the analytical solution for the horizontal case (P1=0) can be obtained by expanding the above solutions for small m, or more simply, by solving the Equations (7)–(9) by setting P1=0. Noting that for ϕ1=ϕ2=0, the solutions are reduced to those of Lavine [7].

The physical quantities of practical interest in this problem are the wall friction Cf Re and the Nusselt number Nu, they are given by

Cf Re=τw12ρfu¯2u¯Lνf,Nu=2qLkf(TwTb), (20)

where Tw is the wall temperature, Tb is the bulk temperature. τw is the wall shear stress which is defined by

τw=±μnfuy|0,L, (21)

where ± signs correspond to the bottom and top walls, respectively.

Substituting Equations (6) and (21) into Equation (20), we obtain

Cf Re=2mμhnfμf2a+cat Y=0,2mμhnfμf{a[cosh(m)+cos(m)]+b[sinh(m)+sin(m)]+ccos(m)}at Y=1, (22)

and

Nu=2qLkf(TwTb)=2(θwθb), (23)

where

θb=01UθdYandθw=θ(Y=0,1). (24)

The average of the top and bottom wall friction is also of interest. It is given by:

CfRe¯=12[CfRe(Y=0)+CfRe(Y=1)]=μhnfμfm2[cos(m)cosh(m)sin(m)sinh(m)]cos(m)cosh(m)1. (25)

Thus, the average wall friction (CfRe¯) is seen to be independent of parameter P2.

Similarly, the average of the top and bottom Nusselt number is given by:

Nu¯=12[Nu(Y=0)+Nu(Y=1)]=1θw|Y=0θb+1θw|Y=1θb. (26)

Furthermore, the average Nusselt number (Nu¯) is dependent of parameter P2.

3. Results and Discussion

To comprehend the current problem, the physical influence of the governing parameters, such as the pressure parameters P1,P2, the nanoparticle volume fractions ϕ1,ϕ2, the velocity profile U(Y), the temperature profile θθb, the average wall friction CfRe¯ and the average Nusselt number Nu¯ are illustrated graphically. The flow reversal occurs to the upper wall satisfies (dU/dY)Y=1=0, or Cf Re|Y=1=0. The following constraint relationship of P1 and P2 based on Equation (22) can be obtained as

αhnfαfP2=P12cos(m)cosh(m)sin(m)sinh(m)cos(m)cosh(m)+sin(m)sinh(m). (27)

The flow regime map of the base fluid (H2O), nanofluid (Cu-H2O,type I) and hybrid nanofluid (Cu-Al2O3-H2O,type II and III) with ϕ1,ϕ2, the inflexion exists for each curve with corresponding to P2=0 and P1=P1, c is shown in Figure 2 and Table 5. About the base fluid, nanofluid and hybrid nanofluid, P1, c is the critical value for P1 which value is 250.281948 (Lavine’s case [7]) for ϕ1=ϕ2=0. For P1P1, c, the involved region is divided into two parts by a certain curve. The upper part is the regime that the flow reversal occurs to the top wall only, and the lower part is the regime in which no flow reversal can be measured. For P1P1, c, this curve separates the regime for which flow reversal occurs to both walls of the regime of flow reversal of the bottom wall only. For a vertical channel (P2 = 0), flow reversal must occur to both walls of the flow in symmetric about the channel centerline in this configuration. About the nanofluid, P1, c=288.675450 for ϕ1=0.05 and P1, c=335.346949 for ϕ1=0.1. Furthermoer, the hybrid nanofluid, P1, c=342.496247 (type II) and P1, c=345.142372 (type III) for ϕ1=ϕ2=0.05; P1, c=476.114704 (type II) and P1, c=492.724576 (type III) for ϕ1=ϕ2=0.1, respectively. For a horizonal channel (P1=0), it is expected that the occurrence of flow reversal of upper wall is founded for P2>P2, c, where P2, c is the critical value of P2 with its value. With ϕ1=ϕ2=0, P2, c=35.999978 with the base fluid, P2, c=35.972464 with the nanofluid and hybrid nanofluid. About nanofluid, P2, c=35.543514 for ϕ1=0.05 and P2, c=35.562942 for ϕ1=0.1. And hybrid nanofluid, P2, c=36.203632 (type II) and P2, c=36.467267 (type III) for ϕ1=ϕ2=0.05; P2, c=37.499401 (type II) and P2, c=38.736813 (type III) for ϕ1=ϕ2=0.1, respectively. With increasing from ϕ1,ϕ2, the critical values P1, c enlarges simultaneously. Notice that P1, c enlarges on increasing ϕ1,ϕ2, while P2, c also increases. Results show that the nanoparticle volume fractions ϕ1,ϕ2 play a key role in delaying the occurrence of the flow reversal. The hybrid nanofluids hold more delayed range than conventional nanofluids, which is about 2.5 times that of nanofluids. The calculations of hybrid nanofluid about type II and type III agree very well; the relative error compared with hybrid nanofluid of type II is 0.7% for ϕ1=ϕ2=0.05 and 3% for ϕ1=ϕ2=0.1. So the hybrid nanofluid of type III that is proposed based on the linear assumptions is useful.

Figure 2.

Figure 2

Flow regime map of the base fluid (H2O), nanofluid (Cu-H2O,type I) and hybrid nanofluid (Cu-Al2O3-H2O,type II and III).

Table 5.

The critical values of P1 and P2.

Critical Values Types ϕ1=ϕ2=0 ϕ1=ϕ2=0.05 ϕ1=ϕ2=0.1
P1, c H2O (Lavine’s case [7]) 250.281948 - -
Cu-H2O (type I) 250.281948 288.675450 335.346949
Al2O3-H2O [12] 250.281948 296.981071 355.527252
Cu-Al2O3-H2O (type II) 250.281948 342.496247 476.114704
Cu-Al2O3-H2O (type III) 250.281948 345.142372 492.724576
P2, c H2O (Lavine’s case [7]) 35.999978 - -
Cu-H2O (type I) 35.972464 35.543514 35.562942
Al2O3-H2O [12] 35.972464 36.597696 37.750800
Cu-Al2O3-H2O (type II) 35.972463 36.203632 37.499401
Cu-Al2O3-H2O (type III) 35.972463 36.467267 38.736813

Velocity and temperature profiles for the base fluid, nanofluid and hybrid nanofluid are presented in Figure 3 and Figure 4. The velocity and temperature profiles for the liquid at P1=100 with P2=0 and P2=36 have been analyzed and temperature profiles will be illustrated as θθb that eliminate the x-dependence. The velocity profiles are symmetric about the centerline and no flow reversals are found for all considered ϕ1,ϕ2 for P2=0 corresponding to the vertical channel configuration. The velocity near the walls increases as ϕ1,ϕ2 increase, while the velocity in the vicinity of the centerline decreases from ϕ1,ϕ2 increasing. The effects of ϕ1,ϕ2 on the velocity distribution are evident; the increases in ϕ1,ϕ2 delay the velocity reduction near the upper wall compared with the base fluid, nanofluid and hybrid nanofluid. Furthermore, the calculations of hybrid nanofluid about type II and type III agree very well. In the case of P2=36, for any given values of ϕ1,ϕ2, it is found that the velocity peak enlarges in magnitude and moves to the lower wall (Y=0) compared with P2=0, while the velocity near the upper wall (Y=1) deceases with the flow reversal. The temperature profiles for the base fluid, nanofluid and hybrid nanofluid at P1=100 are presented in Figure 4. The temperature near the upper wall increases accordingly as P2 enlarges. At the same time, the valley of the temperature shifts towards the lower wall and its value increases consecutively with the increase in P2. The temperature variation near the upper wall becomes larger and larger and the valley of the temperature moves to the upper wall gradually as ϕ1,ϕ2 increase for P2. The hybrid nanofluids about type II and type III agree very well, which are potential fluids that offer better thermophysical properties and heat transfer performance than convectional fluids and nanofluids with single nanoparticles.

Figure 3.

Figure 3

Variation with P2 of the velocity profiles for the base fluid (H2O), nanofluid (Cu-H2O, type I) and hybrid nanofluid (Cu-Al2O3-H2O, type II & III) at P1 = 100.

Figure 4.

Figure 4

Variation with P2 of the temperature profiles for the base fluid (H2O), nanofluid (Cu-H2O, type I) and hybrid nanofluid (Cu-Al2O3-H2O, type II & III) at P1 = 100.

The average wall friction CfRe¯ and the average Nusselt number Nu¯ are also physical quantities of practical interests, as shown as Figure 5 and Figure 6. Figure 5 shows the effects of ϕ1,ϕ2 on the average wall friction with the base fluid, nanofluid and hybrid nanofluid. The average wall friction that is the independent of parameter P2 decreases monotonously as P1 increases. The hybrid nanofluids about type II and type III agree very well as P1 increases, and the relative error compared with hybrid nanofluid of type II is 3% for ϕ1=ϕ2=0.1. Figure 6 shows the effects of ϕ1,ϕ2 on the average Nusselt number with the base fluid, nanofluid and hybrid nanofluid. Contrary to the average friction, the average Nusselt number is dependent of P2 and its value is equal to the average of top and bottom Nusselt number for P1,P2 and ϕ1,ϕ2 are prescribed. The average Nusselt number increases monotonously with the base fluid, nanofluid and hybrid nanofluid as P1 increases for P2=0. At the same time, the valley of the average Nusselt number shifts towards the lower wall and its value increases consecutively with the increase in P2. The effects of ϕ1,ϕ2 on the average Nusselt number distribution are evident with the base fluid, nanofluid and hybrid nanofluid. Furthermore, the calculations of hybrid nanofluid about type II and type III are in very good agreement. The hybrid nanofluids are potential fluids that offer better thermophysical properties and heat transfer performance than convectional fluids and nanofluids with single nanoparticles.

Figure 5.

Figure 5

Variation of average CfRe with P1 when Re=10,Pr=1 and Gr=3000.

Figure 6.

Figure 6

Variation of average Nu with P1 for P2=0 and P2=100 when Re=10,Pr=1 and Gr=3000.

4. Conclusions

In this paper, fully developed mixed convection flow in the inclined channel filled by a hybrid nanofluid with a uniform wall heat flux boundary condition has been studied. The governing ordinary differential equations are made nondimensional and they are solved analytically. The explicitly analytical solutions of the velocity, temperature and pressure have been given. The effects of flow reversal, wall skin friction and Nusselt number of the hybrid nanofluid that depend on the nanoparticle volume fractions and pressure parameters are discussed and shown graphically (see Section 3). The hybrid nanofluids are potential fluids that offer better thermophysical properties and heat transfer performance than convectional fluids and nanofluids with single nanoparticles. The main key findings are listed below.

  • (1)

    The nanoparticle volume fractions play a key role in delaying the occurrence of the flow reversal. The hybrid nanofluids hold a more delayed range than conventional nanofluids, which is about 2.5 times that of nanofluids.

  • (2)

    Two hybrid models (type II and type III) are compared with different nanoparticle volume fractions ϕ1,ϕ2 and pressure parameters P1,P2. It is observed that they are in very good agreement, with the relative error less than 3%. The hybrid model of type III is useful and simplified in that it omits the nonlinear terms due to the interaction of different nanoparticle volumetric fractions.

  • (3)

    The effects of nanoparticle volume fractions on the velocity and temperature distributions are evident, the increases of ϕ1,ϕ2 delay the velocity reduction and enlarge the temperature variation near the upper wall (Y=1) compared with the base fluid, nanofluid and hybrid nanofluid.

  • (4)

    The average wall friction (CfRe¯) that is independent of P2 decreases monotonously as P1 increases. The average Nusselt number (Nu¯) that is dependent of P2 increases monotonously as P1 increases for the vertical channel (P2=0). The valley of the average Nusselt number shifts towards the lower wall and its value increases consecutively with the increase of P2.

Acknowledgments

We thank the anonymous referees for their valuable comments and discussions.

Nomenclature

The following nomenclature is used in this manuscript:

A,B Constants
Cf Wall skin friction coefficient
C¯f Average wall skin friction
Cp Specific heat at constant pressure
g Acceleration due to gravity
Gr Grashof number
khnf Thermal conductivity of the hybrid nanofluid
kf,kn Thermal conductivities of the base fluid and nanofluid, respectively
L Distance between the walls
Nu Nusselt number
p Dimensional thermodynamic pressure
P Dimensionless thermodynamic pressure
P1,P2 Dimensionless pressure parameters
P1,c,P2,c Critical values for P1 and P2, respectively
Pr Prandtl number
q Constant wall heat flux
Re Reynolds number
T Nanofluid temperature
Tb,Tw Bulk and wall temperature, respectively
T0 Constant reference temperature
u(y) Dimensional velocity component along the x axis
u¯ Dimensional average velocity
U(Y) Dimensionless velocity component along the X axis
x Dimensional axis measured along lower plane of channel oriented in downward direction
y Dimensional axis measured in the normal direction to the lower plane
X,Y Dimensionless coordinates
αhnf Thermal diffusivity of the hybrid nanofluid
αf Thermal diffusivity of the base fluid
βf,βn Coefficients of thermal expansion of the fluid and nanofluid, respectively
ϕ1,ϕ2 Nanoparticle volume fractions
γ Inclination of the channel
μhnf Viscosity of the hybrid nanofluid
μf Dynamic viscosity of the base fluid
νf Kinematic viscosity of the base fluid
θ Dimensionless nanofluid temperature
θb,θw Dimensionless bulk and wall temperature, respectively
(ρCp)hnf Heat capacitance of the hybrid nanofluid
ρf,ρn Densities of the fluid and nanofluid fractions, respectively
τw Skin friction or wall shear stress

Author Contributions

X.Y.; original draft preparation, software, formal analysis, S.L.; supervision, project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This work is supported by the National Natural Science Foundation of China (Grant No. 12002390 and 51704307) and Foundation of China University of Petroleum-Beijing (ZX20200119).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All drawings were made by myself.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

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