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. 2021 Jan 10;23(1):89. doi: 10.3390/e23010089

Entropy Generation Analysis of Hybrid Nanomaterial through Porous Space with Variable Characteristics

Muhammad Adil Sadiq 1,*, Farwa Haider 2, Tasawar Hayat 2
PMCID: PMC7828087  PMID: 33435225

Abstract

Salient features of hybrid nanofluid (MoS2-SiO2/water) for Darcy–Forchheimer–Brinkman porous space with variable characteristics is examined. Heat transfer analysis subject to viscous dissipation, nonlinear thermal radiation, and heat generation/absorption is carried out. Disturbance inflow is created by an exponentially stretching curved sheet. Relevant equations are simplified by employing boundary layer theory. Adequate transformations lead to a set of dimensionless equations. Velocity, temperature, and entropy generation rate are analyzed graphically. Comparative results are obtained for hybrid (MoS2-SiO2/water) and nanofluid (MoS2-water and SiO2-water). Physical quantities are analyzed through numerical data.

Keywords: hybrid nanofluid (MoS2 and SiO2), Darcy–Forchheimer–Brinkman porous space, non-linear thermal radiation, viscous dissipation, heat generation/absorption, ND Solve

1. Introduction

Electronics, automotive, telecommunication, aerospace, and biomedical industries require microdevices for heat transfer enhancement in a system. Heat transfer efficiency of such devices can be improved by using a working fluid with enhanced thermophysical properties like thermal conductivity and specific heat. Hybrid nanofluids are potential materials produced by dispersing two dissimilar nanoparticles (metals, carbide and oxide ceramics, carbon nanotubes, and metals) in base fluid (ethylene glycol, oil, and water). Such fluids have superior thermophysical properties and thermal performance than nanofluids. Such nanofluids save energy as well as less harmful environmental impacts. After the pioneering work of Choi [1] on nanofluids, several studies have been conducted to analyze the behavior of such materials. Few of these are mentioned here which considered different nanoparticles such as Cu, Al2O3, Ag, CuO, and several others. Eastman et al. [2] analyzed improvement in thermal conductivity of ethylene glycol-based copper nanofluid. It is noted that ethylene-glycol based copper nanofluid has much higher effective thermal conductivity than pure ethylene glycol. The flow of nanofluid in a lid-driven square cavity is provided by Tiwari and Das [3] They analyzed the behavior of nanofluid by considering solid volume fraction of nanoparticles. Vajravelu et al. [4] presented convective heat transfer in Ag-water and Cu-water nanofluids. A comparative analysis is performed for Ag-water and Cu-water nanofluids. It is observed that boundary layer thickness decreases more rapidly in the case of Ag-water nanofluid in comparison to Cu-water. The three-dimensional flow of nanofluid is examined by Khan et al. [5]. Devasenan and Kalaiselvam [6] provided an experimental investigation of the heat transfer behavior of hybrid nanofluid. Copper-titanium hybrid nanocomposites are considered. They found an increase in thermal conductivity due to the highly crystalline nature of copper-titanium hybrid nanofluid. Malvandi et al. [7] discussed mixed convection in Al2O3-water nanofluid. Selimefendigil et al. [8] elaborated mixed convection in SiO2-water nanofluid by a rotating cylinder. Different shapes of nanoparticles are considered such as spherical, cylindrical, brick, and blade. It is analyzed that the heat transfer rate of cylindrically shaped nanoparticles is higher than that of others. Improvement in heat transfer of Ag-CuO/water nanofluid is addressed by Hayat and Nadeem [9]. Iqbal et al. [10] analyzed curvilinear transport of MoS2-SiO2/water nanofluid. It is noted that blade-shaped nanoparticles have maximum temperature while brick-shaped nanoparticles have the lowest temperature. Thermally radiative flow of Cu-Al2O3/water nanomaterial over a permeable surface is interpreted by Usman et al. [11] Mansour et al. [12] provided entropy generation analysis of square porous cavity filled with Al2O3-Cu/water nanofluid. The influence of internal heat generation in the flow of MoS2-SiO2/C3H8O2 is studied by Shaiq et al. [13] Khan et al. [14] analyzed entropy generation analysis of MoS2-SiO2/C3H8O2 nanofluid with variable viscosity. Heat transfer enhancement in hybrid nanofluid along the wavy surface is studied by Iqbal et al. [15]. It is noted that hybrid nanofluid has a higher transfer rate than nanomaterial. Khan et al. [16] presented an entropy generation analysis of MoS2-SiO2/ water nanofluid through porous space. Acharya [17] analyzed the behavior of hybrid nanofluid inside a microchannel. Hydromagnetic flow of Cu-Al2O3/water nanofluid past moving sheet is illustrated by Aladdin et al. [18] Flow of hybrid nanofluid saturating porous medium with mixed convection is discussed by Waini et al. [19] Aly and Pop [20] provided comparative analysis for stagnation point flow of hybrid nanofluid and nanomaterial with MHD.

Porous space is composed of interconnected solid particles and pores generally encountered in electrochemical systems, iron and steel making, microchemical reactors, biofiltration systems, and combustion of carbon-neutral and renewable fuels. Extensive theoretical and computational studies about porous media are based on classical Darcy’s law. To include inertia and viscous diffusion effects in Darcy’s law, the modifications are made by Forchheimer [21] and Brinkman [22,23] respectively. To resolve this paradox, Nield [24] modeled viscous dissipation in a porous medium. Hadhrami et al. [25] provided another model for viscous dissipation in porous space. Mixed convective flow through porous space is analyzed by Seddeek [26] Umavathi et al. [27] illustrated Darcy-Forchheimer-Brinkman flow of nanofluid in a vertical rectangular duct. Latest developments in flow through a porous medium with constant porosity and permeability and can be cited through refs. [28,29,30,31,32,33,34,35,36]. However little information is available for variable characteristics of porous space [37,38,39,40,41,42,43,44]

Entropy generation is a quantitative tool based on the second law of thermodynamics. It measures irreversibilities in the fluid flow process. Heat and mass transfer, viscous dissipation, buoyancy, and magnetic field are the source of chaos in a thermal system. Several studies are conducted to anticipate the entropy generation rate in thermal systems followed by the pioneering work of Bejan [45]. Entropy generation of nanofluid in a cavity is analyzed by Mahmoudi et al. [46]. It is observed that the entropy generation rate decreases due to the addition of nanoparticles. Entropy generation analysis of nanofluid in a vertical porous microchannel is provided by López et al. [47] Sithole et al. [48] explored entropy generation analysis of nanofluid with nonlinear thermal radiation. It is noted that the entropy generation rate decreases in presence of thermal radiation. Entropy generation analysis of ferrofluid saturating porous space is elaborated by Astanina et al. [49]. Huminic and Huminic [50] discussed entropy generation analysis of hybrid nanofluid. Entropy generation analysis of viscous fluid with buoyancy is interpreted by Ganesh et al. [51] Kashyap and Dass [52] deliberated entropy generation analysis of the two-phase mixed convective flow of hybrid nanofluid. The effects of three different boundary conditions on fluid flow are analyzed. It is observed that the entropy generation rate increases by a change in the boundary condition. Moreover, the addition of nanoparticles also augments the entropy generation rate which is not desirable for the effectiveness of a thermal system. Entropy generation for nanofluid through non-Darcy porous space is studied by Sheikholeslami et al. [53] Effect of activation energy inflow over the curved surface with entropy generation is analyzed by Muhammad et al. [54] Hayat et al. [55] provided entropy generation for the flow of nanofluid due to curved surface filling porous space. Hayat et al. [56] presented entropy generation analysis of effective Prandtl number.

In view of the above-mentioned studies, the main objectives of the present study are threefold. Firstly, to formulate the flow of hybrid nanofluid by a curved stretching surface through porous space. Variable porosity and permeability are chosen. This concept is given a little attention even for flow by flat stretching case. Secondly, to consider the effects of nonlinear thermal radiation and heat generation/absorption in heat transfer analysis. Thirdly to anticipate the entropy generation rate in the considered problem. Solution development is due to the NDSolve technique of Mathematica. Characteristics of flow, thermal field, and entropy generation rate through involved variables are interpreted. Numerical computations are obtained for physical quantities.

2. Model Development

Here the flow of hybrid nanofluid through Darcy–Forchheimer–Brinkman porous space is analyzed. Viscous dissipation, heat generation/absorption, and non-linear thermal radiation are also taken. The disturbance in flow is created by a curved stretching surface. The sheet is stretched with an exponential velocity uw(s)=aes/L (see Figure 1). Here curvilinear coordinates frame (s, r) is adopted. Relevant equations for the considered problem are

r((r+R)v)+Rus=0, (1)
u2r+R=1ρhnfpr, (2)
vur+Rr+Ruus+uvr+R=1ρhnfRr+Rps+νhnf(2ur2+1r+Ruru(r+R)2)νhnfε(r)k*(r)uCbε2(r)(k*(r))1/2u2, (3)
vTr+uTsRr+R=αhnf(2Tr2+1r+RTr)+μhnf(ρcp)hnf(urur+R)2+Q(ρcp)hnf(TT)1(ρcp)hnfr(16σ˜3kT3Tr)+μhnf(ρcp)hnfε(r)k*(r)u2+ρhnf(ρcp)hnfCbε2(r)(k*(r))1/2u3, (4)
u=aes/L,v=0,T=Tf=T+T0eAs/2L at r=0, (5)
u0,ur0,TT as r, (6)

where

k*(r)=k(1+derγ), (7)
ε(r)=ε(1+d*erγ). (8)

Model for hybrid nanofluid is [13]:

μhnf=μf(1ϕ1ϕ2)2.5, νhnf=μhnfρhnf, ρhnf=ρf(1ϕ1ϕ2)+ρ1ϕ1+ρ2ϕ2,αhnf=khnf(ρcp)hnf, (ρcp)hnf=(ρcp)f(1ϕ1ϕ2)+(ρcp)1ϕ1+(ρcp)1ϕ1,khnfkf=ϕ1k1+ϕ2k2+2ϕkf+2ϕ(ϕ1k1+ϕ2k2)2(ϕ1+ϕ2)2kfϕ1k1+ϕ2k2+2ϕkfϕ(ϕ1k1+ϕ2k2)+(ϕ1+ϕ2)2kf. (9)

Here ϕ1 signifies solid volume fraction of SiO2, ϕ2 the solid volume fraction of MoS2, ρhnf hybrid nanofluid density, (ρcp)hnf heat capacity of hybrid nanofluid, μhnf effective dynamic viscosity of hybrid nanofluid, khnf the thermal conductivity of hybrid nanofluid, ρ1 the density of SiO2, ρ2 the density of MoS2, k1 the thermal conductivity of SiO2, k2 the thermal conductivity of MoS2, kf the thermal conductivity of base fluid, ρf the density of base fluid, k and ε the constant permeability and porosity, d and d* the variable permeability and porosity, Q the heat generation/absorption, Cb the drag coefficient, σ˜ the Stefan Boltzmann coefficient and k the mean absorption coefficient. Following Table 1 [14] consists of characteristics of base liquids and nanoparticles.

Figure 1.

Figure 1

Physical model of flow configuration.

Table 1.

Physical properties of base and nanoparticles.

Physical Properties Base Fluid Nanoparticles
H2O SiO2 MoS2
ρ (kg/m3) 997.1 2650 5060
k (W/mK) 0.613 1.5 34.5
Cp (J/kgK) 4179 730 397.746

Considering

u=Uw=aes/Lf(ζ), v=Rr+Raνfes/L2L(f(ζ)+ζf(ζ)), ζ=(aes/L2νfL)1/2r,T=T+T0eAs2Lθ(ζ), p=ρfa2e2s/LH(ζ), (10)

we have

1(1ϕ1ϕ2+ρ1ρfϕ1+ρ2ρfϕ2)H=1ζ+Kf2, (11)
1(1ϕ1ϕ2)2.5(1ϕ1ϕ2+ρ1ρfϕ1+ρ2ρfϕ2)(f+1ζ+Kf1(ζ+K)2f21σRes1+d*eζ1+deζf)ζ+2K(ζ+K)2K(f)2+Kζ+Kff+K(ζ+K)2ff2β(1+d*eζ)21+deζf2=1(1ϕ1ϕ2+ρ1ρfϕ1+ρ2ρfϕ2)Kζ+K(4H+ζH) (12)
1Pr1(1ϕ1ϕ2+(ρcp)1(ρcp)fϕ1+(ρcp)2(ρcp)fϕ2)khnfkf(θ+1ζ+Kθ)+Kζ+K(fθAfθ)+1(1ϕ1ϕ2+(ρcp)1(ρcp)fϕ1+(ρcp)2(ρcp)fϕ2)(2Q*θ+Ec(1ϕ1ϕ2)2.5((f1ζ+Kf)2+2σRes1+d*eζ1+deζf2)43RdPr(((1+(θw1)θ)3)θ)+2βEc(1ϕ1ϕ2+(ρcp)1(ρcp)fϕ1+(ρcp)2(ρcp)fϕ2)(1+d*eζ)21+deζf3)=0, (13)
f=0, f=1, θ=1 at ζ=0, (14)
f0, f0, θ0 as ζ. (15)

Here Equation (1) is trivially verified. Eliminating pressure H from Equations (11) and (12), we have

1(1ϕ1ϕ2)2.5(1ϕ1ϕ2+ρ1ρfϕ1+ρ2ρfϕ2)(fiv+2ζ+Kf1(ζ+K)2f+1(ζ+K)3f21σRes1+d*eζ1+deζ(f+1ζ+Kf))+K(ζ+K)2ff+Kζ+KffK(ζ+K)3ff3K(ζ+K)2f23Kζ+Kff2β(1+d*eζ)21+deζ(2ff+1ζ+Kf2)=0. (16)

Here Pes depicts the Peclet number, γ the parameter, Res the local Reynolds number, β the inertia coefficient, Ec the Eckert number, K the curvature parameter, σ the permeability parameter, Rd the radiation parameter, Q* the heat generation/absorption parameter, Pr the Prandtl number, and Br the Brinkman number. These definitions are

Pes=ResPr, γ=αfLPes1/22νfL, Res=uwLνf, σ=kL2ε, K=(aes/L2νfL)1/2R,β=Cbε2Lk, Rd=4σT3k*kf, θw=TwT, Q*=QLuw(ρcp)f, Ec=uw2(TwT)(cp)f,Pr=νfαf, Br=PrEc. (17)

3. Physical Quantities

Skin friction coefficient and local Nusselt number are given by

(Res2)1/2Cf=1(1ϕ1ϕ2)2.5(f(0)1Kf(0)), (18)
(Res2)1/2Nus=(khnfkf+43θw3Rd)θ(0). (19)

4. Entropy Generation

Entropy generation expression for considered flow problem is

Sgen=khnfTm2(Tr)2Thermal irreversibility+μhnfTm(urur+R)2Viscous dissipation irreversibility+QTm(TT)Heat generation/absorption irreversibility+1Tmr(16σ3kT3Tr)Thermal radiation irreversibility+μhnfTmε(r)k*(r)u2+Cbε2(r)ρhnfTmk*1/2u3Porous dissipation irreversibility, (20)

Applying transformations (10) above expression reduces to

Ng(ζ)=khnfkfα1θ2+2PrQ*θ+43Rd((1+(θw1)θ)3θ)+Br(1ϕ1ϕ2)2.5((f1ζ+Kf)2+2σRes1+d*eζ1+deζf2)+2βBr(1ϕ1ϕ2+ρ1ρfϕ1+ρ2ρfϕ2)(1+d*eζ)21+deζf3, (21)

in which α1=ΔTTm is the temperature difference parameter and Ng=TmΔTSgen2νfLaes/L the entropy generation rate.

5. Discussion

This section interprets the characteristics of velocity f(ζ), temperature θ(ζ) and entropy generation rate Ng(ζ) through curvature parameter (K), porosity parameter (σ), Reynolds number (Res), variable porosity and permeability parameters (d) and (d*), inertia coefficient (β), Brinkman number (Br), temperature exponent (A), temperature ratio parameter (θw), radiation parameter (Rd), and heat generation/absorption parameter (Q*). Comparative results are obtained for hybrid nanofluid (MoS2-SiO2/water) and nanofluid (MoS2/water and SiO2/ water). The consequences of f(ζ) against (K) are in Figure 2. An enhancement in f(ζ) is observed through (K) for both hybrid nanofluid and nanomaterial. Physically the bend of the curved stretching sheet contributes in accelerating the flow. The impact of (σ) on f(ζ) is illustrated in Figure 3. Here f(ζ) is an increasing function of (σ) for both hybrid nanofluid and nanofluid. Velocity f(ζ) through (Res) is drawn in Figure 4. Higher (Res) correspond to stronger f(ζ) for both hybrid nanofluid and nanofluid. Physically (Res) has a direct relation with inertial forces due to which the velocity increases. Reverse trend of f(ζ) is noted for (d) and (d*) in both hybrid nanofluid and nanofluid (see Figure 5 and Figure 6). Figure 7 is plotted for the features of f(ζ) through (β). Higher estimation of (β) lead to a reduction in f(ζ) for both hybrid nanofluid (MoS2-SiO2/water) and nanofluid (MoS2/water and SiO2/water). Figure 8 addressed θ(ζ) against (K). By increasing (K) reduction is observed through (K) for both hybrid nanofluid and nanofluid. Figure 9 captured consequences of θ(ζ) against (σ). Here reduction in θ(ζ) is analyzed through higher (σ) for both hybrid nanofluid and nanofluid. Figure 10 depicts that θ(ζ) is a decreasing function of (Res) for both hybrid nanofluid (MoS2-SiO2/water) and nanofluid (MoS2/water and SiO2/ water). Behaviors of θ(ζ) through (d) and (d*) is portrayed in Figure 11 and Figure 12. An enhancement in θ(ζ) is observed through (d*) while opposite trend is seen against (d) for both hybrid nanofluid and nanofluid. Aspects of θ(ζ) against (β) is deliberated in Figure 13. Higher (β) produces resilience in the fluid motion due to which more heat is produced which strengthens the thermal field θ(ζ) for both hybrid nanofluid (MoS2-SiO2/water) and nanofluid (MoS2/water and SiO2/ water). Figure 14 cleared that θ(ζ) is an increasing function of (Br) for both hybrid nanofluid and nanofluid. Physically (Br) has a direct relation with heat generation by fluid friction which causes stronger θ(ζ). Significant behavior of θ(ζ) through (A) is drawn in Figure 15. Higher (A) produces weaker θ(ζ) in both hybrid nanofluid and nanofluid. Curves of θ(ζ) against (Rd) is elucidated in Figure 16. Higher estimation of (Rd) strengthen θ(ζ) and more related layer thickness for both hybrid nanofluid and nanofluid. Variation of θ(ζ) through (θw) is displayed in Figure 17. It is seen that higher (θw) enhance θ(ζ) for both hybrid nanofluid (MoS2-SiO2/water) and nanofluid (MoS2/water and SiO2/ water). Role of (Q*) on θ(ζ) is highlighted in Figure 18. Here an augmentation in θ(ζ) is observed through (Q*) for both hybrid nanofluid and nanofluid. Influence of (K) on Ng(ζ) is depicted in Figure 19. Entropy generation rate decreases due to higher (K) for both hybrid nanofluid and nanofluid. Figure 20 and Figure 21 analyzed the behavior of Ng(ζ) against (Br) and (Rd). Similar trend of Ng(ζ) is witnessed through (Br) and (Rd) for both hybrid nanofluid and nanomaterial. Figure 22 illustrates that Ng(ζ) increases for higher (θw) for both hybrid nanofluid (MoS2-SiO2/water) and nanofluid (MoS2/water and SiO2/water). Impact of (Q*) on Ng(ζ) is sketched in Figure 23. Higher (Q*) produces augmentation in θ(ζ) due to rise in surface temperature for both hybrid nanofluid and nanofluid. Consequences of (α1) on Ng(ζ) is highlighted in Figure 24. Here Ng(ζ) is an increasing function of (α1) for both hybrid nanofluid and nanofluid. Contribution of involved variables on skin friction coefficient (Res2)1/2Cf is displayed in Table 2 Reduction in (Res2)1/2Cf is seen through (K), (σ), (Res), (d) and (β) for both hybrid nanofluid and nanofluid. Significant behavior of (Res2)1/2Nus through influential variables is shown in Table 3 Here (K), (σ), (d), (Rd) and (θw) strengthen the (Res2)1/2Nus for both hybrid nanofluid and nanofluid. Table 4 is drawn to compare the values of skin friction coefficient with Okechi et al. [28]. It is analyzed that present results are in good agreement with those presented in ref. [28].

Figure 2.

Figure 2

Sketch of f(ζ) against K.

Figure 3.

Figure 3

Sketch of f(ζ) against σ.

Figure 4.

Figure 4

Sketch of f(ζ) against Res.

Figure 5.

Figure 5

Sketch of f(ζ) against d.

Figure 6.

Figure 6

Sketch of f(ζ) against d*.

Figure 7.

Figure 7

Sketch of f(ζ) against β.

Figure 8.

Figure 8

Sketch of θ(ζ) against K.

Figure 9.

Figure 9

Sketch of θ(ζ) against σ.

Figure 10.

Figure 10

Sketch of θ(ζ) against Res.

Figure 11.

Figure 11

Sketch of θ(ζ) against d.

Figure 12.

Figure 12

Sketch of θ(ζ) against d*.

Figure 13.

Figure 13

Sketch of θ(ζ) against β.

Figure 14.

Figure 14

Sketch of θ(ζ) against Br.

Figure 15.

Figure 15

Sketch of θ(ζ) against A.

Figure 16.

Figure 16

Sketch of θ(ζ) against Rd.

Figure 17.

Figure 17

Sketch of θ(ζ) against θw.

Figure 18.

Figure 18

Sketch of θ(ζ) against Q*.

Figure 19.

Figure 19

Sketch of Ng(ζ) against K.

Figure 20.

Figure 20

Sketch of Ng(ζ) against Br.

Figure 21.

Figure 21

Sketch of Ng(ζ) against Rd.

Figure 22.

Figure 22

Sketch of Ng(ζ) against θw.

Figure 23.

Figure 23

Sketch of Ng(ζ) against Q*.

Figure 24.

Figure 24

Sketch of Ng(ζ) against α1.

Table 2.

Numerical data of skin friction coefficient (Res2)1/2Cf for K, σ, Res, d, d*, and β.

K σ Res d d* β (Res2)1/2Cf
Hybrid Nanofluid MoS2-Water SiO2-Water
1.0 1.1 1.1 3.0 1.5 0.2 3.84238 3.85225 3.79266
1.3 3.41971 3.43047 3.36545
1.5 3.23852 3.24971 3.18205
2.0 1.0 1.1 3.0 1.5 0.2 2.99600 3.00776 2.93661
2.0 2.75157 2.76442 2.68650
3.0 2.65921 2.67253 2.59173
2.0 1.1 1.1 3.0 1.5 0.2 2.95453 2.96646 2.89425
1.5 2.83785 2.85030 2.77490
1.9 2.76557 2.77835 2.70085
2.0 1.1 1.1 1.0 1.5 0.2 3.24720 3.25959 3.18459
2.0 3.06787 3.07997 3.00672
3.0 2.95453 2.96646 2.89425
2.0 1.1 1.1 3.0 0.0 0.2 2.64363 2.65338 2.59446
1.0 2.84189 2.85292 2.78613
2.0 3.07546 3.08842 3.00990
2.0 1.1 1.1 3.0 1.5 0.0 2.74260 2.75107 2.69994
0.1 2.85047 2.86073 2.79873
0.3 3.05515 3.06865 2.98681

Table 3.

Numerical data of local Nusselt number (Res2)1/2Nu for K, σ, Res, d, d*, β, Br, Rd, θw and Q*.

K σ Res d d* β Br Rd θw Q* (Res2)1/2Nu
Hybrid Nanofluid MoS2-Water SiO2-Water
1.0 1.1 1.1 3.0 1.5 0.2 0.3 0.3 1.1 0.1 0.78812 0.77888 0.78773
1.3 0.95609 0.94689 0.96164
1.6 1.06312 1.05373 1.07280
2.0 1.0 1.1 3.0 1.5 0.2 0.3 0.3 1.1 0.1 1.12722 1.11800 1.13864
2.0 1.29904 1.28665 1.32381
3.0 1.36435 1.35064 1.39455
2.0 1.1 1.1 3.0 1.5 0.2 0.3 0.3 1.1 0.1 1.15619 1.14646 1.16977
2.0 1.29904 1.28665 1.32381
3.0 1.36435 1.35064 1.39455
2.0 1.1 1.1 3.0 0.0 0.2 0.3 0.3 1.1 0.1 1.36447 1.35379 1.38047
1.0 1.23024 1.22030 1.24414
2.0 1.07829 1.06870 1.09196
2.0 1.1 1.1 3.0 1.5 0.0 0.3 0.3 1.1 0.1 1.28077 1.27229 1.28646
0.1 1.21696 1.20783 1.22679
0.3 1.09811 1.08785 1.11512
2.0 1.1 1.1 3.0 1.5 0.2 0.5 0.3 1.1 0.1 0.75746 0.75223 0.74922
0.6 0.55799 0.55499 0.53882
0.7 0.35843 0.35767 0.32834
2.0 1.1 1.1 3.0 1.5 0.2 0.3 0.0 1.1 0.1 1.09425 1.08172 1.11263
0.4 1.16916 1.15964 1.18257
0.8 1.22079 1.21096 1.23532
2.0 1.1 1.1 3.0 1.5 0.2 0.3 0.3 1.0 0.1 1.14395 1.13379 1.15834
1.4 1.18662 1.17787 1.19835
1.8 1.19871 1.19025 1.21112
2.0 1.1 1.1 3.0 1.5 0.2 0.3 0.3 1.1 −0.2 1.55119 1.53599 1.57635
0.0 1.30480 1.29301 1.32259
0.2 0.97895 0.97161 0.98815

Table 4.

Comparative values of skin friction coefficient (Res2)1/2Cf for distinct values of K.

K (Res2)1/2Cf
Okechi et al. [28] Present
5 1.4196 1.45703
10 1.3467 1.36819
20 1.3135 1.32810
30 1.3028 1.31536
40 1.2975 1.30912
50 1.2944 1.30539
100 1.2881 1.29804
200 1.2850 1.29443
1000 1.2826 1.29152

6. Conclusions

The main points of the current analysis are:

  • Velocity has the opposite scenario for variable characteristics of porosity and permeability.

  • Aspects of the permeability parameter on velocity are reversed when compared with the thermal field.

  • Enhancement in velocity is witnessed against the curvature parameter.

  • Temperature against Brinkman number and radiation parameter have a similar trend.

  • Augmentation in the thermal field is observed through the inertia coefficient.

  • Entropy generation rate increases for heat generation/absorption and temperature ratio parameter.

  • Skin friction coefficient for variable permeability parameter decays.

  • Augmentation in local Nusselt number is witnessed for radiation and temperature ratio parameters.

  • Some possible extension of the current analysis may be as follows:

  • Importance of melting heat transfer effects inflow of hybrid nanofluid.

  • Binary chemical reaction and activation energy aspects inflow by curved stretching surface.

  • Modeling of non-Newtonian liquids inflow due to curved geometry.

Acknowledgments

We wish to express our thanks for the financial support of this research from King Fahd University of Petroleum and Minerals.

Nomenclature

R Radius of curvature s,r space coordinate
u,v velocity components Uw surface stretching velocity
ρ1,ρ2 densities of nanaparticles μf fluid dynamic viscosity
d variable permeability k1,k2 thermal conductivity of nanoparticle
ρf fluid density d* variable porosity
νf kinematic fluid viscosity νhnf kinematic viscosity of hybrid nanofluid
kf basefluid thermal conductivity khnf thermal conductivity of hybrid nanofluid
αf thermal diffusivity of base fluid Tw surface temperature
αhnf thermal diffusivity of hybrid nanofluid T ambient temperature
ε porosity k* permeability of porous medium
p pressure Cb drag coefficient
Q heat generation/absorption σ˜ Stefan Boltzmann constant
k mean absorption coefficient Q* heat generation/absorption parameter
F non-uniform inertia coefficient ϕ1,ϕ2 solid volume fraction of nanoparticles
Rd radiation parameter Res local Reynolds number
β Inertia coefficient Br Brinkman number
Cf skin friction coefficient Nus local Nusselt number
σ local porosity parameter Pes Peclet number
θ dimensionless temperature f dimensionless velocity
K curvature parameter Ng(ζ) entropy generation rate
H dimensionless pressure ζ dimensionless variable
Pr Prandtl number A temperature exponent

Author Contributions

M.A.S., F.H. and T.H. contributed in mathematical modeling, computation of numerical solutions, analysis of results and writing of article. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by KFUPM, grant number SB191015.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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