Accepted Manuscript
Mixed convection peristaltic motion of Copper-water nanomaterial with velocity slip effects in a curved channel T. Hayat, S. Farooq, A. Alsaedi PII: DOI: Reference:
S0169-2607(16)30995-6 10.1016/j.cmpb.2017.02.006 COMM 4350
To appear in:
Computer Methods and Programs in Biomedicine
Received date: Revised date: Accepted date:
19 September 2016 20 January 2017 8 February 2017
Please cite this article as: T. Hayat, S. Farooq, A. Alsaedi, Mixed convection peristaltic motion of Copper-water nanomaterial with velocity slip effects in a curved channel, Computer Methods and Programs in Biomedicine (2017), doi: 10.1016/j.cmpb.2017.02.006
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Highlights • Copper-water nanomaterial in peristalsis is modeled. • First order velocity slip conditions are considered.
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• Heat generation/absorption is presented.
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• Heat transfer rate at upper wall of the channel is also discussed.
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Mixed convection peristaltic motion of Copper-water nanomaterial with velocity slip effects in a curved channel T. Hayata,b , S. Farooqa,1 and A. Alsaedib Department of Mathematics, Quaid-I-Azam University 45320, Islamabad 44000, Pakistan
b
Nonlinear Analysis and Applied Mathematics (NAAM) Research Group, Department of
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a
Mathematics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia Abstract:
Background and objective: The primary objective of present analysis is to model
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the peristalsis of copper-water based nanoliquid in the presence of first order velocity and thermal slip conditions in a curved channel. Mixed convection, viscous dissipation and heat generation/absorption are also accounted. Method:
Mathematical formulation is simplified under the assumption of small
Reynolds number and large wavelength. Regular perturbation technique is employed to
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find the solution of the resulting equations in terms of series for small Brinkman number. The final expression for pressure gradient, pressure rise, stream function, velocity and tem-
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perature are obtained and discussed through graphs. Mathematica software is utilized to compute the solution of the system of equations and to plot the graphical results.
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Results: Results indicates that insertion of 30% copper nanoparticles in the basefluid (water) velocity and temperature reduces by almost 3% and 40% respecively. Moreover it
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is seen that size of the trapped bolus also reduces almost 20% with the insertion of 20% nanoparticles (copper) in the basefluid (water). Conclusion: It is noted that velocity and temperature are decreasing functions of
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nanoparticle volume fraction. Moreover the temperature rises when heat generation parameter and Brinkman number are enhanced. Key words: Copper-water nanofluid; Curved channel; First order velocity slip condi-
tions; Heat generation; Mixed convection. 1
Tel.: + 92 51 90642172.
e-mail address:
[email protected]
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1
Introduction
Mixed convection flow has numerous applications in engineering for instance cooling of electronic devices, food processing, solidification, float glass production, nuclear reactors, microelectronic devices, coating and solar power. The communication between the shear driven flow and natural convection has important effects on the enhancement in the flow mixing
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and heat transfer process. Volumetric internal heat generation is an important issue in engineering such as nuclear power plants, concrete or inside of earth. Basically in the presence of buoyancy forces, these flows are highly considerable as means to ease the thermal capability in numerous industrial procedures. Convection in channel is also experienced in advanced
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cooling/heating systems, ejection of nuclear waste and in heat exchangers. Keeping in mind the above mentioned key features in engineering and industry the researchers focused towards the topic of mixed convection (see some studies [1-5]). It is an indensible challenge for scientists and researchers to improve the heat transfer ability of conventional liquids including water, engine oil and ethylene glycol having low thermal conductivity. Nanofluid is
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the mixture of base fluid and nanoparticles (copper, iron, gold, titanium etc.) of nanosized (10-100nm) which is used to improve the heat transfer rate of microelectronics, computer
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microchips, transportation, fuel cells, food processing, biomedicine, manufacturing and solid state lightening. Mostly used nanoparticles are of spherical and tubular shaped. Choi [6] was
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the first who used the nanomaterial (nanoparticles) to improve thermal conductivity of fluids. Buongiorno [7] suggests that Brownian motion and thermophoresis are very important in nanofluids dynamics. Some modelers used the Buongiorno’s model to study the nanoflu-
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ids characteristics given in the refs. [8-11]. Xuan and Li [12] computed the expressions (relations) for the effective viscosity and density of the nanofluids. The effective viscosity
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for the two phase flow introduced by Brinkman’s [13] seemed to be in excellent agreement with that of Xuan and Li [14]. The analysis of Xuan and Li [12] and Brinkman [13] was extended by Tiwari and Das [15] which was later utilized by several investigators to explore the characteristics of nanofluids (for detail see refs. [16-26]). The achieved results are found in an excellent agreement with the available experimental research. Flows generated by the oscillatory movement of the channel walls are usually known as peristaltic flows. Such phenomenon is comprised due to sinusoidal motion of the channel walls which propel the fluid filled within the channel/tube. Basically the peristaltic motion
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is the continuous process of wave-like muscular contractions which is useful in transporting physiological materials like chyme through intestine, food bolus through oesophagus, urine transport from kidney to gallbladder, locomotion in earthworm, ovum in the fallopian tube, blood in the small blood vessels transportation of water in trees and in several others. Peristalsis is responsible in moving physiological fluids along the physiological ducts by contrac-
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tion/expansion of circular smooth muscle behind the fluids and relaxation of circular smooth muscle ahead of it. Medical devices such as dialysis machine, open heart bypass machine, stethoscope, heart lung machine and ventilator machine obey the principle of peristalsis. The principle of peristalsis is further useful in several industrial processes like transport of sanitary and toxic materials, finger and roller pumps, hose pumps and peristaltic pumps.
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The interesting experimental and theoretical studies was initially introduced by Latham [27] and Shapiro et al. [28]. These two pioneering studies were further extended for both Newtonian and non-Newtonian materials with various flow assumptions as elaborated in the refs. [29-36]. Afterwards the peristaltic flows in straight or planer channels have been considered extensively. However such consideration is not satisfactory when the flows mostly through
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physiological conduits, arteries and glandular ducts are considered. In such situations and the industry, the flow configurations are of curved shapes. To fill this gap Sato et al. [37]
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firstly explored the peristalsis in curved channel. Ali et al. [38] extended the work mentioned in ref. [37] under large wavelength assumption. Heat transfer analysis on peristalsis
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of viscous liquid in a curved configuration is explored by Ali et al. [39]. Recently Hayat et al. [40] and [41] examined the impact of radial magnetic field on the peristaltic flow of
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Carreau-Yasuda liquid and Carreau liquid with wall properties and convective conditions in a curved channel respectively. Ali et al. [42] numerically discussed the heat transfer effects
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on peristaltic flow of an Oldroyed 8-constant liquid in a curved channel. Further Hayat et al. [43] extended the study presented in ref. [42] by considering convective heat and mass transfer effects in a curved channel. Hina et al. [44] considered the peristalsis of nanofluid in a curved channel. Magnetohydrodynamic pressure driven peristaltic flow of nanofluid in a curved geometry is analyzed by Noreen et al. [45]. Nadeem et al. [46] presented the peristaltic flow of Williamson nanomaterial in a curved channel with wall properties. Nadeem et al. [47] also studied the peristalsis of two phase nanofluid model in a curved channel. Narla et al. [48] formulated the peristaltic flow of Jeffrey nanofluid in a curved channel. Peristalsis of nanofluid has a significant role in the drug delivery systems and in can4
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cer therapy as means to destroy the tissues. Literature survey indicates that attempts on the peristalsis of two phase nanofluid model in a curved channel are rare. The intention of the present communication is to explore such fluid model describing peristalsis in a curved channel. Thus our main purpose here is to investigate mixed convection peristalsis of copper-water nanofluid in a curved channel. The channel walls verify the velocity conditions.
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Impacts of viscous dissipation and heat generation/absorption are also taken into account. The curved channel is filled with an incompressible copper-water nanoliquid. Relevant modelling is made in view of Tiwari and Das model [15]. Solution of the dimensionless problem is utilized in terms of perturbation series. Physical explanation of the obtained results is
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Problem formulation
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discussed through plots for various flow quantities of interest.
Here we consider peristalsis of copper-water nanoliquid filled in a two-dimensional curved channel (of width 2a1 ) twisted in a circle with radius R∗ and centre at O (see Fig. 1). Velocity
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¯ and axial X ¯ directions are dented by V¯1 and V¯2 respectively. Moreover components in radial R both the peristaltic walls are considered at different temperatures T1 and T0 respectively.
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Here flow is due to propagation of sinusoidal waves along the axial direction. Aspects of heat generation/absorption and mixed convection are also taken into account. Further the
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first order velocity and thermal slip conditions are considered at channel boundaries The shape of waves are
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2π ¯ ¯ ¯ ¯ ¯ H X, t = ± a1 + b1 sin X − ct . λ∗ Where c is the wave speed λ∗ the wavelength t¯ the time and b1 the amplitude.
(1) The
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ρnf denotes the nanofluid density, µef f the effective dynamic viscosity of nanofluid, Cnf the specific heat, κef f the effective thermal conductivity of nanofluid, Φ0 the heat genera¯ the body force, P¯ the pressure and T the fluid ¯ the velocity, ρb tion absorption quantity, V temperature. The ρnf , µef f , (ρβ)nf , (ρC)nf , and κef f for copper-water nanoparticle are given in the form [6,9,16,49]:
ρnf = ρbf (1 − φ) + ρnf φ, (ρβ)nf = (1 − φ) (ρβ)bf + φ (ρβ)nf , µef f = (ρC)nf = (1 − φ) (Cρ)bf + φ (Cρ)nf ,
κef f κnf = κbf κnf 5
µbf
(1 − φ)2.5 + 2κbf − 2φ (κbf − κnf ) . (2) + 2κbf + 2φ (κbf − κnf )
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Here Maxwell-Gamett’s model (MG-model) is considered to approximate the effective thermal conductivity κef f and effective dynamic viscosity µef f of the nanofluid. In the above equation φ denotes the nanoparticle volume fraction and ρbf the density of base fluid (water), ρnf the nanoparticle (copper) density. The velocity is given by ¯ R, ¯ t¯),V¯2 (X, ¯ R, ¯ t¯),0). ¯ = (V¯1 (X, V
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The relevant equations are [9,16,21,47,49]:
¯ ∂ ∗ ¯ ¯ ∗ ∂ V2 R + R V + R 1 ¯ ¯ = 0, ∂R ∂X
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¯ ∂ P¯ ∂ V1 ¯ ∂ V¯1 R∗ V¯2 ∂ V¯1 V¯22 + V1 ¯ + ∗ ¯ ¯ − ∗ ¯ = − ¯ ρnf ∂ t¯ ∂R R + R ∂X R +R ∂R # " 2 2¯ 1 ∂ V¯1 R∗ ∂ V1 V¯1 2R∗ ∂ 2 V¯1 ∂ V¯2 +µef f − ¯ ,(5) ¯2 + R ¯ + R∗ ∂ R ¯ + R ¯ + R∗ ¯2 − R ¯ + R∗ 2 ¯ + R∗ 2 ∂ X ∂R ∂X R
+g (ρβ)nf (T − T0 ) ,
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¯ ¯ ∂ V2 ¯ ∂ V¯2 R∗ V¯2 ∂ V¯2 V¯1 V¯2 R∗ ∂P ρnf + V1 ¯ + ∗ ¯ ¯ − ∗ ¯ = − ¯ ∂X ¯ ∂ t¯ ∂R R + R ∂X R +R R∗ + R " # 2 2¯ ∂ 2 V¯2 1 ∂ V¯2 R∗ V¯2 2R∗ ∂ V¯1 ∂ V2 +µef f + ¯ ¯2 + R ¯ + R∗ ∂ R ¯ + R ¯ + R∗ ¯2 − R ¯ + R∗ 2 ¯ + R∗ 2 ∂ X ∂R ∂X R
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# " ∗2 2 2 ¯2 R∗ ∂T ∂T ∂T V 1 ∂T R ∂ T ∂ T (ρC)nf + V¯1 ¯ + ∗ ¯ ¯ = κef f ¯2 ¯ 2 + R∗ + R ¯ ∂R ¯ + R∗ + R ¯ 2 ∂X ∂ t¯ ∂R R + R ∂X ∂R " 2 2 ! ¯ 2 # ∂ V¯1 R∗ ∂ V¯2 V¯1 ∂ V2 R∗ ∂ V¯1 V¯2 µef f 2 + + ¯ ¯ ∂X ¯ + R∗ + R ¯ ¯ + R∗ + R ¯ ∂X ¯ −R ¯ + R∗ ∂R R∗ + R ∂R (7)
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+Φ0 .
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The velocity and thermal slip conditions are ¯ ¯2 α n ˜ ∂ V V 2 1 ¯ = −H ¯ X, ¯ t¯ . V¯2 − + = 0, T = T at R (8) 1 2.5 ¯ ¯ + R∗ ∂R R (1 − φ) ¯ ∂ V2 V¯2 α1 n ˜ ¯ ¯=H ¯ X, ¯ t¯ . + = 0, T = T at R (9) V2 + 0 ¯ ¯ + R∗ R (1 − φ)2.5 ∂ R ¯ X ¯ whereas the flow in the channel The flow is considered unsteady in stationary frame R, can be treated as steady in moving frame (¯ r, x¯). The two frames are related by
¯ − ct¯, r¯ = R, ¯ v¯1 (¯ ¯ R, ¯ t¯ , v¯2 (¯ ¯ R, ¯ t¯ − c, x¯ = X x, r¯) = V¯1 X, x, r¯) = V¯2 X, ¯ R, ¯ t¯ , p¯ (¯ ¯ R, ¯ t¯ , T (¯ x, r¯) = T X, x, r¯) = P¯ X, 6
(10)
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and now equations. (4 − 7) yield ∂ ∂¯ v2 {(R∗ + r¯) v¯1 } + R∗ = 0, ∂¯ r ∂ x¯
(11)
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# ∂¯ v1 ∂¯ v1 R∗ (¯ v2 + c) ∂¯ v1 (¯ v2 + c)2 ∂ p¯ ρnf −c + v¯1 + − ∗ =− ∗ ∂ x¯ ∂¯ r R + r¯ ∂ x¯ R + r¯ ∂¯ r " # 2 2 ∂ 2 v¯1 v1 R∗ ∂ v¯1 1 ∂¯ v¯1 2R∗ ∂¯ v2 + , (12) +µef f + − − ∂¯ r2 r¯ + R∗ ∂¯ r r¯ + R∗ ∂ x¯2 (¯ r + R∗ )2 (¯ r + R∗ )2 ∂ x¯ ∂¯ v2 ∂¯ v2 R∗ (¯ v2 + c) ∂¯ v2 v¯1 (¯ v2 + c) R∗ ∂ p¯ ρnf −c + v¯1 + − =− ∗ ∗ ∗ ∂ x¯ ∂¯ r R + r¯ ∂ x¯ R + r¯ R + r¯ ∂ x¯ " # 2 2 2R∗ ∂¯ ∂ 2 v¯2 1 ∂¯ R∗ v¯2 v1 v2 ∂ v¯2 + +µef f + + − ∂¯ r2 r¯ + R∗ ∂¯ r r¯ + R∗ ∂ x¯2 (¯ r + R∗ )2 (¯ r + R∗ )2 ∂ x¯
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+g (ρβ)nf (T − T0 ) ,
(13)
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2 ∂T (¯ v2 + c) R∗ ∂T ∂ T 1 ∂T R∗2 ∂ 2 T ∂T (ρC)nf −c + v¯1 + + ∗ + = κef f ∂ x¯ ∂¯ r R∗ + r¯ ∂ x¯ ∂¯ r2 R + r¯ ∂¯ r (R∗ + r¯)2 ∂ x¯2 " 2 2 ! 2 # R∗ ∂¯ ∂¯ v1 v2 v¯1 ∂¯ v2 R∗ ∂¯ v1 (¯ v2 + c) + +µef f 2 + ∗ + + ∗ − ∗ ∂¯ r R∗ + r¯ ∂ x¯ R + r¯ ∂¯ r R + r¯ ∂ x¯ R + r¯
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+Φ0 . Defining
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¯ 2π¯ x r¯ v¯1 v¯2 2πa1 H , v1 = , v2 = , δ = ∗ , η = ± , ∗ , r = λ a1 c c λ a1 µbf Cnf ρca1 R∗ ct¯ 2πa21 p¯ p= , Re = , k= , Pr = ,t = ∗, cµbf λ∗ µbf a1 κbf λ µbf Cp a21 Φ0 a21 T − T0 , β0 = , Pr = , Ec = , θ= T1 − T0 (T1 − T0 ) κbf κbf Cnf (T1 − T0 ) a21 g (ρβ)nf (T1 − T0 ) Br = Pr Ec, Gr = , cµbf x=
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v1 = δ
k ∂ψ ∂ψ , v2 = − , r + k ∂x ∂r
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equation (11) is satisfied identically and other expressions for long wavelength and small
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Reynolds number yield
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dp = 0, dr ( !) k dp ∂ 1 ∂ 2 ψ 1 − ∂ψ 2 ∂r = (r + k) − 2 − r + k dx ∂r r+k (1 − φ)2.5 (r + k)2 ∂r !) ( (ρβ)nf −1 θ, +Gr 1 + φ (ρβ)bf κnf + 2κbf − 2φ (κbf − κnf ) ∂ 2 θ 1 ∂θ + κnf + 2κbf + 2φ (κbf − κnf ) ∂r2 r + k ∂r 2 2 Br ∂ ψ ∂ψ 1 + 1− + + β 0 = 0, r+k ∂r (1 − φ)2.5 ∂r2
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(18)
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where θ depicts the dimensionless temperature, δ the wave number, k the curvature param-
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eter, Re the Reynolds number, Pr the Prandtl number, Br the Brinkman number, Gr the
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η(x) = 1 + sin [x] , (22) α1 n ˜ indicates the velocity slip parameter. The dimensionless expression for a1
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where α =
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Grashof number and β 0 the source/sink parameter. The conditions now are ! α ∂ 2 ψ 1 − ∂ψ F ∂ψ ∂r − + = 1, θ = 1, at r = −η, ψ= , 2.5 2 2 ∂r ∂r r + k (1 − φ) ! α −F ∂ψ ∂ 2 ψ 1 − ∂ψ ∂r , + + = 1, θ = 0, at r = +η, ψ= 2 ∂r r+k (1 − φ)2.5 ∂r2
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pressure rise per wavelength ∆pλ∗ is
∆pλ∗ =
Z2π
dp dx. dx
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0
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It is worth mentioning that results of ref. [39] can be achieved in the absence of copper water nanoparticles, thermal Grashof number Gr, velocity slip parameter α and heat generation
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parameter β 0 .
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Solution methodology
Writing ψ = ψ 0 + Brψ 1 ..., dp dp0 dp1 = + Br ..., dx dx dx ∆pλ∗ = ∆p0λ∗ + Br∆p1λ∗ ..., θ = θ0 + Brθ1 ..., 8
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one has the following systems at the zeroth and first orders:
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Systems for zeroth order
∂ψ ∂ 2 ψ 0 1 − ∂r0 + ∂r2 r+k
−F0 ∂ψ 0 α ψ0 = , + 2 ∂r (1 − φ)2.5
Systems for first order
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∂ψ ∂ 2 ψ 0 1 − ∂r0 + ∂r2 r+k
= 1, θ0 = 1, at r = −η,
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= 1, θ0 = 0, at r = +η. (27)
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F0 ∂ψ 0 α ψ0 = , − 2 ∂r (1 − φ)2.5
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( !) ∂ψ 0 2 1 − 1 ∂ ∂ ψ k dp0 ∂r = (r + k)2 − 20 − − 2.5 2 r + k dx ∂r ∂r r + k (1 − φ) (r + k) !) ( (ρβ)nf −1 θ0 , +Gr 1 + φ (ρβ)bf κnf + 2κbf − 2φ (κbf − κnf ) ∂ 2 θ0 1 ∂θ0 + β 0 = 0, + κnf + 2κbf + 2φ (κbf − κnf ) ∂r2 r + k ∂r
(28)
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( !) ∂ψ 1 k dp1 1 ∂ ∂ 2ψ1 2 − = (r + k) − 2 − ∂r r + k dx ∂r r+k (1 − φ)2.5 (r + k)2 ∂r ( !) (ρβ)nf +Gr 1 + φ −1 θ1 , (ρβ)bf 1 ∂θ1 κnf + 2κf − 2φ (κbf − κnf ) ∂ 2 θ1 + κnf + 2κf + 2φ (κbf − κnf ) ∂r2 r + k ∂r 2 2 1 ∂ ψ0 1 ∂ψ 0 + + 1− = 0, r+k ∂r (1 − φ)2.5 ∂r2
F1 ∂ψ 1 α ψ1 = , − 2 ∂r (1 − φ)2.5 −F1 ∂ψ 1 α ψ1 = , + 2 ∂r (1 − φ)2.5
∂ψ
1 ∂ 2ψ1 ∂r − ∂r2 r+k
∂ψ
!
1 ∂ 2ψ1 ∂r − ∂r2 r+k
The solutions for zeroth and first order systems are
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= 0, θ1 = 0, at r = −η,
!
= 0, θ1 = 0, at r = +η.
(30)
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1 r ( (B −24k 2 + 3kr + 4r2 β 0 − 36A(4 + 4B (C1 − C2 ) 24A 6 dp0 dp0 + B1 )r + 2k( + B1 + B2 ) + rB2 ) + 2(2Bk 2 (4k + 3r) β 0 +( dx dx dp0 dp0 2 dp0 +3A(2k 2 + 4BC1 r + r + 2k(1 + 3BC1 − BC2 + r) dx dx dx −2 (B1 − B2 ))) log [k + r])
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ψ 0 = B3 −
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1 dp0 2 + Bkβ 0 ) (− B 3 Lr5 β 02 − 2B 2 Lr4 β 0 (10A 2 69120A 5 dx 4BLr3 r2 1 L1 − L2 + (L3 − L4 ) + r L5 + 720A2 (L6 + L7 ) + k+r 3 2 dp1 dp0 dp0 +40(−216A2 (L8 + (2k + r)(2 − 2B 2 L C2 ) + 8B 2 L C1 (3k + r)) dx dx dx +8AB 2 L L9 + L10 r + BC1 r2 + (6k + r) (9B2 − 9B1 ) β 0 + B 3 k 2 L(−2619k 2 +36kr + 4r2 )β 02 ) log [k + r] − 8 L11 + 720A2 (L12 − L13 ) log [k + r] dp0 r (2C2 − 2C1 ) +720BL(12A2 ((k + r)) L14 + B(L15 + 2k dx dp0 2 +C1 r ) + 2B 2 (2C22 r − C1 C2 (9k + r) + C12 (17k + r))) + 2ABk 2 (L16 dx dp0 dp0 +(144BC1 − 36BC2 − 2k +3 r)r)β 0 + B 2 k 4 (79k + 63r)β 02 ) log [k + r]2 dx dx 2 2 0 −960B L 2AC1 + k β (3A (L17 + 4Br (2C1 − C2 )) + Bk 2 (7k + r) β 0 ) log [k + r]3 2 +1440B 3 L (k + r) 2AC1 + k 2 β 0 log [k + r]4 ), (32)
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ψ 1 = B6 +
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(36A1 + A2 ) log [η + k] dp0 = , dx 36A (−η (η + 2k) + (η 2 + 2ηk + 2k 2 ) log [η + k])
(33)
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dp1 4 = (A3 + A4 − A5 + A6 − A7 + A8 2 dx η(η + 2k) − (η + 2ηk + 2k 2 ) log [η + k] B4 B5 −A9 + A10 + (− + + B 3 ηL (−3C1 + 3C2 )2 + A11 + A12 log [η + k] 2 2 B 3 kL + 43C12 − 31C1 C2 + 8C22 ) log [η + k] − A13 log [η + k] 4 0 0 Bη(8C3 − L dp (−8B1 + 8B2 + k(8 + 3k dp ))) dx dx + log [η + k] 8 B 2 ηLβ 0 + A14 log [η + k] + A15 log [η + k] + A16 216A BL(12A2 (2B 2 A17 + A18 + A19 )) log [η + k]2 − 96A2 2 2 0 B L(2AC1 + k β ) A21 log [η + k]4 3 + A log [η + k] − ), (34) 20 72A2 48A2 θ 0 = C2 −
r (2k + r) β 0 − 2 (k 2 β 0 + 2AC1 ) log [k + r] 4A 10
(35)
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θ 1 = C4 −
1 dp0 2 4 02 2 3 0 + 3Bkβ 0 ) (3B Lr β + 4B Lr β (16A 6912A2 dx
576BL (4A (C1 + C2 ) + 3k 2 β 0 )(A(6 (B2 − B1 ) + 3k(2 + 2B (C1 − C2 ) k+r dp0 dp0 +k ) + 2Bk 3 β 0 ) + (48L(A(6 (B2 − B1 ) + 3k(2 + 2B (C1 − C2 ) + k ) dx dx dp0 2 dp0 0 +2Bk 3 β 0 )))/ (k + r)2 ) + 6Lr2 (72A2 )β + 16AB(6BC1 − 3BC2 + 2k dx dx dp0 dp0 (24BC1 − 8BC2 + k ) + 16AB(6 (B1 − B2 ) +39B 2 k 2 β 02 ) + 12Lr(72A2 dx dx dp0 144BL +k(−6 + 3BC2 + 43k ))β 0 + 5B 2 k 3 β 02 ) + (2AC1 + k 2 β 0 ) dx k+r dp0 dp0 dp0 (−24A(2 (B1 − B2 ) − 2k + 2Bk (C2 − C1 ) − k 2 +k r + r2 ) dx dx dx −B(−16k 3 + 2k 2 r + 3kr2 + r3 )β 0 ) log [k + r] − 12(16ABkL(6 (B1 − B2 ) dp0 dp0 +k(−6 + 3BC2 + 43k ))β 0 + 5B 2 k 4 Lβ 02 + 72A2 (8B(3C1 − C2 )kL dx dx 2 dp 0 + 8C3 )) log [k + r] + 72L(24A2 (2B 2 (C1 − C1 )2 +k 2 L dx dp0 dp0 dp0 +2B (C2 − C1 ) k − (2 (B2 − B1 ) + k(2 + k )) + 8ABk 2 (3B (C1 − C2 ) dx dx dx dp0 0 −2k )β ) + 3B 2 k 4 β 02 ) log [k + r]2 − 288B 2 L(2AC1 + k 2 β 0 )(4A (C1 − C2 ) dx +k 2 β 0 ) log [k + r]3 + 144B 2 L(2AC1 + k 2 β 0 )4 ), (36)
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+
where the involved values are given in Appendix.
Discussion
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The prime goal here is to examine the influence of first order velocity slip parameter α, nanoparticle volume fraction φ, Grashof number Gr and curvature parameter on pressure
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rise ∆pλ∗ , pressure gradient dp/dx and stream function ψ. Plots for temperature field are prepared for various values of thermal slip parameter γ, nanoparticle volume fraction φ, heat generation/absorption parameter β 0 and Brinkman number Br. Variation in heat transfer
rate −
κef f 0 θ κf
(η) is shown through bar charts for thermal slip parameter γ, nanoparticle vol-
ume fraction φ and Brinkman number Br.
4.1
Pumping and trapping
To discuss the impact of different pertinent parameters on the basic quantities of peristaltic motion such as pumping and trapping, we have prepared Figs. 2-12. Influence of first 11
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order velocity slip parameter α, nanoparticle volume fraction φ, Grashof number Gr and curvature parameter k on pressure rise ∆pλ∗ is exhibited in the Figs. 2-5. The discussion for pressure are made in three different regions which are known as backward , peristaltic and retrograde pumping regions. It is revealed from Fig. 2 that pressure rise ∆pλ∗ decreases in the backward (∆pλ∗ > 0, Θ < 0) and peristaltic (∆pλ∗ , Θ > 0) pumping region and it
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rises in the retrograde (∆pλ∗ < 0, Θ > 0) pumping region for larger first order velocity slip parameter α. From Fig. 3 it is noted that impact of nanoparticle volume fraction φ on pressure rise ∆pλ∗ is similar to that of α. It is noted here that ∆pλ∗ is larger for base fluid (water) and small for nanoparticles (copper) in backward and peristaltic pumping regions where it is reverse in retrograde pumping region. Fig. 4 illustrated that pressure
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rise ∆pλ∗ enhances for larger Grashof number Gr. Fig. 5 discloses the effect of curvature parameter k on pressure rise ∆pλ∗ . This Fig. describe that for larger curvature the pressure rise enhances in backward (∆pλ∗ > 0, Θ < 0) and peristaltic (∆pλ∗ , Θ > 0) pumping regions where it decreases in retrograde pumping region (∆pλ∗ < 0, Θ > 0). Figs. 6-9 are made to see the behavior of pressure gradient dp/dx for different values of
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first order velocity slip parameter α, nanoparticle volume fraction φ, Grashof number Gr and curvature parameter k. Fig. 6 elucidates that pressure gradient enhances for larger first order
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velocity slip parameter α. Fig. 7 shows the impact of nanoparticle volume fraction φ on pressure gradient. It depicts that dp/dx has a sinusoidal behavior and it attains maximum
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value when the maximum occlusion is provided by the peristaltic walls. In occlude portion of the channel the pressure gradient enhances when nanoparticle volume fraction is increased.
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It is due to the fact that resistance in the flow field provided by the insertion of nanoparticles becomes large when the channel is occlude. Impact of Grashof number on pressure gradient
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is similar as reported for α and φ (see Fig. 8). Fig. 9 describe that the pressure gradient decreases when we shift from curved to planer channel (i.e. larger k). Influence of first order velocity parameter α, nanoparticle volume fraction φ and Grashof
number Gr on trapping are disclosed in Figs. 10-12. Impact of velocity slip parameter α on streamlines is depicted in Fig. 10. It is seen that when the effects of velocity slip parameter enhances the size of trapped bolus reduces and bolus disappeared when (α = 0.3).
Fig. 11 illustrates that size of trapped bolus decreases with the addition of nanoparticle volume fraction φ. It is important to note that nanoparticles (copper) generates resistance for streamlines. Fig. 12 depicts that the size of trapped bolus enhances for larger Grashof 12
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number Gr.
4.2
Velocity distribution
Characteristics of axial velocity for different values of first order velocity parameter α, nanoparticle volume fraction φ, Grashof number Gr and curvature parameter k are shown
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in Figs. 13-16. Fig. 13 portrays the effect of α on axial velocity. This Fig. elaborates that axial velocity is minimum at center of the channel and maximum in the vicinity of the channel walls. Fig. 14 exhibits that nanoliquids with low concentration of nanoparticles possesses smaller magnitude of the axial velocity at center. Hence larger nanoparticle volume fraction provides more resistance to the flow field. However in the vicinity of the channel walls such
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observation remains invalid which is basically due to velocity slip effects. Figs 15 delineates that axial velocity enhances at the lower wall of the channel and it decreases near the upper wall of the channel for different values of Grashof number Gr. Fig. 16 shows that axial velocity is maximum at the center of the channel whereas it decreases near the channel walls
Temperature distribution
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when curvature parameter k rises.
Effects of nanoparticle volume fraction φ, heat generation/absorption parameter β 0 , Brinkman
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number Br and curvature parameter on temperature are shown in Figs. 17-20. Fig. 17 depicts the variation in temperature θ for increasing values of φ. It is illustrated from this plot
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that temperature of the nanofluid decreases with an addition of the nanoparticle volume fraction. This is a clear evidence that heat produced by the heat source is quickly transferred to the walls and consequently the temperature of the fluid decreases. High thermal
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conductivity of nanoparticles plays an important role in fast dissipation of the fluid temperature. This confirms the use of copper nanoparticles in different types of coolants. Fig. 18 shows that temperature is an increasing function of heat generation/absorption parameter β 0 . Fig. 19 portrays the impact of Brinkman number Br on temperature. It illustrates that temperature of the nanofluid enhances due to the loss of kinetic energy when fluid particles collide with each other. Temperature of the nanofluid decreases for larger values of curvature parameter k (see Fig. 20).
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5
Final outcomes
Here we investigated the mixed convection effects in peristalsis of copper-water nanofluid with first order velocity and thermal slip condition in curved configuration. The important achievements of the present study are summarized as follows:.
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• Impact of velocity slip parameter α and nanoparticle volume fraction on pressure is qualitatively similar.
• It is observed that in the occluded part of the channel the pressure gradient attains its maximum value in the presence of nanoparticle volume fraction φ.
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• Addition of nanoparticles (copper) trapping is less likely when compared with basefluid (water).
• Velocity slip parameter α have dominating effects on axial velocity.
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• Larger viscous dissipative heat cause an increase in the temperature. • It is seen that magnitude of the axial velocity for basefluid is maximum and it is
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minimum when φ is enhanced.
Table 1: Numerical values of the thermophysical properties. Basefluid(water) Nanoparticles(Copper)
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Property
997.1
8933
Thermal conductivity (W/mK)
0.613
401
Specific heat (J/kgK)
4179
385
Thermal expansion coefficient (1/k) × 10−6
210
16.65
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Density (kg/m3 )
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6
Appendix
We here include: L1 = 160BL(3A(−2B1 + 2B2 + k(2 + 2BC1 − 2BC2 + k
dp0 )) + 2Bk 3 β 0 )2 , dx
dp0 2 dp0 0 )β + 383B 2 k 2 β 02 ), + 20AB(44BC1 − 12BC2 + 3k dx dx dp0 L3 = −80AB 2 L(−72B1 + 72B2 + k(72 + 106BC1 − 78BC2 − 665k ))β 0 , dx dp0 dp0 2 dp1 L4 = 3163B 3 k 3 Lβ 02 + 720A2 (12B 2 (15C1 − 4C2 )L − BkL + 48( + B4 + B5 ))), dx dx dx dp0 ))β 0 + 146053B 3 k 4 Lβ 02 , L5 = 80AB 2 kL(72B1 − 72B2 − k(72 − 8614BC1 + 2562BC2 + 325k dx dp0 L6 = 192B 3 (6C12 − 4C1 C2 + C22 )L − 36B 2 (3C1 − 4C2 )kL , dx dp0 dp0 dp1 L7 = B(96C3 − 96C4 − L (−192B1 + 192B2 + k(192 + 89k ))) + 48k( + B4 + B5 ), dx dx dx dp0 dp0 (−8B1 + 8B2 + k(8 + 3k ))), L8 = 8B 3 (−3C1 + C2)2 L + B(8C3 − L dx dx dp0 dp0 L9 = 54k 2 − 1590BC1 k 2 + 504BC2 k 2 − 258k 3 , L10 = 9k + 12BC1 k − 9BC2 k − 90k 2 , dx dx dp0 ))β 0 + 15311B 3 k 5 Lβ 02 , L11 = 10AB 2 k 2 L(648B1 − 648B2 + k(−648 + 7480BC1 − 2400BC2 + 411k dx L12 = 3B 3 (43C12 − 31C1 C2 + 8C22 )kL + 3B 2 L(B1 (3C1 + 2C2 ) − B2 (3C1 + 2C2 ) dp0 dp0 −k(C1 (3 − 6k ) + C2 (2 + k ))), dx dx dp0 dp0 dp1 (−18B1 + 18B2 + k(18 + 7k ))) + 6k 2 − 6B4 + 6B5 , L13 = Bk(−18C3 + 6C4 + L dx dx dx dp0 dp0 L14 = −2 (−2B1 + 2B2 + k(2 + k )), dx dx dp0 L15 = −6B1 C1 + 6B2 C1 − 4B1 C2 + 4B2 C2 + 6C1 k + 4C2 k + 6C2 k 2 , dx dp0 , L16 = −24B1 + 24B2 + 24k + 180BC1 k − 52BC2 k + 7k 2 dx dp0 L17 = 2B1 − 2B2 − 2k + 6BC1 k − 2BC2 k − k 2 , dx
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L2 = (360A2
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A1 = (4B3 + 2F0 + η(4 + 4BC1 − 4BC2 + B1 η + B2 η + 2B1 k + 2B2 k)), A2 = Bη(−4η 2 − 3ηk + 42k 2 )β 0 + 24(3A(B1 − B2 − 2BC1 η − k
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−3BC1 k + BC2 k) − Bk 2 (3η + 4k)β 0 , B4 ηk B5 ηk F1 B4 η 2 1 − − B5 η 2 − − − 2B 3 (6C12 − 4C1 C2 + C22 )ηL, A3 = −B6 − 2 4 4 2 2 2 0 0 0 3B 2 (3C1 − 4C2 )ηkL dp Bη 2 kL dp B 2 (15C1 − 4C2 )η 2 L dp dx dx dx A4 = − + + , 16 8 192 0 0 Bη(96C3 − 96C4 − L dp (−192B1 + 192B2 + k(192 + 89k dp ))) dx dx A5 = , 96 0 (B 2 η 2 L(−72B1 + 72B2 + k(72 + 106BC1 − 78BC2 − 665k dp ))β 0 ) dx A6 = , 1728A 0 (B 2 ηkL(72B1 − 72B2 − k(72 − 8614BC1 + 2562BC2 + 325k dp ))β 0 ) dx A7 = , 864A 0 + Bkβ 0 ) B 3 η 5 Lβ 02 3163B 3 η 2 k 3 Lβ 02 146053B 3 ηk 4 Lβ 02 B 2 η 4 Lβ 0 (10A dp dx + − + , A8 = 172800A2 138240A2 69120A2 34560A2 0 BL(3A(−2B1 + 2B2 + k(2 + 2BC1 − 2BC2 + k dp )) + 2Bk 3 β 0 )2 dx A9 = , 432A2 (η + k) 2
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0 0 Bη 3 L(360A2 dp + 20AB(44BC1 − 12BC2 + 3k dp )β 0 + 383B 2 k 2 β 02 ) dx dx A10 = , 51840A2 0 L(−C2 (η + 2k) + 4C1 (η + 3k)) dp log [η + k] dx A11 = , 2 4B η 0 0 ) + C2 (2 + k dp ))) B 2 L(B1 (3C1 + 2C2 ) − B2 (3C1 + 2C2 ) − k(C1 (3 − 6k dp dx dx , A12 = 4 0 0 Bk(−18C3 + 6C4 + L dp (−18B1 + 18B2 + k(18 + 7k dp ))) dx dx A13 = , 12 A14 = (BC1 η 2 + 9ηk + 12BC1 ηk − 9BC2 ηk + 54k 2 − 1590BC1 k 2 + 504BC2 k 2 dp0 dp0 − 258k 3 ), −9B1 (η + 6k) + 9B2 (η + 6k) − 90ηk 2 dx dx 0 (B 2 k 2 L(648B1 − 648B2 + k(−648 + 7480BC1 − 2400BC2 + 411k dp ))β 0 dx A15 = , 864A 15311B 3 k 5 Lβ 02 log [η + k] B 3 ηk 2 (4η 2 + 36ηk − 2619k 2 )Lβ 02 log [η + k] A16 = − , 8640A2 1728A2 A17 = (2C22 η − C1 C2 (8η + 9k) + C12 (14η + 17k)), dp0 A18 = B(−6B1 C1 + 6B2 C1 − 4B1 C2 + 4B2 C2 + 6C1 k + 4C2 k + C1 η 2 dx dp dp0 dp0 dp dp0 0 0 −2C1 ηk + 4C2 ηk + 6C2 k 2 ) − 2(η + k) (−2B1 + 2B2 + k(2 + k )), dx dx dx dx dx A19 = 2ABk 2 (−24B1 + 24B2 + 144BC1 η − 36BC2 η + 24k + 180BC1 k − 52BC2 k dp0 0 + 3η 2 − 2ηk + 7k 2 )β + B 2 k 4 (63η + 79k)β 02 , dx dp0 ) A20 = (3A(2B1 − 2B2 + 8BC1 η − 4BC2 η − 2k + 6BC1 k − 2BC2 k − k 2 dx 2 +Bk 2 (9η + 7k)β 0 ), A21 = (B 3 (η + k)L 2AC1 + k 2 β 0 21
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where B1 − B6 and C1 − C4 can be calculated through algebraic computations.
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Fig. 1. Schematic diagram.
Fig. 2. α variation for ∆pλ∗ when = 0.5, Br = 0.1, k = 2.5, γ = 0.1, φ = 0.1, Gr = 5, β 0 = 3.
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Fig. 3. φ variation for ∆pλ∗ when
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= 0.5, Br = 0.1, k = 2.5, γ = 0.1, α = 0.1, Gr = 5, β 0 = 3.
Fig. 4. Gr variation for ∆pλ∗ when = 0.5, Br = 0.1, k = 2.5, γ = 0.1, φ = 0.1, α = 0.1, β 0 = 3.
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Fig. 5. k variation for ∆pλ∗ when
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= 0.5, Br = 0.1, α = 0.1, γ = 0.1, φ = 0.1, Gr = 5, β 0 = 3.
Fig. 6. α variation for
dp dx
when = 0.5, Br = 0.1, k = 2.5, γ = 0.1, φ = 0.1, Gr = 5, β 0 = 3.
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when = 0.5, Br = 0.1, k = 2.5, γ = 0.1, α = 0.1, Gr = 5, β 0 = 3.
dp dx
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Fig. 7. φ variation for
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Fig. 8. Gr variation for
dp dx
when = 0.5, Br = 0.1, k = 2.5, γ = 0.1, α = 0.1, φ = 0.1, β 0 = 3.
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dp dx
when = 0.5, Br = 0.1, α = 0.1, γ = 0.1, φ = 0.1, Gr = 5, β 0 = 3.
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Fig. 9. k variation for
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Fig. 10. Influence of α on streamlines when = 0.5, Br = 0.1, Θ = 1.5, φ = 0.1, γ = 0.1, k = 2.5, Gr = 5, β 0 = 3.
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Fig. 11. Influence of φ on streamlines when
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= 0.5, Br = 0.1, Θ = 1.5, α = 0.1, γ = 0.1, k = 2.5, Gr = 5, β 0 = 3.
Fig. 12. Influence of Gr on streamlines when = 0.5, Br = 0.1, Θ = 1.5, α = 0.1, γ = 0.1, φ = 0.1, k = 2.5, β 0 = 3. 27
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Fig. 13. Influence of α on axial velocity v2 when
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= 0.5, x = 0.0, Br = 0.1, Θ = 1.5, k = 2.5, γ = 0.1, φ = 0.1, Gr = 5, β 0 = 3.
Fig. 14. Influence of φ on axial velocity v2 when
= 0.5, x = 0.0, Br = 0.1, Θ = 1.5, k = 2.5, γ = 0.1, α = 0.1, Gr = 5, β 0 = 3.
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Fig. 15. Influence of Gr on axial velocity v2 when
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= 0.5, x = 0.0, Br = 0.1, Θ = 1.5, k = 2.5, γ = 0.1, φ = 0.1, α = 0.1, β 0 = 3.
Fig. 16. Influence of k on axial velocity v2 when
= 0.5, x = 0.0, Br = 0.1, Θ = 1.5, φ = 0.1, γ = 0.1, α = 0.1, Gr = 5, β 0 = 3.
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Fig. 17. φ variation for θ when
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= 0.5, x = 0.0, Br = 0.1, Θ = 1.5, k = 2.5, γ = 0.1, α = 0.1, Gr = 5, β 0 = 3.
Fig. 18. β 0 variation for θ when
= 0.5, x = 0.0, Br = 0.1, Θ = 1.5, k = 2.5, Gr = 5, φ = 0.1, α = 0.1, γ = 0.1.
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Fig. 19. Br variation for θ when
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Fig. 20. k variation for θ when
= 0.5, x = 0.0, Θ = 1.5, Br = 0.1, γ = 0.1, φ = 0.1, α = 0.1, Gr = 5, β 0 = 3.
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