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Research Papers

A Similarity Solution for Mixed-Convection Boundary Layer Nanofluid Flow on an Inclined Permeable Surface

[+] Author and Article Information
Masoud Ziaei-Rad

Department of Mechanical Engineering,
Faculty of Engineering,
University of Isfahan,
Hezar Jerib Avenue,
Isfahan 81746-73441, Iran
e-mail: m.ziaeirad@eng.ui.ac.ir

Abbas Kasaeipoor

Department of Mechanical Engineering,
Faculty of Engineering,
University of Isfahan,
Isfahan 81746-73441, Iran
e-mail: a.kasaeipoor@gmail.com

Mohammad Mehdi Rashidi

Shanghai Key Lab of Vehicle Aerodynamics
and Vehicle Thermal Management Systems,
Tongji University,
4800 Cao An Road,
Jiading, Shanghai 201804, China;
ENN-Tongji Clean Energy Institute
of Advanced Studies,
Shanghai 200072, China
e-mail: mm_rashidi@tongji.edu.cn

Giulio Lorenzini

Department of Engineering and Architecture,
University of Parma,
Parco Area delle Scienze 181/A,
Parma 43124, Italy
e-mail: giulio.lorenzini@unipr.it

1Corresponding author.

Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF THERMAL SCIENCE AND ENGINEERING APPLICATIONS. Manuscript received September 9, 2016; final manuscript received December 6, 2016; published online March 7, 2017. Assoc. Editor: Ali J. Chamkha.

J. Thermal Sci. Eng. Appl 9(2), 021015 (Mar 07, 2017) (9 pages) Paper No: TSEA-16-1258; doi: 10.1115/1.4035733 History: Received September 09, 2016; Revised December 06, 2016

This paper concerns with calculation of heat transfer and pressure drop in a mixed-convection nanofluid flow on a permeable inclined flat plate. Solution of governing boundary layer equations is presented for some values of injection/suction parameter (f0), surface angle (γ), Galileo number (Ga), mixed-convection parameter (λ), volume fraction (φ), and type of nanoparticles. The numerical outcomes are presented in terms of average skin friction coefficient (Cf) and Nusselt number (Nu). The results indicate that adding nanoparticles to the base fluid enhances both average friction factor and Nusselt number for a wide range of other effective parameters. We found that for a nanofluid with φ = 0.6, injection from the wall (f0 = −0.2) offers an enhancement of 30% in Cf than the base fluid, while this growth is about 35% for the same case with wall suction (f0 = 0.2). However, increasing the wall suction will linearly raise the heat transfer rate from the surface, similar for all range of nanoparticles volume fraction. The computations also showed that by changing the surface angle from horizontal state to 60 deg, the friction factor becomes 2.4 times by average for all φ's, while 25% increase yields in Nusselt number for the same case. For assisting flow, there is a favorable pressure gradient due to the buoyancy forces, which results in larger Cf and Nu than in opposing flows. We can also see that for all φ values, enhancing Ga/Re2 parameter from 0 to 0.005 makes the friction factor 4.5 times, while causes 50% increase in heat transfer coefficient. Finally, we realized that among the studied nanoparticles, the maximum influence on the friction and heat transfer belongs to copper nanoparticles.

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Figures

Grahic Jump Location
Fig. 1

A schematic of mixed-convection nanofluid flow over an inclined permeable plate

Grahic Jump Location
Fig. 2

Velocity profiles of pure-fluid mixed-convection flow over a horizontal permeable surface for different injection/suctionparameters (n = 0.01, λ = −0.03, and Pr = 0.7), a comparison with Ref. [10]

Grahic Jump Location
Fig. 3

Variation of wall temperature gradient with mixed-convection parameter for a pure-fluid flow over a horizontal permeable surface (f0 = 0.2, n = 0.02, and Pr = 0.7), a comparison with Ref. [10]

Grahic Jump Location
Fig. 4

Average skin friction coefficient versus injection/suctionparameters for water–Cu nanofluid mixed-convection flow over an inclined surface with different concentrations of Cu nanoparticles (λ = 0.04, γ = 30, and Ga/Re2 = 0.001)

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Fig. 13

Average Nusselt number versus φ for different nanofluids in a mixed-convection flow over an inclined permeable surface (λ = 0.04, f0 = 0.2, γ = 30, and Ga/Re2 = 0.001)

Grahic Jump Location
Fig. 12

Average skin friction coefficient versus φ for different nanofluids in a mixed-convection flow over an inclined permeable surface (λ = 0.04, f0 = 0.2, γ = 30, and Ga/Re2 = 0.001)

Grahic Jump Location
Fig. 11

Average Nusselt number versus Ga/Re2 for water–Cu nanofluid mixed-convection flow over an inclined permeable surface with different Cu concentrations (λ = 0.04, f0 = 0.2, and γ = 30)

Grahic Jump Location
Fig. 10

Average skin friction coefficient versus Ga/Re2 for water–Cu nanofluid mixed-convection flow over an inclined permeable surface with different Cu concentrations (λ = 0.04, f0 = 0.2, and γ = 30)

Grahic Jump Location
Fig. 9

Average Nusselt number versus surface angle for water–Cu nanofluid mixed-convection flow over an inclined permeable surface with different Cu concentrations (λ = 0.04, f0 = 0.2, and Ga/Re2 = 0.001)

Grahic Jump Location
Fig. 8

Average skin friction coefficient versus surface angle for water–Cu nanofluid flow over an inclined permeable surfacewith different Cu concentrations (λ = 0.04, f0 = 0.2, and Ga/Re2 = 0.001)

Grahic Jump Location
Fig. 7

Average Nusselt number versus mixed-convection parameter for water–Cu nanofluid flow over an inclined permeable surface with different Cu concentrations (f0 = 0.2, γ = 30, and Ga/Re2 = 0.001)

Grahic Jump Location
Fig. 6

Average skin friction coefficient versus mixed-convection parameter for water–Cu nanofluid flow over an inclined permeable surface with different Cu concentrations (f0 = 0.2, γ = 30, and Ga/Re2 = 0.001)

Grahic Jump Location
Fig. 5

Average Nusselt number versus injection/suction parameters for water–Cu nanofluid mixed-convection flow over an inclined surface with different concentrations of Cu nanoparticles (λ = 0.04, γ = 30, and Ga/Re2 = 0.001)

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