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Research Papers: Micro/Nanoscale Heat Transfer

Unsteady Flow of Carreau Fluid in a Suspension of Dust and Graphene Nanoparticles With Cattaneo–Christov Heat Flux

[+] Author and Article Information
S. Mamatha Upadhya

Department of Mathematics,
Garden City College of Science
and Management Studies,
16th KM., Old Madras Road,
Bangalore 560049, Karnataka, India
e-mail: mamathasupadhya@gmail.com

Mahesha

Department of Mathematics,
University BDT College of Engineering,
Davangere 577004, Karnataka, India
e-mail: maheshubdt@gmail.com

C. S. K. Raju

Department of Mathematics,
GITAM School of Technology,
Bangalore 561203, India
e-mail: sivaphd90@gmail.com

1Corresponding author.

Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF HEAT TRANSFER. Manuscript received July 4, 2017; final manuscript received March 26, 2018; published online May 22, 2018. Assoc. Editor: Thomas Beechem.

J. Heat Transfer 140(9), 092401 (May 22, 2018) (9 pages) Paper No: HT-17-1394; doi: 10.1115/1.4039904 History: Received July 04, 2017; Revised March 26, 2018

This is a theoretical exploration of the magnetohydrodynamic Carreau fluid in a suspension of dust and graphene nanoparticles. Graphene is a two-dimensional single-atom thick carbon nanosheet. Due to its high thermal conductivity, electron mobility, large surface area, and stability, it has remarkable material, electrical, optical, physical, and chemical properties. In this study, a simulation is performed by mixing of graphene + water and graphene + ethylene glycol into dusty non-Newtonian fluid. Dispersion of graphene nanoparticles in dusty fluids finds applications in biocompatibility, bio-imaging, biosensors, detection and cancer treatment, in monitoring stem cells differentiation, etc. Graphene + water and graphene + ethylene glycol mixtures are significant in optimizing the heat transport phenomena. Initially arising set of physical governing partial differential equations are transformed to ordinary differential equations (ODEs) with the assistance of similarity transformations. Consequential highly nonlinear ODEs are solved numerically through Runge–Kutta Fehlberg scheme. The computational results for nondimensional temperature and velocity profiles are presented through graphs. Additionally, the numerical values of friction factor and heat transfer rate are tabulated numerically for various physical parameter obtained. We also validated the present results with previous published study and found to be highly satisfactory. The formulated model in this study reveals that heat transfer rate and wall friction is higher in mixture of graphene + ethylene glycol when compared to graphene + water.

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References

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Figures

Grahic Jump Location
Fig. 1

Physical model representing the flow problem

Grahic Jump Location
Fig. 2

Influence of ϕ on f′(ζ) and F′(ζ)

Grahic Jump Location
Fig. 3

Influence of M on f′(ζ) and F′(ζ)

Grahic Jump Location
Fig. 4

Influence of βv on f′(ζ) and F′(ζ)

Grahic Jump Location
Fig. 5

Influence of A on f′(ζ) and F′(ζ)

Grahic Jump Location
Fig. 6

Influence of We on f′(ζ) and F′(ζ)

Grahic Jump Location
Fig. 7

Influence of ϕ on θ(ζ) and θp(ζ)

Grahic Jump Location
Fig. 8

Influence of R on θ(ζ) and θp(ζ)

Grahic Jump Location
Fig. 9

Influence of M on θ(ζ) and θp(ζ)

Grahic Jump Location
Fig. 10

Influence of Λ on θ(ζ) and θp(ζ)

Grahic Jump Location
Fig. 11

Influence of Ec on θ(ζ) and θp(ζ)

Grahic Jump Location
Fig. 12

Influence of βv on θ(ζ) and θp(ζ)

Grahic Jump Location
Fig. 13

Influence of βt on θ(ζ) and θp(ζ)

Grahic Jump Location
Fig. 14

Influence of A on θ(ζ) and θp(ζ)

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