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Research Papers: Forced Convection

Second Law Analysis of Heat and Mass Transfer of Nanofluids Along a Plate With Prescribed Surface Heat Flux

[+] Author and Article Information
Waqar A. Khan

Department of Mechanical
and Mechatronics Engineering,
University of Waterloo,
Waterloo, ON N2L 3G1, Canada
e-mail: wkhan_2000@yahoo.com

Richard Culham

Department of Mechanical
and Mechatronics Engineering,
University of Waterloo,
Waterloo, ON N2L 3G1, Canada

A. Aziz

Life Fellow ASME
Distinguished Research Professor
Department of Mechanical Engineering,
Gonzaga University,
E. 502 Boone Avenue,
Spokane, WA 99258

1Corresponding author.

Contributed by the Heat Transfer Division of ASME for publication in the JOURNAL OF HEAT TRANSFER. Manuscript received August 21, 2014; final manuscript received March 16, 2015; published online April 21, 2015. Assoc. Editor: Giulio Lorenzini.

J. Heat Transfer 137(8), 081701 (Aug 01, 2015) (9 pages) Paper No: HT-14-1556; doi: 10.1115/1.4030246 History: Received August 21, 2014; Revised March 16, 2015; Online April 21, 2015

A model based on the works of Buongiorno, which includes the effects of Brownian motion and thermophoresis, is used to develop the governing equations for convection in nanofluids. The analysis includes examples with water and ethylene glycol as the base fluids and nanoparticles of Cu and Al2O3. An assumption of zero nanoparticle flux is used at the surface of the plate to make the model more physically realistic. The model accounts for the effects of both Brownian motion and thermophoresis in the mass boundary condition. Using suitable transformations, the governing partial differential equations are converted into ordinary differential equations which are solved numerically. The dimensionless velocity, temperature, and concentration gradients are used in the second law analysis to determine heat and mass transfer rates. It is shown that the dimensionless entropy generation rate strongly depends upon the solid volume fraction of the nanoparticles, local Reynolds number, and group parameters.

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Figures

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Fig. 1

Variation of dimensionless entropy generation rates with transverse distance inside boundary layer for (a) water-based and (b) ethylene glycol-based nanofluids

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Fig. 2

Effects of solid volume fraction of different nanoparticles and group parameter on dimensionless entropy generation rates for (a) water-based and (b) ethylene glycol-based nanofluids

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Fig. 3

Effects of solid volume fraction of different nanoparticles and group parameter on irreversibility ratio for (a) water-based and (b) ethylene glycol-based nanofluids

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Fig. 4

Effects of solid volume fraction of different nanoparticles and group parameter on Bejan number for (a) water-based and (b) ethylene glycol-based nanofluids

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Fig. 5

Variation of dimensionless entropy generation rates with local Reynolds number and heat flux variation parameter for (a) water-based and (b) ethylene glycol-based nanofluids

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Fig. 6

Variation of total dimensionless entropy generation rate with local Reynolds number and heat flux variation parameter for (a) water-based and (b) ethylene glycol-based nanofluids

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Fig. 7

Variation of irreversibility ratio with local Reynolds number and heat flux variation parameter for (a) water-based and (b) ethylene glycol-based nanofluids

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Fig. 8

Variation of Bejan number with local Reynolds number and heat flux variation parameter for (a) water-based and (b) ethylene glycol-based nanofluids

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Fig. 9

Variation of total dimensionless entropy generation rate with mass transfer parameters for (a) water-based and (b) ethylene glycol-based nanofluids

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Fig. 10

Variation of Bejan number with mass transfer parameters for (a) water-based and (b) ethylene glycol-based nanofluids

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