Preprint Article Version 1 NOT YET PEER-REVIEWED

Further Investigation on Laminar Forced Convection of Nanofluid Flows in a Uniformly Heated Pipe Using Direct Numerical Simulations

  1. Université de Sherbrooke, Faculté de génie, Département de génie mécanique, 2500 Boulevard de l’Université, Sherbrooke, QC J1K 2R1, Canada
Version 1 : Received: 22 September 2016 / Approved: 23 September 2016 / Online: 23 September 2016 (08:36:48 CEST)

A peer-reviewed article of this Preprint also exists.

Sekrani, G.; Poncet, S. Further Investigation on Laminar Forced Convection of Nanofluid Flows in a Uniformly Heated Pipe Using Direct Numerical Simulations. Appl. Sci. 2016, 6, 332. Sekrani, G.; Poncet, S. Further Investigation on Laminar Forced Convection of Nanofluid Flows in a Uniformly Heated Pipe Using Direct Numerical Simulations. Appl. Sci. 2016, 6, 332.

Journal reference: Appl. Sci. 2016, 6, 332
DOI: 10.3390/app6110332

Abstract

In the present paper, laminar forced convection nanofluid flows in a uniformly heated horizontal tube were revisited by direct numerical simulations. Single and two-phase models were employed with constant and temperature-dependent properties. Comparisons with experimental data showed that the mixture model performs better than the single-phase model in the all cases studied. Temperature-dependent fluid properties also resulted in a better prediction of the thermal field. A particular attention was paid to the grid arrangement. The two-phase model was used then confidently to investigate the influence of the nanoparticle size on the heat and fluid flow with a particular emphasis on the sedimentation process. Four nanoparticle diameters were considered: 10, 42, 100 and 200 nm for both copper-water and alumina/water nanofluids. For the largest diameter dnp = 200 nm, the Cu nanoparticles were more sedimented by around 80 %, while the Al2O3 nanoparticles sedimented only by 2.5 %. Besides, it was found that increasing the Reynolds number improved the heat transfer rate, while it decreased the friction factor allowing the nanoparticles to stay more dispersed in the base fluid. The effect of nanoparticle type on the heat transfer coefficient was also investigated for six different water-based nanofluids. Results showed that the Cu-water nanofluid achieved the highest heat transfer coefficient, followed by C, Al2O3, CuO, TiO2, and SiO2, respectively. All results were presented and discussed for four different values of the concentration in nanoparticles, namely φ = 0, 0.6, 1 and 1.6%. Empirical correlations for the friction coefficient and the average Nusselt number were also provided summarizing all the presented results.

Subject Areas

nanofluid; numerical simulation; heat transfer; sedimentation

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