Laminar convective heat transfer and viscous pressure loss of alumina–water and zirconia–water nanofluids

Rea, Ulzie; McKrell, Thomas; Hu, Lin‐Wen; Buongiorno, Jacopo

doi:10.1016/j.ijheatmasstransfer.2008.10.025

Cited by 454 publications

(183 citation statements)

References 22 publications

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“…The measurement by Ho et al [19] showed that the thermal conductivity of Al 2 O 3 -water nanofluid increased more than 10% relatively with particle volumetric fraction 3%. Their data agreed well with the experimental result by Wang et al [20] and theoretical correlation of Rea et al [21], although their measurement was for low volume fraction and higher than that predicted by Masuda et al [22]. Vajjha and Das [17] performed experiment on the thermal conductivity of nanofluids dispersing Al 2 O 3 or CuO nanoparticles into a base fluid.…”

Section: Introductionsupporting

confidence: 85%

An improved model for thermal conductivity of nanofluids with effects of particle size and Brownian motion

Dong

Chen

2017

J Therm Anal Calorim

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Based on the generalized distribution of the temperature field, an improved model for the thermal conductivity of nanofluid has been derived. The impact of particle size and Brownian motion is modeled through the effective volume fraction, based on particle radius. In the special case, the generalized relationship reduces to the classical Maxwell model. On the other hand, the effect of Brownian movement is equivalent to increasing the effective volume fraction of nanoparticles. The effective radius of the nanoparticle is proposed, where the switching time and the equivalent volume fraction depend on the Brownian velocity of the nanoparticles. Considering the above two effects, an effective model is obtained. Comparison of thermal conductivity for Al 2 O 3 -water nanofluid is made between the present model and several theoretical models. Theoretical predictions on CuO-water nanofluid, ZnOTiO 2 hybrid nanofluids and MWCNTs nanofluid are also verified against experimental data.

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Section: Introductionsupporting

confidence: 85%

An improved model for thermal conductivity of nanofluids with effects of particle size and Brownian motion

Dong

Chen

2017

J Therm Anal Calorim

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“…They state nanofluids behaved as homogenous mixtures with experimental Nusselt numbers following classical relations developed for the single-phase approach, modified for the mean nano-particle concentration, being accurate to within ±10%; this uncertainty is explained by movement of nanoparticles due to Brownian motion and viscosity gradient due to concentration, with non-uniform shear rate having insignificant effect on heat transfer. Similar uncertainty was found for metal oxide nanofluids [17] and for CNT nano-fluids [9].…”

Section: -Introductionsupporting

confidence: 80%

CFD assessment of the effect of nanoparticles on the heat transfer properties of acetone/ZnBr2 solution

Mohammed

Giddings

Walker

et al. 2018

Applied Thermal Engineering

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“…The second term 1.7 Re/Pr 4 1/3 ϕ in Equation (30) is small compared to 1 in all cases. The results are then well fitted with Equation (29) and so with the correlation provided by Rea et al [35] for Al 2 O 3 /water-based nanofluids, 431 ≤ Re ≤ 2000 and ϕ ≤ 0.06. It corresponds to Equation (29) with a prefactor equal to 2.0398 instead of 1.953.…”

Section: Discussionsupporting

confidence: 62%

“…Two correlations for the thermal conductivity k n f and for the dynamic viscosity µ n f are considered here. The equations used to evaluate the nanofluid properties (density [11], heat capacity [32,33], viscosity [34,35]) are as follows:…”

Section: Water Propertiesmentioning

confidence: 99%

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

Sekrani

Poncet

2016

Applied Sciences

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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. 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 d np = 200 nm, the Cu nanoparticles were more sedimented by around 80%, while the Al 2 O 3 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, Al 2 O 3 , CuO, TiO 2 , and SiO 2 , 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.

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Laminar convective heat transfer and viscous pressure loss of alumina–water and zirconia–water nanofluids

Cited by 454 publications

References 22 publications

An improved model for thermal conductivity of nanofluids with effects of particle size and Brownian motion

An improved model for thermal conductivity of nanofluids with effects of particle size and Brownian motion

CFD assessment of the effect of nanoparticles on the heat transfer properties of acetone/ZnBr2 solution

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

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