Heat transfer of nanofluids in turbulent pipe flow

Corcione, Massimo; Cianfrini, Marta; Quintino, Alessandro

doi:10.1016/j.ijthermalsci.2012.01.009

Cited by 41 publications

(14 citation statements)

References 74 publications

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“…They revealed that the convective heat transfer and pressure drop of nanofluids tested in fully developed turbulent flow region can be predicted with the help of the traditional correlations and models, provided that the effective nanofluid properties are used in calculating the dimensionless numbers. Corcione et al [15] study heat transfer of nanoparticle suspensions in single-phase turbulent pipe flow theoretically. They extended the convective heat transfer correlations available in the literature for singlephase flows to nanoparticle suspensions, provided that the thermophysical properties appearing in them are the nanofluid effective properties calculated at the reference temperature.…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation of turbulent forced-convective heat transfer of Al2O3–water nanofluid with variable properties in tube

Aghaei

Sheikhzadeh

Dastmalchi

et al. 2015

Ain Shams Engineering Journal

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In this study, the flow field and heat transfer of Al 2 O 3 -water nanofluid turbulent forced convection in a tube are investigated. The surface of the tube is hot (T h = 310 K). Simulations are carried out for constant water Prandtl number of 6.13, Reynolds numbers from 10,000, 20,000, 30,000 to 100,000, nanoparticles volume fractions of 0, 0.001, 0.1, 0.2, 0.4 and nanoparticles' diameter of 25, 33, 75, and 100 nm. The finite volume method and SIMPLE algorithm are utilized to solve the governing equations numerically. The numerical results showed that with enhancing Reynolds numbers, average Nusselt number increases. The variations of the average Nusselt number relative to volume fractions are not uniform. For all of the considered volume fractions, by increasing the Reynolds number the skin friction factor decreases and with increasing volume fractions and Reynolds number the pressure drop increases. Ó 2014 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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Section: Introductionmentioning

confidence: 99%

Numerical investigation of turbulent forced-convective heat transfer of Al2O3–water nanofluid with variable properties in tube

Aghaei

Sheikhzadeh

Dastmalchi

et al. 2015

Ain Shams Engineering Journal

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“…Keshavarz Moraveji and Razvarz [13] showed that by charging the Al20 3/water nanofluid to the heat pipe, thermal per formance is enhanced by reducing the thermal resistance and wall temperature difference. Corcione et al [14] illustrated that there exists an optimal particle loading for maximum heat transfer. The optimal concentration of nanoparticles increases as the nanofluid bulk temperature and the Reynolds number are increased, and the length-to-diameter ratio of the pipe is decreased, while it is inde pendent of the nanoparticle diameter.…”

Section: Pressure Drop and Heat Transfer Of Nanofluid In Turbulent Pimentioning

confidence: 99%

Pressure Drop and Heat Transfer of Nanofluid in Turbulent Pipe Flow Considering Particle Coagulation and Breakage

Lin

Xia

2014

Journal of Heat Transfer

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Numerical simulations of Al20flwater nanofluid in turbulent pipe flow are performed with considering the particle convection, dijfusion, coagulation, and breakage. The dis tributions of particle volume concentration, the friction factor, and heat transfer charac teristics are obtained. The results show that the initial uniform distributions of particle volume concentration become nonuniform, and increase from the pipe wall to the center. The nonuniformity becomes significant along the flow direction from the entrance and attains a steady state gradually. Friction factors increase with the increase of particle volume concentrations and particle diameter, and with the decrease of Reynolds number. The friction factors increase remarkably at lower volume concentration, while slightly at higher volume concentration. The presence of nanoparticles provides higher heat trans fer than pure water. The Nusselt number of nanofluids increases with increasing Reynolds number, particle volume concentration, and particle diameter. The rate increase in Nus selt number at lower particle volume concentration is more than that at higher concentra tion. For a fixed particle volume concentration, the friction factor is smaller while the Nusselt number is larger for the case with uniform distribution of particle volume concen tration than that with nonuniform distribution. In order to effectively enhance the heat transfer using nanofluid and simultaneously save energy, it is necessary to make the par ticle distribution more uniform. Finally, the expressions of friction factor and Nusselt number as a function of particle volume concentration, particle diameter and Reynolds number are derived based on the numerical data.

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“…Heat transfer of nanofluids in a turbulent pipe flow was studied theoretically by Corcione et al [24] who demonstrated that nanofluids behave like single-phase fluids. They recommended using the Gnielinski correlation [14] for the heat transfer.…”

Section: Introductionmentioning

confidence: 99%

Determining velocity and friction factor for turbulent flow in smooth tubes

Taler

2016

International Journal of Thermal Sciences

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Heat transfer of nanofluids in turbulent pipe flow

Cited by 41 publications

References 74 publications

Numerical investigation of turbulent forced-convective heat transfer of Al2O3–water nanofluid with variable properties in tube

Numerical investigation of turbulent forced-convective heat transfer of Al2O3–water nanofluid with variable properties in tube

Pressure Drop and Heat Transfer of Nanofluid in Turbulent Pipe Flow Considering Particle Coagulation and Breakage

Determining velocity and friction factor for turbulent flow in smooth tubes

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