A new thermal conductivity model for nanofluids

Koo, Junemoo; Kleinstreuer, Clement

doi:10.1007/s11051-004-3170-5

Cited by 923 publications

(421 citation statements)

References 14 publications

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“…Nanofluids, which are engineered dilute and stable colloidal suspensions of metallic and/or ceramic nanoparticles in a conventional base fluid, exhibit thermal conductivity values ~ 20-150 % higher than the base fluids [17]. Several experimental and some theoretical works have been reported on the enhanced thermal conductivity of nanofluids [18][19][20][21] over the past decade. The thermal transport caliber of any nanofluid depends mainly on nanoparticle concentration, thermal conductivity, the diameter of particles, base fluid conductivity and temperature [22].…”

Section: Introductionmentioning

confidence: 99%

Particle and thermohydraulic maldistribution of nanofluids in parallel microchannel systems

Maganti

Dhar

Sundararajan

et al. 2016

Microfluid Nanofluid

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Fluidic maldistribution in microscale multichannel devices requires deep understanding to achieve optimized flow and heat transfer characteristics. A thorough computational study has been performed to understand the concentration and thermo-hydraulic maldistribution of nanofluids in parallel microchannel systems using an Eulerian-Lagrangian twin phase model.The study reveals that nanofluids cannot be treated as homogeneous single phase fluids in such complex flow domains and effective property models fail drastically to predict the performance parameters. To comprehend the distribution of the particulate phase, a novel concentration maldistribution factor has been proposed. It has been observed that distribution of particles need not essentially follow the flow pattern, leading to higher thermal performance than expected from homogeneous models. Particle maldistribution has been conclusively shown to be due to various migration and diffusive phenomena like Stokesian drag, Brownian motion, thermophoretic drift, etc. The implications of particle distribution on the cooling performance have been illustrated and smart fluid effects (reduced magnitude of maximum temperature) have been observed and a mathematical model to predict the enhanced cooling performance in such flow geometries has been proposed. The article presents lucidly the effectiveness of discrete phase approach in modelling nanofluid thermo-hydraulics and sheds insight on behavior of nanofluids in complex flow domains.2

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Section: Introductionmentioning

confidence: 99%

Particle and thermohydraulic maldistribution of nanofluids in parallel microchannel systems

Maganti

Dhar

Sundararajan

et al. 2016

Microfluid Nanofluid

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“…Based on static mechanics, several attempts have been made to formulate appropriate effective thermal conductivity (Xue and Xu 2005;Leong et al 2006;Tillman and Hill 2007;Murshed et al 2008). Koo and Kleinstreuer (2004) stated that the effective thermal conductivity is composed of the particle's conventional static part and a Brownian motion part. Moreover, the Brownian motion effect was found to become more effective at higher temperature as observed experimentally.…”

Section: Introductionmentioning

confidence: 99%

Mixed convection flow along an inclined permeable plate: effect of magnetic field, nanolayer conductivity and nanoparticle diameter

Rana

Bég²

2014

Appl Nanosci

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Steady, two-dimensional mixed convection boundary layer flow of an incompressible Al 2 O 3 -water nanofluid along an inclined permeable plate in the presence of transverse magnetic field has been examined numerically. The governing equations (Boussinesq approximation) with associated boundary condition are solved using FEM for nanofluid containing spherical-shaped nanoparticles having volume fraction ranging from 1 to 4 %. Staticbased model for calculating the effective thermal conductivity at 300 K, proposed by Leong et al. (J Nanopart Res 8:245-254, 2006) and Murshed et al. (Int J Therm Sci 47:560-568, 2008) has been implemented. Effect of various pertinent parameters with different classical and experimental models for effective dynamic viscosity is discussed.

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“…For example a number of authors have proposed that Brownian motion induced nanoscale convection is a significant factor [3][4][5] , while others have argued to the contrary [6][7] . The debate behind the mechanism was largely fueled by limited experimental characterization of the nanofluid systems.…”

mentioning

confidence: 99%

Effect of aggregation on thermal conduction in colloidal nanofluids

Prasher

Evans

Meakin

et al. 2006

Applied Physics Letters

361

207

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Using effective medium theory the authors demonstrate that the thermal conductivity of nanofluids can be significantly enhanced by the aggregation of nanoparticles into clusters. Predictions of the effective medium theory are in excellent agreement with detailed numerical calculation on model nanofluids involving fractal clusters and show the importance of cluster morphology on thermal conductivity enhancements.

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A new thermal conductivity model for nanofluids

Cited by 923 publications

References 14 publications

Particle and thermohydraulic maldistribution of nanofluids in parallel microchannel systems

Particle and thermohydraulic maldistribution of nanofluids in parallel microchannel systems

Mixed convection flow along an inclined permeable plate: effect of magnetic field, nanolayer conductivity and nanoparticle diameter

Effect of aggregation on thermal conduction in colloidal nanofluids

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