New temperature dependent thermal conductivity data for water-based nanofluids

Mintsa, Honorine Angue; Roy, G.; Nguyen, Cong Tam; Doucet, Dominique

doi:10.1016/j.ijthermalsci.2008.03.009

Cited by 873 publications

(368 citation statements)

References 40 publications

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“…Similar data for the same nanofluids are given in [7,8]. The decrease in thermal conductivity with increasing nanoparticle size was also noted when studying other nanofluids [9][10][11][12].…”

Section: Introductionsupporting

confidence: 72%

Thermal conductivity measurements of nanofluids

Pryazhnikov

Минаков

Rudyak

et al. 2017

International Journal of Heat and Mass Transfer

214

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The paper presents the results of systematic measurements of the thermal conductivity coefficient of nanofluids at room temperature. In total, more than fifty various nanofluids based on water, ethylene glycol, and engine oil containing particles of SiO2, Al2O3, TiO2, ZrO2, CuO, and diamond were studied. The nanoparticles volume concentration ranged from 0.25 to 8% and the particles size ranged from 10 to 150 nm. It is shown that the thermal conductivity of nanofluids is not described by the classical theories (Maxwell's and so forth). The nanofluid thermal conductivity coefficient is a complicated function not only of the particle concentration, but also the particles size, their material, and type of base fluid. Measured thermal conductivity coefficients almost always exceed the values calculated by the Maxwell's formula, though nanofluids with sufficiently small particles may have thermal conductivity coefficients even lower than those predicted by the Maxwell theory. However, in all cases, the nanofluid thermal conductivity coefficient enhances with increasing particle size. It is convincingly shown that there is no direct correlation between the thermal conductivity of the nanoparticle material and the thermal conductivity of nanofluid containing these particles. The base liquid also significantly influences the effective thermal conductivity of the nanofluid. It has been confirmed that the lower the thermal conductivity of the base fluid, the higher the relative thermal conductivity coefficient of the nanofluid.

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Section: Introductionsupporting

confidence: 72%

Thermal conductivity measurements of nanofluids

Pryazhnikov

Минаков

Rudyak

et al. 2017

International Journal of Heat and Mass Transfer

214

View full text Add to dashboard Cite

show abstract

“…One of the techniques, to enhance effective thermal conductivity of these heat transfer fluids, is to add nanoparticles or nanotubes in the base fluids. After Choi and Eastman (1995) and Choi et al (2001), it has been proved experimentally by many researchers (Masuda et al 1993;Das et al 2003;Pak and Cho 1998;Xuan and Li 2003;Eastman et al 2001;Mintsa et al 2009) that even with small solid volume fraction of nanoparticles (usually less than 5 %), the thermal conductivity of heat transfer fluids can be enhanced by 10-50 %. These studies have been reviewed by Trisaksri and Wongwises (2007), Wang and Mujumdar (2007), Eastman et al (2004), and Kakaç and Pramuanjaroenkij (2009), among others.…”

Section: Introductionmentioning

confidence: 99%

Fluid flow and heat transfer of carbon nanotubes along a flat plate with Navier slip boundary

2013

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Homogeneous flow model is used to study the flow and heat transfer of carbon nanotubes (CNTs) along a flat plate subjected to Navier slip and uniform heat flux boundary conditions. This is the first paper on the flow and heat transfer of CNTs along a flat plate. Two types of CNTs, namely, single-and multi-wall CNTs are used with water, kerosene or engine oil as base fluids. The empirical correlations are used for the thermophysical properties of CNTs in terms of the solid volume fraction of CNTs. For the effective thermal conductivity of CNTs, Xue (Phys B Condens Matter 368:302-307, 2005) model has been used and the results are compared with the existing theoretical models. The governing partial differential equations and boundary conditions are converted into a set of nonlinear ordinary differential equations using suitable similarity transformations. These equations are solved numerically using a very efficient finite difference method with shooting scheme. The effects of the governing parameters on the dimensionless velocity, temperature, skin friction, and Nusselt numbers are investigated and presented in graphical and tabular forms. The numerical results of skin friction and Nusselt numbers are compared with the available data for special cases and are found in good agreement.

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“…It was investigated the effect of the particle size such as Al2Cu and Ag2Al [14] particle dispersed into water and EG, Al2O3/water and Al2O3/eg [22] particle size vary from 30-120nm for Al2Cu and Ag2Al,8 and 282 nm for Al2O3. They [23,24] measured the thermal conductivity of Al2O3 nanofluid and compare with [25][26][27] which showed that there was not much difference in the thermal conductivity of the particle size 80,38.4 and 47nm.…”

Section: Particle Sizementioning

confidence: 99%