• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2177-2181
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• 2007

In this paper, effective thermal conductivities of water-based $Al_2O_3$-nanofluids with low concentration from 0.01 vol. % to 0.3 vol. % are experimentally obtained by transient hot wire method (THWM). The water-based $Al_2O_3$-nanofluids are manufactured by two-step method which is widely used. To examine suspension and dispersion characteristics of the water-based $Al_2O_3$-nanofluids, Zeta potential as well as transmission electron micrograph (TEM) is observed. We confirm the manufactured $Al_2O_3$-nanofluids have good suspension and dispersion. The effective thermal conductivities of the water-based $Al_2O_3$-nanofluids with low concentration are enhanced up to 1.64% compared with that of DI water at $21^{\circ}C$. In addition, experimental results are compared with theoretical results from Jang and Choi model.

• Journal of the Korean Solar Energy Society
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• v.32 no.6
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• pp.85-92
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• 2012

A nanofluid is a fluid containing suspended solid particles, with sizes on the order of nanometers. Normally, nanofluids have higher thermal conductivitiest han their base fluids. Therefore, we measured the thermal conductivity and viscosity of oxidized carbon nanofluids based the mixture of distilled water and ethanol (ethanol concentration is 0.2) oxidized carbon nanofluids were made by ultrasonic dispersing oxidized multi-walled carbon nanotubes in the mixture of distilled water and ethanol at the rates of 0.001~ 0.1 vol%. The thermal conductivity and viscosity of oxidized carbon nanofluids were measured by using transient hot-wire method and rotational digital viscometer, respectively. And all of experiments were carried out at the same temperature conditions($10^{\circ}C$, $25^{\circ}C$ and $70^{\circ}C$). As a result, when volume fraction of nanofluids is 0.1 vol%, thermal conductivity was improved 13.6% ($10^{\circ}C$), 15.1% ($25^{\circ}C$), and 17.0% ($70^{\circ}C$), and its viscosity was increased by 36.0% ($10^{\circ}C$), 32.9% ($25^{\circ}C$) and 19.5% ($70^{\circ}C$) than the base fluids.

• Journal of the Korean Solar Energy Society
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• v.32 no.6
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• pp.93-99
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• 2012

A nanofluid is a fluid containing suspended solid particles, with sizes on the order of nanometers. Especially graphene nanoparticle that has the high thermal conductivity properties among the various nanoparticles added to the nanofluid is receiving attention. Graphene is a flat monolayer of $sp^2$-bonded carbon atoms tightly packed into a honeycomb lattice. And are known to have very high thermal conductivity. Therefore, we compared thermal conductivity with viscosity of graphene M-5 nanofluids and graphene M-15 nanofluids. Graphene M-5 and graphene M-15 have different average particle diameters and the other properties are the same. Two kinds of graphene nanofluids was examined by measuring thermal conductivity via transient hot-wire method. And the viscosity was measured by using a rotational digital viscometer. As a result, graphene M-5 nanofluids exhibited better thermal conductivity and viscosity than graphene M-15 nanofluids.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.33 no.10
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• pp.729-736
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• 2009

Pool boiling heat transfer and critical heat flux (CHF) of water-based nanofluids with alumina and titania nanoparticles of 0.01% by volume were investigated on a disk heater at saturated and atmospheric conditions. The experimental results showed that the boiling in nanofluids caused the considerable increase in CHF on the flat surface heater. It was revealed by visualization of the heater surface subsequent to the boiling experiments that a major amount of nanoparticles deposited on the surface during the boiling process. Pool boiling of pure water on the surface modified by such nanoparticle deposition resulted in the same CHF increases as what boiling nanofluids, thus suggesting the CHF enhancement in nanofluids was an effect of the surface modification through the nanoparticle deposition during nanofluid boiling. Possible reasons for CHF enhancement in pool boiling of nanofluids are discussed with surface property changes caused by the nanoparticle deposition.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.474-478
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• 2008

It has been shown that a nanofluid consisting of nanoparticles dispersed in base fluid has much higher effective thermal conductivity than pure fluid. In this study, four kinds of nanofluids such as multiwalled carbon nanotube (MWCNT) in water, CuO in water, SiO2in water, and CuO in ethylene glycol, are produced. Their thermal conductivities are measured by a transient hot-wire method. The thermal conductivity of water-based MWCNT nanofluid is shown to be increased by up to 11.3% at a volume fraction of 0.01. The measured thermal conductivities of MWCNT nanofluids are higher than those calculated with Hamilton-Crosser's model due to neglecting solid-liquid interaction at the interface. The results show that the thermal conductivity enhancement of nanofluids depends on the thermal conductivities of both particles and the base fluid. Stability of nanofluids is estimated by UV-vis spectrum analysis. Stability of nanofluid depends on the type of base fluid and the suspended particles. Also it can be improved in addition of a surfactant.

• Korean Journal of Materials Research
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• v.17 no.9
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• pp.493-499
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• 2007

Oil-based nanofluids were prepared by dispersing nonconducting fibrous $Al_2O_3$ and spherical AlN nanoparticles in transformer oil. In this study, the effects of wet grinding and surface modification of particles on thermal and electrical properties of nanofluids were investigated. Grinding experiments were conducted with high-speed bead mill and ultrasonic homogenizer and nanoparticles were surface modified by oleic acid and polyoxyethylene alkyl acid ester(PAAE) in n-hexane or transformer oil, at the same time. It is obvious that the combination of nanoparticle, dispersant and dispersion solvent is very important for the dispersity of nanofluids. For nanofluids containing 1.0vol.% AlN particles in transformer oil, the enhancement of thermal conductivity was 11.6% compared with pure transformer oil. However, the electric-insulating property of AlN nanofluids was very low due to used dispersant itself. Therefore, the effect of the dispersant on thermal/electrical/physical properties of the transformer oil should be considered before selecting a proper dispersant.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.165-169
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• 2008

Binary nanofluids(Binary mixture + nanoparticles) have been extensively paid attention for application in absorption system as a new working fluid. Thermal property evaluation of the new refrigerants is inevitable to apply them for actual system. The objectives of this paper are to measure the thermal conductivity of the binary nanofluids by the transient hot-wire method, and to assess the application possibility of the binary nanofluids for absorption system. It was found that the thermal conductivity of the binary nanofluids ($H_2O/LiBrAl_2O_3$) increased with increasing the concentration of the nanoparticles ($Al_2O_3$) and enhanced up to 27% at 0.1 vol % of the nanoparticles.

• Advances in nano research
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• v.12 no.5
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• pp.489-499
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• 2022

Nanofluids have recently triggered a substantial scientific interest as cooling media. However, their stability is challenging for successful engagement in industrial applications. Different factors, including temperature, nanoparticles and base fluids characteristics, pH, ultrasonic power and frequency, agitation time, and surfactant type and concentration, determine the nanofluid stability regime. Indeed, it is often too complicated and even impossible to accurately find the conditions resulting in a stabilized nanofluid. Furthermore, there are no empirical, semi-empirical, and even intelligent scenarios for anticipating the stability of nanofluids. Therefore, this study introduces a straightforward and reliable intelligent classifier for discriminating among the stability regimes of alumina-water nanofluids based on the Zeta potential margins. In this regard, various intelligent classifiers (i.e., deep learning and multilayer perceptron neural network, decision tree, GoogleNet, and multi-output least squares support vector regression) have been designed, and their classification accuracy was compared. This comparison approved that the multilayer perceptron neural network (MLPNN) with the SoftMax activation function trained by the Bayesian regularization algorithm is the best classifier for the considered task. This intelligent classifier accurately detects the stability regimes of more than 90% of 345 different nanofluid samples. The overall classification accuracy and misclassification percent of 90.1% and 9.9% have been achieved by this model. This research is the first try toward anticipting the stability of water-alumin nanofluids from some easily measured independent variables.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.52-57
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• 2006

This study investigates the distribution stability of binary nanofluids where binary mixtures such as $NH_3/H_2O$ and $H_2O/LiBr$ solution are used as a base fluid. When a little amount of certain nanosized particles is added into a basefluid, the thermal conductivity of that mixture increases greatly. Such mixtures are named 'nanofluids' where nano-particles should be distributed stably and uniformly so the distribution stability of nanoparticles in nanofluids is one of the most important factors for nanofluid application. Therefore, binary nanofluids in which binary mixtures are applied as the basefluids are considered as working fluids. The kind and the concentration of nanoparticles, and the concentration of ammonia are considered as the key parameters. The objectives of this paper are to visualize the dispersed status of particles in binary nanofluids and to find the effect of key parameters on the distribution stability in the ammonia absorption system.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.8
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• pp.725-732
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• 2013

This study examined the convective heat transfer characteristics of nanofluids flowing over a heated fine wire. Convective heat transfer coefficients were measured for four different nano-engine-oil samples under three different temperature boundary conditions, i.e., both or either variation of wire and fluid temperature and constant film temperature. Experimental investigations that the increase in the convective heat transfer coefficients of nanofluids in the internal pipe flow often exceeded the increase in thermal conductivity were recently published; however, the current study did not confirm these results. Analyzing the behavior of the convective heat transfer coefficient under various temperature conditions was a useful tool to explain the relation between the thermal conductivity and the boundary layer thickness of nanofluids.