• 동력기계공학회지
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• 제17권2호
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• pp.78-86
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• 2013

In this research, dilute colloidal suspension alumina nanofluids were prepared by dispersing alumina nanoparticles in DI water and ethylene glycol as base fluids. Particle size analyzer and TEM test results revealed that the size of the alumina nanofluids(3wt% and 5wt%) with dispersion time 3hrs were 46nm and 60nm respectively. Thermal conductivity of these alumina nanofluids was measured by means of hot wire technique using a LAMBDA system. For water based alumina nanofluids, thermal conductivity enhancement was from 2.29% to 3.06% with 5wt% alumina at temperatures ranging from 15 to $40^{\circ}C$. Whereas in case of ethylene glycol based alumina nanofluids under the same temperature range, thermal conductivity enhancement was from 9.6% to 10% with 5wt% alumina. An enhancement of 37% average convective heat transfer was achieved with 5wt% alumina nanofluids at Re of 1,100.

• 한국분무공학회지
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• 제19권4호
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• pp.174-181
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• 2014

This study investigates the effects of nanoparticle size and temperature on the thermal conductivity enhancement of water-based alumina ($Al_2O_3$) nanofluids, using the centrifuging method and relative centrifugal forces of differing magnitude to produce nanofluids of three different particles without involving any dispersants or surfactants. We determined the coupling dependency in thermal conductivity enhancement relative to nanoparticle size and temperature of the alumina nanofluids and also experimentally showed that the effect of temperature on thermal conductivity is strongly dependent on nanoparticle size. Also, our experimental data presented that the effective medium theory models such as the Maxwell model and Hasselman and Johnson model are not sufficient to explain the thermal conductivity of nanofluids since they cannot account for the temperature- and size-dependent nature of water-based alumina nanofluids.

• Advances in nano research
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• 제12권5호
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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.

• Nuclear Engineering and Technology
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• 제45권3호
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• pp.335-346
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• 2013

The Critical Heat Flux (CHF) of water with dispersed alumina nanoparticles was measured for the geometry and flow conditions relevant to the In-Vessel Retention (IVR) situation which can occur during core melting sequences in certain advanced Light Water Reactors (LWRs). CHF measurements were conducted in a flow boiling loop featuring a test section designed to be thermal-hydraulically similar to the vessel/insulation gap in the Westinghouse AP1000 plant. The effects of orientation angle, pressure, mass flux, fluid type, boiling time, surface material, and surface state were investigated. Results for water-based nanofluids with alumina nanoparticles (0.001% by volume) on stainless steel surface indicate an average 70% CHF enhancement with a range of 17% to 108% depending on the specific flow conditions expected for IVR. Experiments also indicate that only about thirty minutes of boiling time (which drives nanoparticle deposition) are needed to obtain substantial CHF enhancement with nanofluids.

• 대한기계학회논문집B
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• 제33권10호
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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.

• Journal of Advanced Marine Engineering and Technology
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• 제37권1호
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• pp.16-21
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• 2013

나노유체란 유체 내에 금속 또는 비금속성 나노 크기의 입자를 분산시킨 것으로서 열전달율을 높이기 위해 다양한 곳에서 사용되어진다. 본 논문에서는 50 nm 크기의 알루미나를 증류수에 분산시켜 농도 및 유속에 따른 기본적인 열전달 특성을 알아보고자 하였다. 실험 결과 알루미나 나노유체의 농도가 증가할수록 평균 및 국소 열전달 계수가 증가하는 경향을 보였다. 또한 X/D=50~120 구간에서 6 Wt%의 나노유체의 국소 열전달 계수값이 증류수와 비교하였을 때 최대 37~46% 정도 높게 나타났다. 6 Wt% 농도에서 레이놀즈수가 1100~1300일 때 평균 열전달 계수가 증류수에 비해 큰 폭으로 증가함을 확인하였다.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2005년도 동계학술발표대회 논문집
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• pp.539-545
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• 2005

In this paper, the thermal characteristics of natural convection in a rectangular cavity with nanofluids such as water-based nanofluids containing alumina are theoretically investigated with a new model of the thermal conductivity for nanofluids presented by Jang and Choi and various models for effective viscosity. In addition, based on theoretical results, the effects of various parameters such as the volume fraction, the temperature, and the size of nanoparticles on free convective instability and heat transfer characteristics in a rectangular cavity with nanofluids are suggested.

• 대한기계학회논문집B
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• 제29권9호
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• pp.1065-1073
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• 2005

The thermal conductivity of water- and ethylene glycol-based nanofluids containing alumina $(Al_2O_3)$, zinc oxide (ZnO) and titanium dioxide $(TiO_2)$ nanoparticles is measured by varying the particle diameter and volume fraction. The transient hot-wire method using an anodized tantalum wire for electrical insulation is employed for the measurement. The experimental results show that nanofluids have substantially higher thermal conductivities than those of the base fluid and the ratio of thermal conductivity enhancement increases linearly with the volume fraction. It has been found that the ratio of thermal conductivity enhancement increases with decreasing particle size but no empirical or theoretical correlation can explain the particle-size dependence of the thermal conductivity. This work provides, for the first time to our knowledge, a set of consistent experimental data over a wide range of nanofluid conditions and can therefore serve as a basis for developing theoretical models to predict thermal conduction phenomena in nanofluids.

• 융합정보논문지
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• 제9권12호
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• pp.147-156
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• 2019

동심 이중관에서 기본유체 물과 나노입자 산화알미늄의 혼합인 나노유체를 적용한 대향유동을 유한체적법의 수치적 방법으로 열전달 특성을 규명하였다. 고온유체는 내부 원형관으로 흐르며 열을 외부 환형관으로 흐르는 저온유체로 전달한다. 고온유체와 저온유체의 체적유량 및 나노입자의 체적농도를 변수로 두어 열전달 및 유동 특성을 조사했다. 결과는 나노입자의 체적농도와 체적유량의 증가함에 따라 열전달 성능이 증가함을 보였다. 외부와 내부 관 모두에서 나노유체인 경우가 기본유체보다 나노입자의 체적농도가 8%일 때 나노유체가 열전달 성능이 최대 17% 증가하는 것을 확인했다. 또한 기본유체에 비해 환형관의 대류열전달 계수는 최대 31% 증가함을 보였으며 열교환기의 유용도는 약 20%가 상승함을 확인하였다. 하지만 나노입자의 체적농도가 8%일때 마찰인자가 최대 136% 커지는 것을 확인하였다.