Dispersion behavior and thermal conductivity characteristics of Al2O3–H2O nanofluids

Nanofluid is a kind of new engineering material consisting of solid nanoparticles with sizes typically of 1–100 nm suspended in base fluids. In this study, Al₂O₃–H₂O nanofluids were synthesized, their dispersion behaviors and thermal conductivity in water were investigated under different pH values and different sodium dodecylbenzenesulfonate (SDBS) concentration. The sedimentation kinetics was determined by examining the absorbency of particle in solution. The zeta potential and particle size of the particles were measured and the Derjaguin–Landau–Verwey–Overbeek (DLVO) theory was used to calculate attractive and repulsive potentials. The thermal conductivity was measured by a hot disk thermal constants analyser. The results showed that the stability and thermal conductivity enhancements of Al₂O₃–H₂O nanofluids are highly dependent on pH values and different SDBS dispersant concentration of nano-suspensions, with an optimal pH value and SDBS concentration for the best dispersion behavior and the highest thermal conductivity. The absolute value of zeta potential and the absorbency of nano-Al₂O₃ suspensions with SDBS dispersant are higher at pH 8.0. The calculated DLVO interparticle interaction potentials verified the experimental results of the pH effect on the stability behavior. The Al₂O₃–H₂O nanofluids with an ounce of Al₂O₃ have noticeably higher thermal conductivity than the base fluid without nanoparticles, for Al₂O₃ nanoparticles at a weight fraction of 0.0015 (0.15 wt%), thermal conductivity was enhanced by up to 10.1%.     

Analytical prediction of forced convective heat transfer of fluids embedded with nanostructured materials (nanofluids)

Nanofluids are a new class of heat transfer fluids developed by suspending nanosized solid particles in liquids. Larger thermal conductivity of solid particles compared to the base fluid such as water, ethylene glycol, engine oil etc. significantly enhances their thermal properties. Several phenomenological models have been proposed to explain the anomalous heat transfer enhancement in nanofluids. This paper presents a systematic literature survey to exploit the characteristics of nanofluids, viz., thermal conductivity, specific heat and other thermal properties. An empirical correlation for the thermal conductivity of Al₂O₃ + water and Cu + water nanofluids, considering the effects of temperature, volume fraction and size of the nanoparticle is developed and presented. A correlation for the evaluation of Nusselt number is also developed and presented and compared in graphical form. This enhanced thermophysical and heat transfer characteristics make fluids embedded with nanomaterials as excellent candidates for future applications.      

Predicting the thermal conductivity enhancement of nanofluids using computational intelligence

Nanofluids, composed of nanoparticles in base liquids, have drawn increasing attention in heat transfer applications due to their anomalously increased thermal conductivity. Pertinent parameters, including the base liquid thermal conductivity, particle thermal conductivity, particle size, particle volume fraction, and temperature, have been shown to have significant but complex effects on thermal performance of nanofluids, which is commonly characterized by the thermal conductivity enhancement, E%. In this work, machine learning is used to develop the Gaussian process regression model to find statistical correlations between E% and aforementioned physical parameters among various types of nanofluids. Nearly 300 nanofluid samples, dispersions of metal and ceramic nanoparticles in water, ethylene glycol, and transformer oil, are explored for this purpose. The modeling approach demonstrates a high degree of accuracy and stability, contributing to efficient and low-cost estimations of E%.     

Fabrication, characterization and measurement of thermal conductivity of Fe3O4 nanofluids

Magnetite Fe₃O₄ nanoparticles were synthesized by a co-precipitation method at different pH values. The products were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, and transmission electronic microscopy. Their magnetic properties were evaluated on a vibrating sample magnetometer. The results show that the shape of the particles is cubic and they are superparamagnetic at room temperature. Magnetic nanofluids were prepared by dispersing the Fe₃O₄ nanoparticles in water as a base fluid in the presence of tetramethyl ammonium hydroxide as a dispersant. The thermal conductivity of the nanofluids was measured as a function of volume fraction and temperature. The results show that the thermal conductivity ratio of the nanofluids increases with increase in temperature and volume fraction. The highest enhancement of thermal conductivity was 11.5% in the nanofluid of 3 vol% of nanoparticles at 40 °C. The experimental results were also compared with the theoretical models.     

Effect of Brownian motion on flow and heat transfer of nanofluids over a backward-facing step with and without adiabatic square cylinder

A mathematical model to predict large enhancement of thermal conductivity of nanofluids by considering the Brownian motion is proposed. The effect of the Brownian motion on the flow and heat transfer characteristics is examined. The computations were done for various types of nanoparticles such as CuO, Al₂O₃, and ZnO dispersed in a base fluid (water), volume fraction of nanoparticles ? in the range of 1 % to 6 % at a fixed Reynolds number Re = 450 and nanoparticle diameter d_np = 30 nm. Our results demonstrate that Brownian motion could be an important factor that enhances the thermal conductivity of nanofluids. Nanofluid of Al₂O₃ is observed to have the highest Nusselt number Nu among other nanofluids types, while nanofluid of ZnO nanoparticles has the lowest Nu. Effects of the square cylinder on heat transfer characteristics are significant with considering Brownian motion. Enhancement in the maximum value of Nu of 29 % and 26 % are obtained at the lower and the upper walls of the channel, respectively, by considering the Brownian effects, with square cylinder, compared with that in the case without considering the Brownian motion. On the other hand, results show a marked improvement in heat transfer compared to the base fluid, this improvement is more pronounced on the upper wall for higher ?.     

Comparative study on thermal performance of helical screw tape inserts in laminar flow using Al2O3/water and CuO/water nanofluids

This paper presents a comparison of thermal performance of helical screw tape inserts in laminar flow of Al₂O₃/water and CuO/water nanofluids through a straight circular duct with constant heat flux boundary condition. The helical screw tape inserts with twist ratios Y = 1.78, 2.44 and 3 were used in the experimental study using 0.1% volume concentration Al₂O₃/water and CuO/water nanofluids. Nanofluids with required volume concentration of 0.1% were prepared by dispersing specified amounts of Al₂O₃ and CuO nanoparticles in deionised water. The performance analysis of helical screw tape inserts in laminar flow of Al₂O₃/water and CuO/water nanofluids is done by evaluating thermal performance factor for constant pumping power condition. Thermal performance factor of helical screw tape inserts using CuO/water nanofluid is found to be higher when compared with the corresponding value using Al₂O₃/water. Therefore, the helical screw tape inserts show better thermal performance when used with CuO/water nanofluid than with Al₂O₃/water nanofluid.     

Dispersion stability and thermal conductivity of propylene glycol-based nanofluids

The dispersion stability and thermal conductivity of propylene glycol-based nanofluids containing Al₂O₃ and TiO₂ nanoparticles were studied in the temperature range of 20–80 °C. Nanofluids with different concentrations of nanoparticles were formulated by the two-step method and no dispersant was used. In contrast to the common belief, the average particle size of nanofluids was observed to decrease with increasing temperature, and nanofluids showed an excellent stability over the temperature range of interest. Thermal conductivity enhancement for both studied nanofluids was a nonlinear function of concentration and was temperature independent. Theoretical analyses were also performed using existing models compared with experimental results. The model based on the aggregation theory appears to be the best.     

Intriguingly high convective heat transfer enhancement of nanofluid coolants in laminar flows

We reported on investigation of the convective heat transfer enhancement of nanofluids as coolants in laminar flows inside a circular copper tube with constant wall temperature. Nanofluids containing Al₂O₃, ZnO, TiO₂, and MgO nanoparticles were prepared with a mixture of 55 vol.% distilled water and 45 vol.% ethylene glycol as base fluid. It was found that the heat transfer behaviors of the nanofluids were highly depended on the volume fraction, average size, species of the suspended nanoparticles and the flow conditions. MgO, Al₂O₃, and ZnO nanofluids exhibited superior enhancements of heat transfer coefficient, with the highest enhancement up to 252% at a Reynolds number of 1000 for MgO nanofluid. Our results demonstrated that these oxide nanofluids might be promising alternatives for conventional coolants.     

Effect of time dependent morphological parameters of nanoclusters on perikinetic heat conduction and induced micro-convection mechanisms of oxide based nanofluids

The article represents an experimentally supported quantitative analysis to observe the effect of time, temperature, nanoclusters’ morphology, and instantaneous volume fractions on perikinetic heat conduction and Brownian motion-based induced convection mechanisms of oxide (Al₂O₃ and TiO₂, size 25–30 nm) based nanofluids. The appropriate models of thermal conductivity have been introduced to study the effect of various parameters such as; varying volume fractions, suspensions’ stabilities, nanoclusters’ growth, temperature, and the liquid layering. The developed model could predict the thermal conductivity enhancements of nanofluids within the accuracy of ± 0.5% to ± 4.5.0% in the temperature range from 20°C to 50°C.

Abbreviations: DI: De-ionized water; DLS: Dynamic light scattering; XRD: X-rays diffraction; TEM: Transmission electronic microscope; SDBS:Sodium dodecyl benzene sulphonate.

Figure Effect of temperature on the Brownian Reynold number for Al₂O₃-H₂O and TiO₂-H₂O nanofluids.     

Influence of pH on Nanofluids' Viscosity and Thermal Conductivity

Aiming at the dispersion stability of nanopartieles regarded as the guide of heat transfer enhancement, we investigate the viscosity and the thermal conductivity of Cu and Al2O3 nanoparticles in water under different pH values. The results show that there exists an optimal pH value for the lowest viscosity and the highest thermal conductivity, and that at the optimal pH value the nanofluids containing a small amount of nanoparticles have noticeably higher thermal conductivity than that of the base fluid without nanoparticles. For the two nanofluids the enhancements of thermal conductivity are observed up to 13% （Al2O3-water） or 15% （Cu-water） at 0.4 wt%, respectively. Therefore, adjusting the pH values is suggested to improve the stability and the thermal conductivity for practical applications of nanofluid.     

Experiment and Lattice Boltzmann numerical study on nanofluids flow in a micromodel as porous medium

Al₂O₃ nanofluids flow has been studied in etched glass micromodel which is idealization of porous media by using a pseudo 2D Lattice Boltzmann Method (LBM). The predictions were compared with experimental results. Pressure drop / flow rate relations have been measured for pure water and Al₂O₃ nanofluids. Because the size of Al₂O₃ nanoparticles is tiny enough to permit through the pore throats of the micromodel, blockage does not occur and the permeability is independent of the nanofluid volume fraction. Therefore, the nanofluid behaves as a single phase fluid, and a single phase LBM is able to simulate the results of this experiment. Although the flow in micromodels is 3D, we showed that 2D LBM can be used provided an effective viscous drag force, representing the effect of the third dimension, is considered. Good qualitative and quantitative agreement is seen between the numerical and experimental results.     

Studies on Al<Subscript>2</Subscript>O<Subscript>3</Subscript>, CuO,and TiO<Subscript>2</Subscript> water-based nanofluids: A comparative approach in laminar and turbulent flow

The Prandtl number, Reynolds number and Nusselt number are functions of thermophysical properties of nanofluids, and these numbers strongly influence the convective heat transfer coefficient. The thermophysical properties vary with volumetric concentration of nanofluids. Therefore, a comprehensive analysis was performed to evaluate the effects on the performance of nanofluids due to variations of density, specific heat, thermal conductivity and viscosity, which are functions of nanoparticle volume concentration. Three metallic oxides, aluminum oxide (Al₂O₃), copper oxide (CuO), and titanium dioxide (TiO₂), dispersed in water as the base fluid were studied. A convenient figure of merit, known as the Mouromtseff number, is used as a base of comparisonfor laminar and turbulent flows. The results indicated that the considered nanofluids can successfully replace water in specific applications for a single-phase forced convection flow in a tube.     

Investigation on characteristics of thermal conductivity enhancement of nanofluids

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, SiO₂ in water, and CuO in ethylene glycol, are produced. Their thermal conductivities are measured by a transient hot-wire method. The thermal conductivity enhancement of water-based MWCNT nanofluid is increased 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 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.     

A thermal conductivity model for nanofluids including effect of the temperature-dependent interfacial layer

The interfacial layer of nanoparticles has been recently shown to have an effect on the thermal conductivity of nanofluids. There is, however, still no thermal conductivity model that includes the effects of temperature and nanoparticle size variations on the thickness and consequently on the thermal conductivity of the interfacial layer. In the present work, the stationary model developed by Leong et al. (J Nanopart Res 8:245–254, 2006) is initially modified to include the thermal dispersion effect due to the Brownian motion of nanoparticles. This model is called the ‘Leong et al.’s dynamic model’. However, the Leong et al.’s dynamic model over-predicts the thermal conductivity of nanofluids in the case of the flowing fluid. This suggests that the enhancement in the thermal conductivity of the flowing nanofluids due to the increase in temperature does not come from the thermal dispersion effect. It is more likely that the enhancement in heat transfer of the flowing nanofluids comes from the temperature-dependent interfacial layer effect. Therefore, the Leong et al.’s stationary model is again modified to include the effect of temperature variation on the thermal conductivity of the interfacial layer for different sizes of nanoparticles. This present model is then evaluated and compared with the other thermal conductivity models for the turbulent convective heat transfer in nanofluids along a uniformly heated tube. The results show that the present model is more general than the other models in the sense that it can predict both the temperature and the volume fraction dependence of the thermal conductivity of nanofluids for both non-flowing and flowing fluids. Also, it is found to be more accurate than the other models due to the inclusion of the effect of the temperature-dependent interfacial layer. In conclusion, the present model can accurately predict the changes in thermal conductivity of nanofluids due to the changes in volume fraction and temperature for various nanoparticle sizes.     

A new thermal conductivity model for nanofluids

In a quiescent suspension, nanoparticles move randomly and thereby carry relatively large volumes of surrounding liquid with them. This micro-scale interaction may occur between hot and cold regions, resulting in a lower local temperature gradient for a given heat flux compared with the pure liquid case. Thus, as a result of Brownian motion, the effective thermal conductivity, k_eff, which is composed of the particles conventional static part and the Brownian motion part, increases to result in a lower temperature gradient for a given heat flux. To capture these transport phenomena, a new thermal conductivity model for nanofluids has been developed, which takes the effects of particle size, particle volume fraction and temperature dependence as well as properties of base liquid and particle phase into consideration by considering surrounding liquid traveling with randomly moving nanoparticles.The strong dependence of the effective thermal conductivity on temperature and material properties of both particle and carrier fluid was attributed to the long impact range of the interparticle potential, which influences the particle motion. In the new model, the impact of Brownian motion is more effective at higher temperatures, as also observed experimentally. Specifically, the new model was tested with simple thermal conduction cases, and demonstrated that for a given heat flux, the temperature gradient changes significantly due to a variable thermal conductivity which mainly depends on particle volume fraction, particle size, particle material and temperature. To improve the accuracy and versatility of the k_effmodel, more experimental data sets are needed.     

Heat Transfer and Hydrodynamic Performance Analysis of a Miniature Tangential Heat Sink Using Al2O3–H2O and TiO2–H2O Nanofluids

In this article, thermal and hydrodynamic performances of a miniature tangential heat sink are investigated experimentally by using Al₂O₃–H₂O and TiO₂–H₂O nanofluids. The effects of flow rate and volume concentration on the thermal performance have been investigated for the Reynolds number range of 210 to 1,100. Experimental results show that the average convective heat transfer coefficient increases 14 and 11% and the bottom temperature of the heat sink decreases 2.2°C and 1.6°C by using Al₂O₃–H₂O and TiO₂–H₂O nanofluid instead of pure distilled water, respectively.     

The effect of particle size on the thermal conductivity of alumina nanofluids

We present new data for the thermal conductivity enhancement in seven nanofluids containing 8–282 nm diameter alumina nanoparticles in water or ethylene glycol. Our results show that the thermal conductivity enhancement in these nanofluids decreases as the particle size decreases below about 50 nm. This finding is consistent with a decrease in the thermal conductivity of alumina nanoparticles with decreasing particle size, which can be attributed to phonon scattering at the solid–liquid interface. The limiting value of the enhancement for nanofluids containing large particles is greater than that predicted by the Maxwell equation, but is predicted well by the volume fraction weighted geometric mean of the bulk thermal conductivities of the solid and liquid. This observation was used to develop a simple relationship for the thermal conductivity of alumina nanofluids in both water and ethylene glycol.     

Heat transfer enhancement of laminar nanofluids flow in a triangular duct using vortex generator

In this work, two dimensional laminar flow of different nanofluids flow inside a triangular duct with the existence of vortex generator is numerically investigated. The governing equations of mass, momentum and energy were solved using the finite volume method (FVM). The effects of type of the nanoparticles, particle concentrations, and Reynolds number on the heat transfer coefficient and pressure drop of nanofluids are examined. Reynolds number is ranged from 100 to 800. A constant surface temperature is assumed to be the thermal condition for the upper and lower heated walls. In the present work, three nanofluids are examined which are Al₂O₃, CuO and SiO₂ suspended in the base fluid of ethylene glycol with nanoparticles concentrations ranged from 1 to 6%. The results show that for the case of SiO₂–EG, at ? = 6% and Re = 800, it is found that the average Nusselt number is about 50.0% higher than the case of Re = 100.     

A model for the thermal conductivity of nanofluids – the effect of interfacial layer

A model for predicting the effective thermal conductivity of nanofluids is proposed. It has been documented that the interfacial layer at the solid (particle)/liquid interface and particle size is one of the major mechanisms for enhancing the thermal conductivity of nanofluids. Comparing with other classical models, the proposed model takes into account some additional effects including volume fraction, thickness, thermal conductivity of the interfacial layer and particle size. The proposed model is found to be better than the existing models since the predicted effective thermal conductivity of different types of nanofluids are closer to the experimental results.     

Numerical investigation of laminar flow and heat transfer in a radial flow cooling system with the use of nanofluids

Nanofluids, because of their enhanced heat transfer capability as compared to normal water/glycol/oil based fluids, offer the engineer opportunities for development in areas where high heat transfer, low temperature tolerance and small component size are required. In this present paper, the hydrodynamic and thermal fields of a water–γAl₂O₃ nanofluid in a radial laminar flow cooling system are considered. Results indicate that considerable heat transfer enhancement is possible, even achieving a twofold increase in the case of a 10% nanoparticle volume fraction nanofluid. On the other hand, an increase in wall shear stress is also noticed with an increase in particle volume concentration.