Experimental investigations and theoretical determination of thermal conductivity and viscosity of Al2O3/water nanofluid

Experimental investigations and theoretical determination of effective thermal conductivity and viscosity of Al₂O₃/H₂O nanofluid are reported in this paper. The nanofluid was prepared by synthesizing Al₂O₃ nanoparticles using microwave assisted chemical precipitation method, and then dispersing them in distilled water using a sonicator. Al₂O₃/water nanofluid with a nominal diameter of 43 nm at different volume concentrations (0.33–5%) at room temperature were used for the investigation. The thermal conductivity and viscosity of nanofluids are measured and it is found that the viscosity increase is substantially higher than the increase in thermal conductivity. Both the thermal conductivity and viscosity of nanofluids increase with the nanoparticle volume concentration. Theoretical models are developed to predict thermal conductivity and viscosity of nanofluids without resorting to the well established Maxwell and Einstein models, respectively. The proposed models show reasonably good agreement with our experimental results.     

The role of several heat transfer mechanisms on the enhancement of thermal conductivity in nanofluids

A modelling of the thermal conductivity of nanofluids based on extended irreversible thermodynamics is proposed with emphasis on the role of several coupled heat transfer mechanisms: liquid interfacial layering between nanoparticles and base fluid, particles agglomeration and Brownian motion. The relative importance of each specific mechanism on the enhancement of the effective thermal conductivity is examined. It is shown that the size of the nanoparticles and the liquid boundary layer around the particles play a determining role. For nanoparticles close to molecular range, the Brownian effect is important. At nanoparticles of the order of 1–100 nm, both agglomeration and liquid layering are influent. Agglomeration becomes the most important mechanism at nanoparticle sizes of the order of 100 nm and higher. The theoretical considerations are illustrated by three case studies: suspensions of alumina rigid spherical nanoparticles in water, ethylene glycol and a 50/50w% water/ethylene glycol mixture, respectively, good agreement with experimental data is observed.     

Comparison of the effects of measured and computed thermophysical properties of nanofluids on heat transfer performance

This article reports a comparison of the differences between using measured and computed thermophysical properties to describe the heat transfer performance of TiO₂–water nanofluids. In this study, TiO₂ nanoparticles with average diameters of 21 nm and a particle volume fraction of 0.2–1 vol.% are used. The thermal conductivity and viscosity of nanofluids were measured by using transient hot-wire apparatus and a Bohlin rotational rheometer, respectively. The well-known correlations for calculating the thermal conductivity and viscosity of nanofluids were used for describing the Nusselt number of nanofluids and compared with the results from the measured data. The results show that use of the models of thermophysical properties for calculating the Nusselt number of nanofluids gave similar results to use of the measured data. Where there is a lack of measured data on thermophysical properties, the most appropriate models for computing the thermal conductivity and viscosity of the nanofluids are the models of Yu and Choi and Wang et al., respectively.     

A prediction model for the effective thermal conductivity of nanofluids considering agglomeration and the radial distribution function of nanoparticles

Conventional heat transfer fluids usually have low thermal conductivity, limiting their efficiency in many applications. Many experiments have shown that adding nanosize solid particles to conventional fluids can greatly enhance their thermal conductivity. To explain this anomalous phenomenon, many theoretical investigations have been conducted in recent years. Some of this research has indicated that the particle agglomeration effect that commonly occurs in nanofluids should play an important role in such enhancement of the thermal conductivity, while some have shown that the enhancement of the effective thermal conductivity might be accounted for by the structure of nanofluids, which can be described using the radial distribution function of particles. However, theoretical predictions from these studies are not in very good agreement with experimental results. This paper proposes a prediction model for the effective thermal conductivity of nanofluids, considering both the agglomeration effect and the radial distribution function of nanoparticles. The resulting theoretical predictions for several sets of nanofluids are highly consistent with experimental data.     

The effect of real viscosity on the heat transfer of water based Al2O3 nanofluids in a two-sided lid-driven differentially heated rectangular cavity

The heat transfer and fluid flow behavior of water based Al₂O₃ nanofluids are numerically investigated inside a two-sided lid-driven differentially heated rectangular cavity. Physical properties which have major effects on the heat transfer of nanofluids such as viscosity and thermal conductivity are experimentally investigated and correlated and subsequently used as input data in the numerical simulation. Transport equations are numerically solved with finite volume approach using SIMPLEC algorithm. It was found that not only the thermal conductivity but also the viscosity of nanofluids has a key role in the heat transfer of nanofluids. The results show that at low Reynolds number, increasing the volume fraction of nanoparticles increases the viscosity and has a deteriorating effect on the heat transfer of nanofluids. At high Reynolds number, the increase in the viscosity is compensated by force convection and the increase in the volume fraction of nanoparticles which results in an increase in heat transfer is in coincidence with experimental results.     

CFD studies on natural convection heat transfer of Al<Subscript>2</Subscript>O<Subscript>3</Subscript>-water nanofluids

This work is focused on numerical simulations of natural convection heat transfer in Al₂O₃-water nanofluids using computational fluid dynamics approach. Fluent v6.3 is used to simulate water based nanofluid considering it as a single phase. Thermo-physical properties of the nanofluids are considered in terms of volume fraction and size of nanoparticles, size of base fluid molecule and temperature. The numerical values of effective thermal conductivity have also been compared with the experimental values available in the literature. The numerical result simulated shows decrease in heat transfer with increase in particle volume fraction. Computed result shows similar trend in increase of Nusselt number with Relayigh number as depicted by experimental results. Streamlines and temperature profiles are plotted to demonstrate the effect.     

Mathematical modelling of thermal conductivity for nanofluid considering interfacial nano-layer

Maxwell’s classical model for predicting effective thermal conductivity of colloidal solution predicts the thermal conductivity of nanofluids quite satisfactorily. However, Maxwell’s model does not consider the effect of interfacial layer, Brownian motion of nano-particle and nanoparticle aggregation. In this paper, the effect of interfacial layer on thermal conductivity is considered. A simple expression has been derived to determine thermal conductivity of nanofluid considering interfacial layer formed on the nano particles. The thermal conductivity of the interfacial layer has been precisely determined and results are found to be closer to the experimental values, hence, further improving the results of classical Maxwell model.     

Dependence of particle size on the effective thermal diffusivity and conductivity of nanofluids: role of base fluid properties

Effect of nanoparticle size on effective thermal diffusivity and conductivity of polymeric and water based nanofluids are investigated following thermal wave interference technique. Two sets of nanofluids, prepared by dispersing TiO₂ nanoparticles, with average sizes in the range 5–100?nm, in polyvinyl alcohol and water show opposing particle size dependences. Variations are explained invoking effective medium theory, including size of nanoparticles, molecular weight of base fluid and effects associated with it.     

Numerical simulation of heat transfer in a micro channel heat sinks using nanofluids

In this study, a numerical simulation of copper microchannel heatsink (MCHS) using nanofluids as coolants is presented. The nanofluid is a mixture of pure water and nanoscale metallic or nonmetallic particles with various volume fractions. Also, the effects of various volume fractions, volumetric flow rate and various materials of nanoparticles on the performance of MCHS have been developed. A three-dimensional computational fluid dynamics model was developed using the commercial software package FLUENT, to investigate the conjugate fluid flow and heat transfer phenomena in micro channel heatsinks. The results show that the cooling performance of a microchannel heat sink with water based nanofluid containing Al₂O₃ (vol 8%) is enhanced by about 4.5% compared with micro channel heatsink with pure water. Nanofluids reduce both the thermal resistance and the temperature difference between the top (heated) surface of the MCHS and inlet nanofluid compared with that pure water. The cooling performance of a micro channel heat sink with metal nanofluids improves compared with that of a micro channel heat sink with oxide metal nanofluids because the thermal conductivity of metal nanofluid is higher than oxide metal nanofluids. Micro channel heat sinks with nanofluids are expected to be good candidates as the next generation cooling devices for removing ultra high heat flux.     

Predicting thermal conductivity of liquid suspensions of nanoparticles (nanofluids) based on rheology

A methodology is proposed for predicting the effective thermal conductivity of dilute suspensions of nanoparticles (nanofluids) based on rheology.The methodology uses the rheological data to infer microstructures of nanoparticles quantitatively,which is then incorporated into the conventional Hamilton-Crosser equation to predict the effective thermal conductivity of nanofluids.The methodology is experimentally validated using four types of nanofluids made of titania nanoparticles and titanate nanotubes dispersed in water and ethylene glycol.And the modified Hamilton-Crosser equation successfully predicted the effective thermal conductivity of the nanofluids.     

Measurement of temperature-dependent thermal conductivity and viscosity of TiO2-water nanofluids

Nanofluid is an innovative heat transfer fluid with superior potential for enhancing the heat transfer performance of conventional fluids. Many attempts have been made to investigate its thermal conductivity and viscosity, which are important thermophysical properties. No definitive agreements have emerged, however, about these properties. This article reports the thermal conductivity and dynamic viscosity of nanofluids experimentally. TiO₂ nanoparticles dispersed in water with volume concentration of 0.2–2 vol.% are used in the present study. A transient hot-wire apparatus is used for measuring the thermal conductivity of nanofluids whereas the Bohlin rotational rheometer (Malvern Instrument) is used to measure the viscosity of nanofluids. The data are collected for temperatures ranging from 15 °C to 35 °C. The results show that the measured viscosity and thermal conductivity of nanofluids increased as the particle concentrations increased and are higher than the values of the base liquids. Furthermore, thermal conductivity of nanofluids increased with increasing nanofluid temperatures and, conversely, the viscosity of nanofluids decreased with increasing temperature of nanofluids. Moreover, the measured thermal conductivity and viscosity of nanofluids are quite different from the predicted values from the existing correlations and the data reported by other researchers. Finally, new thermophysical correlations are proposed for predicting the thermal conductivity and viscosity of nanofluids.     

Predicting thermal conductivity of liquid suspensions of nanoparticles （nanofluids） based on rheology

A methodology is proposed for predicting the effective thermal conductivity of dilute suspensions of nanoparticles （nanofluids） based on rheology. The methodology uses the rheological data to infer microstructures of nanoparticles quantitatively, which is then incorporated into the conventional Hamilton-Crosser equation to predict the effective thermal conductivity of nanofluids. The methodology is experimentally validated using four types of nanofluids made of titania nanoparticles and titanate nanotubes dispersed in water and ethylene glycol. And the modified Hamilton-Zrosser equation successfully predicted the effective thermal conductivity of the nanofluids.     

Investigation of viscosity and thermal conductivity of alumina nanofluids with addition of SDBS

The present study focused on thermal conductivity and viscosity of alumina nanoparticles, at low volume concentrations of 0.01–1.0 % dispersed in the mixture of ethylene glycol and water (mass ratio, 60:40). Sodium dodeobcylbenzene sulfonate (SDBS) was applied for better dispersion and stability of alumina nanoparticles and study of its influence on both thermal conductivity and viscosity. The thermal conductivity established polynomial enhancement pattern with increase of volume concentration up to 0.1 % while linear enhancement was obtained at higher concentrations. In addition, thermal conductivity was enhanced with the rise of temperature. However, the augmentation was negligible compared to that obtained with increase of volume concentration. In contrast, viscosity data showed remarkable reduction with increase of temperature. Meanwhile, viscosity of nanofluids enhanced with loading of alumina nanoparticles. Thermal conductivity and viscosity measurements showed higher values over theoretical predictions. Results showed SDBS at different concentrations has distinct influence on thermal conductivity and viscosity of nanofluid.     

Experimental investigation on thermal properties of silver nanofluids

This paper reports on an experimental investigation of the thermal properties behavior of 0.5 wt% silver nanoparticle-based nanofluids (NF) containing oleic acid (OA) and potassium oleate surfactant (OAK⁺) with concentrations of 0.5, 1, and 1.5 wt% respectively. The experiments were conducted from 20 °C to 80 °C. It was shown that the NF with 1 wt% OAK⁺ yielded the highest thermal behavior enhancement of about 28% at 80 °C compared to deionized water. The thermal performance had higher than the base fluid/nanofluids at approximately 80%. Moreover, the NF containing OAK⁺ showed higher thermal conductivity and dynamics of specific heat capacity than deionized water in all of the experimental conditions in this study. The rheological experiment showed that viscosity of NF was significantly dependant on temperature. As shear rate increased, the shear stress of the NF increased; however, the viscosity of the nanofluids decreased first and then stabilized. It was further found that NF containing OAK⁺ at a range of operating temperatures produced Newtonian behavior.     

Experimental study to obtain the viscosity of CuO-loaded nanofluid: effects of nanoparticles’ mass fraction,temperature and basefluid’s types to develop a correlation

In this study, the impacts of temperature, nanoparticles mass fraction, and basefluid types were investigated on the dynamic viscosity of CuO-loaded nanofluids. The nanoparticles were dispersed in deionized water, ethanol, and ethylene glycol as basefluids separately and the measurements were performed on samples with nanoparticles loads ranging from 0.005 to 5 wt%, and the temperature range of 25 to 70 °C. TEM analysis were performed on dried nanoparticles and the results showed the average mean diameter of CuO nanoparticles ranged from 10 to 50 nm. The results of DLS analysis confirmed the results of nanoparticles size obtained by TEM analysis in mentioned basefluids and Zeta-Potential tests exhibited the high stability of the nanoparticles in the basefluids environment. The results indicate that by adding tiny amount of CuO nanoparticles to basefluids, relative viscosity of nanofluid increases. By the increase in nanoparticles load higher than 0.1 wt% the effect of both nanoparticles mass fraction and temperature would be more tangible, while for nanoparticles mass fraction lower than 0.1 wt% no significant change in viscosity was observed. In addition, the results declare that viscosity of nanofluid remains constant at various applied shear rates indicating Newtonian behavior of nanofluid at various nanoparticles load and temperature. According to experimental data, it is also evident that with the increase in temperature, the value of relative dynamic viscosity decreases significantly. Also it is concluded that for CuO/ethanol nanofluid, more interfacial interaction is resulted that causes higher relative dynamic viscosity while for CuO/water lower interfacial interaction between nanoparticles surface and water molecules are resulted which leads to the lower values for this parameter. The results of this study implied that with increase the temperature from 25 to 70 °C at the condition where nanoparticles mass fraction was chosen to be 5 wt%, the value of dynamic viscosity of CuO/ethanol, CuO/deionized water, CuO/ethylene glycol declined 69%, 66%, and 65% respectively. Finally, a correlation was proposed for the relative dynamic viscosity of nanofluid based on the CuO nanoparticles mass fraction and temperature of the basefluid and nanoparticles.     

Two numerical modelings of free convection heat transfer using nanofluids inside a square enclosure

This work describes the numerical simulation of natural convection heat transfer of Cu–water nanofluids in a square enclosure for Rayleigh numbers varying from 10³ up to 10⁵. Two different numerical approaches were used: the finite volume method and the finite element method. The nanofluids were assumed to be single-phase fluids with modified thermal properties obtained from experimental results and theoretical models. The results showed that the Nusselt number for nanofluids was basically the same as that obtained for the base fluid. Therefore, the enhancement observed in the heat transfer coefficient was significant due to the augmentation in the thermal conductivity.     

Molecular dynamics studies on spreading of nanofluids promoted by nanoparticle adsorption on solid surface

Spreading of nanofluids on solid substrate was studied via molecular dynamics simulations. Simulation models for two immiscible fluids (oil and water based nanofluids) confined in a slit between two planar solid walls were set up. The influence of the volume concentration of the nanoparticles on the three-phase contact line motion was investigated. We found that the larger volume concentration results in more visible nanoparticle adsorption on solid surface. This effect further induces an advancing displacement of the contact line compared with the meniscus profiles in low concentration case and that with the absence of nanoparticles. These findings are consistent with the previous experimental and theoretical results and provide the atomic-scale understanding on nanofluid spreading.     

Heat- and mass-transport in aqueous silica nanofluids

Using the transient hot wire and pulsed field gradient nuclear magnetic resonance methods we determined the thermal conductivity and the solvent self-diffusion coefficient (SDC) in aqueous suspensions of quasi-monodisperse spherical silica nanoparticles. The thermal conductivity was found to increase at higher volume fraction of nanoparticles in accordance with the effective medium theory albeit with a smaller slope. On the other hand, the SDC was found to decrease with nanoparticle volume fraction faster than predicted by the effective medium theory. These deviations can be explained by the presence of an interfacial heat-transfer resistance and water retention by the nanoparticles, respectively. We found no evidence for anomalous enhancement in the transport properties of nanofluids reported earlier by other groups.     

Nanofluids thermal behavior analysis using a new dispersion model along with single-phase

A numerical study has been performed to analyze nanofluids convective heat transfer. Laminar α-Al₂O₃-water nanofluid flows in an entrance region of a horizontal circular tube with constant surface temperature. Numerical analysis has been carried out using two different single-phase models (homogenous and dispersion) and two-phase models (Eulerian–Lagrangian and mixture). A new model is developed to consider the nanoparticles dispersion. The transport equations for the tube with constant surface temperature were solved numerically using a control volume approach. The effects of nanoparticles volume fraction (0.5, 1 %) and Reynolds number (650 ≤ Re ≤ 2300) on nanofluid convective heat transfer coefficient were studied. The results are compared with the experimental data and it is shown that the homogenous single-phase model is underestimated and the mixture model is overestimated. Although the Eulerian–Lagrangian model gives a reasonable prediction for the thermal behavior of nanofluids, the dispersion single-phase model gives more accurate prediction despite its simplicity.     

Turbulent forced convection heat transfer of non-Newtonian nanofluids

Forced convection heat transfer of non-Newtonian nanofluids in a circular tube with constant wall temperature under turbulent flow conditions was investigated experimentally. Three types of nanofluids were prepared by dispersing homogeneously γ-Al₂O₃, TiO₂ and CuO nanoparticles into the base fluid. An aqueous solution of carboxymethyl cellulose (CMC) was used as the base fluid. Nanofluids as well as the base fluid show shear-thinning (pseudoplastic) rheological behavior. Results indicate that the convective heat transfer coefficient of nanofluids is higher than that of the base fluid. The enhancement of the convective heat transfer coefficient increases with an increase in the Peclet number and the nanoparticle concentration. The increase in the convective heat transfer coefficient of nanofluids is greater than the increase that would be observed considering strictly the increase in the effective thermal conductivity of nanofluids. Experimental data were compared to heat transfer coefficients predicted using available correlations for purely viscous non-Newtonian fluids. Results show poor agreement between experimental and predicted values. New correlation was proposed to predict successfully Nusselt numbers of non-Newtonian nanofluids as a function of Reynolds and Prandtl numbers.