Effective Thermal Conductivity Of Nanofluids Research Articles

Shear-rate dependent effective thermal conductivity of H2O+SiO2 nanofluids

Effective thermal conductivity (ETC) of water-based silicon dioxide nanofluids in shear flow fields (flow shear rate range was 0–820 1/s) was measured using a rotating Couette apparatus. The results show that the ETC of the nanofluids in shear flow fields is significantly higher than that in static states. For the flow shear rates lower than a critical value (infinite-shear rate), the ETC asymptotically increases with increasing the flow shear rate; for the flow shear rates higher than the critical value, the ETC displays a plateau value (infinite-shear thermal conductivity). The increase of the ETC with shear rate is more obvious as increase the nanoparticle diameter and the nanoparticle volume fraction. For 16 different measured nanofluids, the infinite-shear rates vary from 445.0 to 712.1 1/s, while the infinite-shear thermal conductivities increase by 9%–17% comparing with the zero-shear thermal conductivities. The conventional ETC prediction correlation proposed for the suspensions containing micro-sized particles is not suitable for the nanofluids qualitatively and quantitatively. Finally, an exponential correlation is proposed based on our measured data to predict the ETC of nanofluids considering the effects of flow shear rate, nanoparticle diameter, and nanoparticle volume fraction.

Effect of Particle Size on Effective Thermal Conductivity of Nanofluids

Effect of Particle Size on Effective Thermal Conductivity of Nanofluids

Developing a novel form of thermal conductivity of nanofluids with Brownian motion effect by means of fractal geometry

Abstract Considering the effect of Brownian motion of nanoparticles, an analytical model for effective thermal conductivity of nanofluids is obtained. The formula of calculating effective thermal conductivity of nanofluids is given by taking into account the fractal distribution of nanoparticles. In the present approach, the proposed model is explicitly related to the thermal conductivities of the base fluids and the nanoparticles, the average diameter of nanoparticles, the nanoparticle concentration, the fractal dimension of nanoparticles and physical properties of fluids. It is found that the effective thermal conductivity of nanofluids increases with increasing of the concentration of nanoparticles. And the effective thermal conductivity of nanofluids for the smaller size of nanoparticles is larger than the bigger size at given concentration. A good agreement between the proposed model predictions and experimental data is found. The validity of the fractal model for effective thermal conductivity of nanofluids is thus verified. The proposed fractal model can reveal the physical mechanisms of heat transfer for nanofluids.

Natural convection heat transfer of nanofluids along a vertical plate embedded in porous medium

The unsteady natural convection heat transfer of nanofluid along a vertical plate embedded in porous medium is investigated. The Darcy-Forchheimer model is used to formulate the problem. Thermal conductivity and viscosity models based on a wide range of experimental data of nanofluids and incorporating the velocity-slip effect of the nanoparticle with respect to the base fluid, i.e., Brownian diffusion is used. The effective thermal conductivity of nanofluid in porous media is calculated using copper powder as porous media. The nonlinear governing equations are solved using an unconditionally stable implicit finite difference scheme. In this study, six different types of nanofluids have been compared with respect to the heat transfer enhancement, and the effects of particle concentration, particle size, temperature of the plate, and porosity of the medium on the heat transfer enhancement and skin friction coefficient have been studied in detail. It is found that heat transfer rate increases with the increase in particle concentration up to an optimal level, but on the further increase in particle concentration, the heat transfer rate decreases. For a particular value of particle concentration, small-sized particles enhance the heat transfer rates. On the other hand, skin friction coefficients always increase with the increase in particle concentration and decrease in nanoparticle size.

Role of Interfacial Surfactant Layers in the Thermal Conductivity of Nanofluids

Various mechanisms and correlations have been developed for prediction of thermal conductivity of nano-suspensions. However, seldom theoretical researches on thermal conductivity of nanofluids containing surfactant are found. In this work, a thermal conductivity prediction-model of nanofluid containing surfactants is proposed based on Leong et al.’s model and Langmuir adsorption theory by considering the interfacial surfactant layers. The thickness of the interfacial layer is defined by Langmuir adsorption theory. Compared with the experimental data available in the literature on thermal conductivity of nanofluid containing surfactants, the calculated values on the proposed model have been verified that the proposed models show reasonably good agreement with the experimental results and give better predictions for the effective thermal conductivity of nanofluids compared to existing classical models.

Pumping Energy Saving Using Nanoparticle Suspensions as Heat Transfer Fluids

The pumping power diminution consequent to the use of nanoparticle suspensions as heat transfer fluids is analyzed theoretically assuming that nanofluids behave like single-phase fluids. In this hypothesis, all the heat transfer and friction factor correlations originally developed for single-phase flows can be used also for nanoparticle suspensions, provided that the thermophysical properties appearing in them are the nanofluid effective properties calculated at the reference temperature. In this regard, two empirical equations, based on a wide variety of experimental data reported in the literature, are used for the evaluation of the nanofluid effective thermal conductivity and dynamic viscosity. Conversely, the other effective properties are computed by the traditional mixing theory. Both laminar and turbulent flow regimes are investigated, using the operating conditions, the nanoparticle diameter, and the solid–liquid combination as control parameters. The fundamental result obtained is the existence of an optimal particle loading for minimum cost of operation at constant heat transfer rate. A set of empirical dimensional algebraic equations is proposed to determine the optimal particle loading of water-based nanofluids.

Synthesis of spherical silica/multiwall carbon nanotubes hybrid nanostructures and investigation of thermal conductivity of related nanofluids

In this study, a hybrid of silica nanosphere/multiwall carbon nanotube (MWCNT) has been synthesized by wet chemical method at room temperature. The effect of MWCNTs, silica nanospheres and hybrid nanostructures (80% silica nanosphere/20% MWCNT and 50% silica nanosphere/50% MWCNT) on the thermal conductivity of distilled water has been investigated. SDBS was used as the dispersant to stabilize nanomaterials in the aqueous suspension and its concentration was 1.5 times of the concentration of nanomaterials. As results show, by increasing the concentration of nanomaterials, effective thermal conductivity of nanofluids increased. The most and the least enhancement in the effective thermal conductivity of the fluids were associated with MWCNTs (23.3%) and silica nanospheres (8.8%), while the enhancement for the hybrid nanomaterial was a value between MWCNT and silica nanoparticles. Furthermore, the hybrid consisting of higher percentage of MWCNTs showed more increase in effective thermal conductivity of the nanofluid, compared with the other hybrid.

Optimization of laminar pipe flow using nanoparticle liquid suspensions for cooling applications

Heat transfer of nanoparticle suspensions in laminar pipe flow is studied theoretically. The main idea upon which this work is based is that nanofluids behave more like single-phase fluids than like conventional solid−liquid mixtures. This assumption implies that all the heat transfer and friction factor correlations available in the literature for single-phase flows can be extended to nanoparticle suspensions, provided that the thermophysical properties appearing in them are the nanofluid effective properties calculated at the reference temperature. In this regard, two empirical equations, based on a wide variety of experimental data reported in the literature, are used for the evaluation of the nanofluid effective thermal conductivity and dynamic viscosity. Conversely, the other effective properties are computed by the traditional mixing theory. The novelty of the present study is that the merits of nanofluids with respect to the corresponding base liquid are evaluated in terms of global energetic performance, and not simply by the common point of view of the heat transfer enhancement. Both cases of constant pumping power and constant heat transfer rate are investigated for different operating conditions, nanoparticle diameters, and solid−liquid combinations. The fundamental result obtained is the existence of an optimal particle loading for either maximum heat transfer at constant driving power or minimum cost of operation at constant heat transfer rate. In particular, for any assigned combination of solid and liquid phases, it is found that the optimal concentration of suspended nanoparticles for maximum heat transfer is only slightly higher than that for minimum cost of operation. These optimal concentrations increase as the nanofluid bulk temperature is increased, the length-to-diameter ratio of the pipe is decreased, and the Reynolds number of the base fluid is increased. Moreover, the optimal concentrations increase with increasing the nanoparticle average size at high bulk temperatures, whilst they are practically independent of the nanoparticle diameter at lower bulk temperatures.

Heat transfer of nanofluids in turbulent pipe flow

Heat transfer of nanoparticle suspensions in turbulent pipe flow is studied theoretically. The main idea upon which this work is based is that nanofluids behave more like single-phase fluids than like conventional solid–liquid mixtures. This assumption implies that all the convective heat transfer correlations available in the literature for single-phase flows can be extended to nanoparticle suspensions, provided that the thermophysical properties appearing in them are the nanofluid effective properties calculated at the reference temperature. In this regard, two empirical equations, based on a wide variety of experimental data reported in the literature, are used for the evaluation of the nanofluid effective thermal conductivity and dynamic viscosity. Conversely, the other effective properties are computed by the traditional mixing theory. The novelty of the present study is that the merits of nanofluids with respect to the corresponding base liquid are evaluated in terms of global energetic performance, and not simply by the common point of view of the heat transfer enhancement. Both cases of constant pumping power and constant heat transfer rate are investigated for different operating conditions, nanoparticle diameters, and solid–liquid combinations. The fundamental result obtained is the existence of an optimal particle loading for either maximum heat transfer at constant driving power or minimum cost of operation at constant heat transfer rate. In particular, for any assigned combination of solid and liquid phases, it is found that the optimal concentration of suspended nanoparticles increases as the nanofluid bulk temperature is increased, the Reynolds number of the base fluid is increased, and the length-to-diameter ratio of the pipe is decreased, while it is practically independent of the nanoparticle diameter.

Optimization of Free Convection Heat Transfer From Vertical Plates Using Nanofluids

Free convection heat transfer in nanofluids from vertical flat plates at uniform temperature is investigated theoretically. The main idea upon which the present work is based is that nanofluids behave more like single-phase fluids rather than like conventional solid–liquid mixtures. This assumption implies that all the convective heat transfer correlations available in the literature for single-phase flows can be extended to nanoparticle suspensions, provided that the thermophysical properties appearing in them are the nanofluid effective properties calculated at the reference temperature. In this connection, two empirical equations, based on a wide variety of experimental data reported in the literature, are used for the evaluation of the nanofluid effective thermal conductivity and dynamic viscosity. Conversely, the other effective properties are computed by the traditional mixing theory. The heat transfer enhancement that derives from the dispersion of nanosized solid particles into the base liquid is calculated for different operating conditions, nanoparticle diameters, and combinations of solid and liquid phases. The fundamental result obtained is the existence of an optimal particle loading for maximum heat transfer. In particular, for any assigned combination of suspended nanoparticles and base liquid, it is found that the optimal volume fraction increases as the nanofluid average temperature increases, the nanoparticle size decreases, and the Rayleigh number of the base fluid decreases.

Numerical investigation of the effective thermal conductivity of nano-fluids using the lattice Boltzmann model

The lattice Boltzmann model is proposed for numerical modeling of energy transport inside nano-fluids. Firstly, the lattice Boltzmann model is briefly introduced. Secondly, a lattice Boltzmann model for simulating nano-fluids is described. Finally, results from calculations for the effective thermal conductivity of nano-fluids are presented and compared with theoretical and experimental results. The numerical results on the effective thermal conductivity of investigated nano-fluids are found to be in good agreement with both the theoretical and the experimental data.

An Improved Model for Prediction of the Effective Thermal Conductivity of Nanofluids

An Improved Model for Prediction of the Effective Thermal Conductivity of Nanofluids

Natural convection heat transfer of nanofluids in annular spaces between horizontal concentric cylinders

Abstract Natural convection heat transfer of nanofluids in annular spaces between long horizontal concentric cylinders maintained at different uniform temperatures is investigated theoretically. The main idea upon which the present work is based is that nanofluids behave more like single-phase fluids rather than like conventional solid–liquid mixtures. This assumption implies that all the convective heat transfer correlations available in the literature for single-phase flows can be extended to nanoparticle suspensions, provided that the thermophysical properties appearing in them are the nanofluid effective properties calculated at the reference temperature. In this connection, two empirical equations, based on a wide variety of experimental data reported in the literature, are used for the evaluation of the nanofluid effective thermal conductivity and dynamic viscosity. Conversely, the other effective properties are computed by the traditional mixing theory. The heat transfer enhancement that derives from the dispersion of nano-sized solid particles into the base liquid is calculated for different operating conditions, nanoparticle diameters, and combinations of solid and liquid phases. The fundamental result obtained is the existence of an optimal particle loading for maximum heat transfer. In particular, for any assigned combination of suspended nanoparticles and base liquid, it is found that the optimal volume fraction increases as the nanofluid average temperature increases and the nanoparticle size decreases.

Heat conduction in nanofluids: Structure–property correlation

We examine numerically the effects of particle-fluid thermal conductivity ratio, particle volume fraction, and particle morphology on nanofluids effective thermal conductivity and phase lags of heat flux and temperature gradient, for six types of nanofluids containing sphere, cube, hollow sphere, hollow cube, slab-cross and column-cross nanoparticles, respectively. The particle’s radius of gyration and the non-dimensional particle-fluid interfacial area are found to be two characteristic parameters for the effect of particles’ geometrical structure on the effective thermal conductivity. The nanoparticles with larger values of these two parameters can change fluid conductivity more significantly. Due to the enhanced particle-fluid interfacial heat transfer, the nanofluid effective thermal conductivity can practically reach the Hashin–Shtrikman bounds when the particle-phase connects to form a network and separates the base fluid into a dispersed phase. The particle aggregation can effectively affect the effective thermal conductivity when the separation distance among particles is smaller than about one fifth of the particles’ dimension. For the nanofluids considered in the present work, the phase lags of heat flux and temperature gradient scale with the square of particle dimension and range from 10 −11 s to 10 −7 s; the effect of cross-coupling between the heat conduction in the fluid and particle phases is weak; the phase lag of temperature gradient is larger than that of heat flux such that the heat conduction in them is diffusion-dominant and their effective thermal conductivity can be well predicted by the predictive models developed in the present work based on the classical diffusion theory for two-phase systems.

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-Al 2O 3, TiO 2 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.

A new heat propagation velocity prevails over Brownian particle velocities in determining the thermal conductivities of nanofluids

An alternative insight is presented concerning heat propagation velocity scales in predicting the effective thermal conductivities of nanofluids. The widely applied Brownian particle velocities in published literature are often found too slow to describe the relatively higher nanofluid conductivities. In contrast, the present model proposes a faster heat transfer velocity at the same order as the speed of sound, rooted in a modified kinetic principle. In addition, this model accounts for both nanoparticle heat dissipation as well as coagulation effects. This novel model of effective thermal conductivities of nanofluids agrees well with an extended range of experimental data.

Impact analysis of natural convection on thermal conductivity measurements of nanofluids using the transient hot-wire method

Significant deviations between published results have been reported measuring the effective thermal conductivity of nanofluids with the transient hot-wire method (THWM). This may be attributed to a poor selection of the temperature data range, which should meet the following conditions. The start time should be chosen after the conductive heat flux delay time, while the end time should be selected before a crossover point when natural convection becomes significant. Considering an EG-based 1.06 vol.% ZnO nanofluid, the thermal conductivity was measured to increase by 5.4% over that of the base fluid.

Thermal conductivity of interfacial layers in nanofluids

Thermal conductivity of interfacial layers is an essential parameter for determining how the ordered liquid layering around the particle-liquid interface contributes to the unusual high thermal conductivity of nanofluids. However, so far there is no experimental data regarding this parameter. Using nonequilibrium molecular dynamics simulations of an inhomogeneous Au-Ar system in which the solid-liquid interactions are assumed to be much stronger than the liquid-liquid interactions, we show explicitly that the thermal conductivity of a 1-nm-thick interfacial layer is 1.6 ∼ 2.5 times higher than that of the base fluid. The simulation results are incorporated into a three-level clustering model to calculate the effective thermal conductivity of nanofluids. The results show that the contribution of the interfacial layer to thermal conductivity enhancements should be considered if there are particle clusters in nanofluids.

Heat transfer augmentation in nanofluids via nanofins

Theoretical results derived in this article are combined with experimental data to conclude that, while there is no improvement in the effective thermal conductivity of nanofluids beyond the Maxwell's effective medium theory (J.C. Maxwell, Treatise on Electricity and Magnetism, 1891), there is substantial heat transfer augmentation via nanofins. The latter are formed as attachments on the hot wire surface by yet an unknown mechanism, which could be related to electrophoresis, but there is no conclusive evidence yet to prove this proposed mechanism.

A FRACTAL MODEL FOR NUCLEATE POOL BOILING OF NANOFLUIDS AT HIGH HEAT FLUX INCLUDING CHF

A fractal model for nucleate pool boiling of nanofluids at high heat flux and critical heat flux (CHF) is developed based on the fractal distribution of nanoparticles and nucleation sites on boiling surfaces in this paper. The formula of calculating high heat flux and CHF for nanofluids in nucleate pool boiling is given by taking into account heat convection between nanoparticles and liquids due to the Brownian motion of nanoparticles in fluids. The proposed model is expressed as a function of temperature of nanofluids, the effective thermal conductivity of nanofluids, the average size of nanoparticles, the fractal dimension of nanoparticles and nucleation sites, the nanoparticles volume fraction of suspension, and physical properties of fluids. No additional/new empirical constant is introduced in this fractal model. An agreement between the proposed model predictions and experimental data is found. The validity of the fractal model for nucleate pool boiling of nanofluids at high heat flux and CHF is thus verified.