The particle thermal conductivity influence of nanofluids on thermal performance of the microtubes

The paper presents the numerical analysis on microchannel laminar heat transfer and fluid flow of nanofluids in order to evaluate the suitable thermal conductivity of the nanoparticles that results in superior thermal performances compared to the base fluid. The diameter ratio of the micro-tube was D_i/D_o = 0.3/0.5 mm with a tube length L = 100 mm in order to avoid the heat dissipation effect. The heat transfer rate was fixed to Q = 2 W. The water based Al₂O₃, TiO₂ and Cu nanofluids were considered with various volume concentrations ϕ = 1,3 and 5% and two diameters of the particles d_p = 13 nm and 36 nm. The analysis is based on a fixed Re and pumping power Π, in terms of average heat transfer coefficient and maximum temperature of the substrate. The results reveal that only the nanofluids with particles having very high thermal conductivity (λ_Cu = 401 W/m K) are justified for using in microcooling systems. Moreover, the analysis is sensitive to both the comparison criteria (Re or Π) and heat transfer parameters (h_ave or t_max).     

Experimental investigation and model development for thermal conductivity of α-Al2O3-glycerol nanofluids

In order to investigate the effect of nanoparticle volume fraction, nanoparticle size and temperature on the thermal conductivity of glycerol based alumina (α-Al₂O₃) nanofluids, a set of experiments were carried out for temperature ranging from 20 °C to 45 °C. The nanofluids contained α-Al₂O₃ nanoparticles of three different sizes (31 nm, 55 nm and 134 nm) were prepared by two-step method at volume fractions ranging from 0.5% to 4%. The experimental results show that α-Al₂O₃-glycerol nanofluids have substantially higher thermal conductivity than the base fluid and the maximum enhancement of the relative thermal conductivity was 19.5% for the case of 31 nm at 4% volume fraction. The data analyses indicated that the volume fraction and size of the nanoparticles have significant effects on the thermal conductivity ratio (TCR) of Al₂O₃-glycerol nanofluids, while the temperature has almost no significant effect on the data for range of this study. At room temperature, the effective thermal conductivity remains almost constant for 50 h at 4% volume fractions. The comparison of the obtained experimental data and predictions from some existing theoretical and empirical models reveals that the thermal conductivity ratio and its trend could not be accurately explained by the models in open literature. Consequently, a new empirical correlation based on the experimental data has been developed in this study.     

Experimental thermal conductivity of ethylene glycol and water mixture based low volume concentration of Al2O3 and CuO nanofluids

Thermal conductivity of ethylene glycol and water mixture based Al₂O₃ and CuO nanofluids has been estimated experimentally at different volume concentrations and temperatures. The base fluid is a mixture of 50:50% (by weight) of ethylene glycol and water (EG/W). The particle concentration up to 0.8% and temperature range from 15 °C–50 °C were considered. Both the nanofluids are exhibiting higher thermal conductivity compared to base fluid. Under same volume concentration and temperature, CuO nanofluid thermal conductivity is more compared to Al₂O₃ nanofluid. A new correlation was developed based on the experimental data for the estimation of thermal conductivity of both the nanofluids.     

Experimental studies on thermal conductivity of blends of ethylene glycol-water-based TiO2 nanofluids

A set of three nanofluids of different blends were prepared with ethylene glycol–water and TiO₂ nanoparticles and are characterized for thermal conductivity as a function of temperature and volume concentration of nanoparticles. The measurements were taken in the temperature range from 30 °C to 70 °C, which happens to be most widely used range of temperature for many cooling applications in heat transfer equipment. Nanofluids were prepared by dispersing the nanoparticles in base fluids such as (1) water, (2) ethylene glycol plus water in the ratio of 40%:60% and 3) ethylene glycol plus water in the ratio of 50%:50% by weight. Based on the experimental results, it is observed that the thermal conductivity of TiO₂ nanofluids, considered in the present investigation, increases with increase in percentage of volume concentration of TiO₂ and also with temperature. Current experimental investigation presents valuable data on the measured thermal conductivity of TiO₂ nanofluids for very low volume concentrations from 0.2% to 1.0% of nanoparticles in the temperature range of 30 °C–70 °C.     

Thermal conductivity of ethylene glycol and water mixture based Fe3O4 nanofluid

Thermal conductivity of ethylene glycol and water mixture based Fe₃O₄ nanofluid has been investigated experimentally. Magnetic Fe₃O₄ nanoparticles were synthesized by chemical co-precipitation method and the nanofluids were prepared by dispersing nanoparticles into different base fluids like 20:80%, 40:60% and 60:40% by weight of the ethylene glycol and water mixture. Experiments were conducted in the temperature range from 20 °C to 60 °C and in the volume concentration range from 0.2% to 2.0%. Results indicate that the thermal conductivity increases with the increase of particle concentration and temperature. The thermal conductivity is enhanced by 46% at 2.0 vol.% of nanoparticles dispersed in 20:80% ethylene glycol and water mixture compared to other base fluids. The theoretical Hamilton–Crosser model failed to predict the thermal conductivity of the nanofluid with the effect of temperature. A new correlation is developed for the estimation of thermal conductivity of nanofluids based on the experimental data.     

The effect of alumina/water nanofluid particle size on thermal conductivity

This study examines the effect of particle size, temperature, and weight fraction on the thermal conductivity ratio of alumina(Al₂O₃)/water nanofluids. A Al₂O₃/water nanofluid produced by the direct synthesis method served as the experimental sample, and nanoparticles, each of a different nominal diameter (20, 50, and 100 nm), were dispersed into four different concentrations (0.5, 1.0, 1.5, and 2.0 wt%). This experiment measured the thermal conductivity of nanofluids with different particle sizes, weight fractions, and working temperatures (10, 30, 50 °C). The results showed a correlation between high thermal conductivity ratios and enhanced sensitivity, and small nanoparticle size and higher temperature. This research utilized experimental data to construct a new empirical equation, taking the nanoparticle size, temperature, and lower weight fraction of the nanofluid into consideration. Comparing the regression results with the experimental values, the margin of error was within ?3.5% to +2.7%. The proposed empirical equation showed reasonably good agreement with our experimental results.     

ReD-dependence of dynamic thermal conductivities of nanofluids

The dynamic thermal conductivity of nanofluids is examined under fully developed laminar flow conditions (440 < Re_D < 818) in a circular tube (1.753-mm ID) subjected to a uniform heat flux. The experiment has been conducted using nanofluids containing Al₂O₃ nanoparticles of 45-nm nominal diameter dispersed in DI water at two volume concentrations of 2% and 4%. At the small Reynolds numbers, the measured dynamic thermal conductivity is lower by as much as 16% in comparison with the corresponding static thermal conductivity at Re_D = 0. The dynamic thermal conductivity gradually increases with increasing Re_D, but never exceeds the static conductivity level up to the highest tested Reynolds number of 818. The hot wall-to-fluid temperature gradient drives thermophoretic depletion of nanoparticles from the wall to the tube center. The lower dynamic thermal conductivity at the small Reynolds number is believed to be attributed to the reduced effective conduction near the wall where the nanoparticle concentration is relatively lower than in the core of the tube. In contrast, examination of the heat transfer between the suspended nanoparticles and the surrounding water molecules shows that the nanoparticle thermophoretic velocities increase with increasing Reynolds number. The increased thermophoretic velocities inside the nanofluid tend to compensate for the aforementioned reduced thermal conductivity near the wall, and this is conjectured to account for the recovery of the dynamic thermal conductivity to the static level at the higher Reynolds number.     

Rheology and thermal conductivity of non-porous silica (SiO2) in viscous glycerol and ethylene glycol based nanofluids

Nanofluids are advanced fluids with novel properties useful for diverse applications in heat transfer. This article reports the experimental determination of thermal conductivity and viscosity for silica (SiO₂) nanofluids in ethylene glycol (EG) and glycerol (G) as base fluids. A two-step method was applied to disperse the nanoparticles in the base fluids for the particle volume concentration of 0.5–2.0%. The dispersion stability of the nanofluids was evaluated by zeta potential analysis. All the measurements were performed in the temperature interval from 30 °C to 80 °C. It was found that the thermal conductivity increases with temperature. The SiO₂-EG showed higher conductivity enhancement than SiO₂-G nanofluids. Rheological analyses confirm Newtonian behavior for silica nanofluids within shear rate range of 20–100 s^− 1. Viscosity decreases with an increase in operating temperature. The SiO₂-EG demonstrated very weak temperature dependence compared to the SiO₂-G nanofluids. Based on these measured properties, the criterion for heat transfer performance was determined. Furthermore, equations have been proposed with accuracy within ± 10% deviations to predict the thermal conductivity and dynamic viscosity of EG and G-based SiO₂ nanofluids.     

Experimental investigation and development of new correlation for thermal conductivity and viscosity of BioGlycol/water based SiO2 nanofluids

Nanofluids are a new class of engineered heat transfer fluids which exhibit superior thermophysical properties and have potential applications in numerous important fields. In this study, nanofluids have been prepared by dispersing SiO₂ nanoparticles in different base fluids such as 20:80% and 30:70% by volume of BioGlycol (BG)/water (W) mixtures. Thermal conductivity and viscosity experiments have been conducted in temperatures between 30 °C and 80 °C and in volume concentrations between 0.5% and 2.0%. Results show that thermal conductivity of nanofluids increases with increase of volume concentrations and temperatures. Similarly, viscosity of nanofluid increases with increase of volume concentrations but decreases with increase of temperatures. The maximum thermal conductivity enhancement among all the nanofluids was observed for 20:80% BG/W nanofluid about 7.2% in the volume concentration of 2.0% at a temperature of 70 °C. Correspondingly among all the nanofluids maximum viscosity enhancement was observed for 30:70% BG/W nanofluid about 1.38-times in the volume concentration of 2.0% at a temperature of 70 °C. The classical models and semi-empirical correlations failed to predict the thermal conductivity and viscosity of nanofluids with effect of volume concentration and temperatures. Therefore, nonlinear correlations have been proposed with 3% maximum deviation for the estimation of thermal conductivity and viscosity of nanofluids.     

Thermal conductivity measurement and characterization of binary nanofluids

Binary nanofluids, nanoparticle suspensions in binary mixture, are developed to enhance the heat and mass transfer performance of absorption refrigeration cycles. To stabilize the nanoparticles in a strong electrolyte, polymer is used as a steric stabilizer. The effective thermal conductivities of the binary nanofluids with the concentrations of nanoparticle up to 0.1 vol% are measured using the transient hot wire method. Comparing the thermal conductivity change with time, it is found that the dispersion stability of nanofluids is a dominant factor for enhancing the thermal conductivity of binary nanofluids. It is also found that the thermal conductivity of the binary nanofluids (H₂O/LiBr binary mixture with Al₂O₃ nanoparticles) increases with the particle volume concentration and enhances by 2.2% at 0.1 vol% concentration condition. Also a modified dimensionless group is proposed to find the maximum radius of nanoparticles to maintain stable nanofluids. In this study, it was estimated ～1.3 μm.     

Investigation of thermal conductivity and viscosity of Fe3O4 nanofluid for heat transfer applications

Experimental investigations and theoretical determination of effective thermal conductivity and viscosity of magnetic Fe₃O₄/water nanofluid are reported in this paper. The nanofluid was prepared by synthesizing Fe₃O₄ nanoparticles using the chemical precipitation method, and then dispersed in distilled water using a sonicator. Both experiments were conducted in the volume concentration range 0.0% to 2.0% and the temperature range 20 °C to 60 °C. The thermal conductivity and viscosity of the nanofluid were increased with an increase in the particle volume concentration. Viscosity enhancement was greater compared to thermal conductivity enhancement under at same volume concentration and temperature. Theoretical equations were developed to predict thermal conductivity and viscosity of nanofluids without resorting to the well established Maxwell and Einstein models, respectively. The proposed equations show reasonably good agreement with the experimental results.     

Experimental study on the thermo-physical properties of car engine coolant (water/ethylene glycol mixture type) based SiC nanofluids

The engine coolant (water/ethylene glycol mixture type) becomes one of the most commonly used commercial fluids in cooling system of automobiles. However, the heat transfer coefficient of this kind of engine coolant is limited. The rapid developments of nanotechnology have led to emerging of a relatively new class of fluids called nanofluids, which could offer the enhanced thermal conductivity (TC) compared with the conventional coolants. The present study reports the new findings on the thermal conductivity and viscosity of car engine coolants based silicon carbide (SiC) nanofluids. The homogeneous and stable nanofluids with volume fraction up to 0.5 vol.% were prepared by the two-step method with the addition of surfactant (oleic acid). It was found that the thermal conductivity of nanofluids increased with the volume fraction and temperature (10–50 °C), and the highest thermal conductivity enhancement was found to be 53.81% for 0.5 vol.% nanofluid at 50 °C. In addition, the overall effectiveness of the current nanofluids (0.2 vol.%) was found to be ~ 1.6, which indicated that the car engine coolant-based SiC nanofluid prepared in this paper was better compared to the car engine coolant used as base liquid in this study.     

Thermal and fluid dynamic behaviors of confined laminar impinging slot jets with nanofluids

Heat transfer enhancement technologies play an important role in research and industrial fields; thus, they have been widely applied to many applications as in refrigeration, automotive, aerospace, and process industry. For example, heat transfer can be passively enhanced by increasing the thermal conductivity of the working fluids, adopting nanofluids, or actively by employing impinging jets.In this paper a numerical analysis on confined impinging slot jets working with pure water or water/Al₂O₃ based nanofluids is presented. The flow is laminar and a constant uniform temperature is applied on the target surface. The single-phase model approach has been adopted in order to describe the nanofluid behavior and different particle volume concentrations have been considered. Moreover, simulations have been performed for different geometric ratios in order to take into account the confining effects and Reynolds numbers. The behavior of the system has been analyzed in terms of average and local convective heat transfer coefficient, Nusselt number, and required pumping power profiles. Correlations for stagnation point and average Nusselt number for 100 ≤ Re ≤ 400, 0% ≤ ϕ ≤ 5% and 4 ≤ H/W ≤ 10 are provided.     

Thermal conductivity measurement of methanol-based nanofluids with Al2O3 and SiO2 nanoparticles

In this study, the methanol-based nanofluids with Al₂O₃ and SiO₂ nanoparticles are prepared by dispersing nanoparticles in pure methanol using an ultrasonic equipment. The main objective of this paper is to measure the thermal conductivity of the methanol-based nanofluids. We have also measured the zeta potential, particle size and Tyndall effect for the present nanofluids. The transient hot-wire method is applied for measuring the thermal conductivity of methanol-based nanofluids. The measurement uncertainty in repeatability is obtained as 1.95% for deionized (DI) water and 1.34% for pure methanol, respectively. The effective thermal conductivity of methanol-based nanofluids is measured at a temperature of 293.15 K. The results show that the thermal conductivity increases with an increase of the nanoparticle volume fraction, and the enhancement is observed to be 10.74% and 14.29% over the basefluid at the volume fraction of 0.5vol% for Al₂O₃ and SiO₂ nanoparticles, respectively. Clustering of nanoparticles is considered to be the main reason for the thermal conductivity enhancement.     

Heat transfer and friction factor of water based TiO2 and SiO2 nanofluids under turbulent flow in a tube

The heat transfer coefficient and friction factor of TiO₂ and SiO₂ water based nanofluids flowing in a circular tube under turbulent flow are investigated experimentally under constant heat flux boundary condition. TiO₂ and SiO₂ nanofluids with an average particle size of 50 nm and 22 nm respectively are used in the working fluid for volume concentrations up to 3.0%. Experiments are conducted at a bulk temperature of 30 °C in the turbulent Reynolds number range of 5000 to 25,000. The enhancements in viscosity and thermal conductivity of TiO₂ are greater than SiO₂ nanofluid. However, a maximum enhancement of 26% in heat transfer coefficients is obtained with TiO₂ nanofluid at 1.0% concentration, while SiO₂ nanofluid gave 33% enhancement at 3.0% concentration. The heat transfer coefficients are lower at all other concentrations. The particle concentration at which the nanofluids give maximum heat transfer has been determined and validated with property enhancement ratio. It is observed that the pressure drop is directly proportional to the density of the nanoparticle.     

Effect of rotating cylinder on heat transfer in a square enclosure filled with nanofluids

Convective heat transfer in a differentially heated square enclosure with an inner rotating cylinder is studied theoretically. The free space between the cylinder and the enclosure walls is filled with water–Ag, water–Cu, water–Al₂O₃ or water–TiO₂ nanofluids. The governing equations are formulated for velocity, pressure and temperature formulation and are modeled in COMSOL, a partial differential equation (PDE) solver based on the Galerkin finite element method (GFEM). The governing parameters considered are the solid volume fraction, 0.0 ? ? ? 0.05, the cylinder radius, 0 ? R ? 0.3 and the angular rotational velocity, ?1000 ? Ω ? 1000. The results are presented to show the effect of these parameters on the heat transfer and fluid flow characteristics. It is found that the strength of the flow circulation is much stronger for a higher nanoparticle concentration, a better thermal conductivity value and a smaller cylinder with a faster, negative rotation. The maximum heat transfer are obtained at a high nanoparticle concentration with a good conductivity value, a slow positive rotation and a moderate cylinder size located in the center of the enclosure.     

Transport properties of ultra-low concentration CuO–water nanofluids containing non-spherical nanoparticles

CuO–water nanofluids were prepared from non-spherical CuO nanoparticles by dispersing them in water through the aid of ultrasonication along with the use of Tiron as dispersant. Thermal conductivity enhancements of 13% and 44% have been obtained with 0.016 vol% CuO–water nanofluids at 28 °C and 55 °C respectively, which could be attributed to the high aspect ratio and Brownian motion of nanoparticles. Correlations have been developed to predict the influence of temperature (28–55 °C) and nanoparticles volume concentration (<0.016 vol%) on relative viscosity and thermal conductivity ratio. The results indicate the potential of this nanofluid for thermal management applications.     

Experimental investigation of oxide nanofluids laminar flow convective heat transfer

In the present investigation nanofluids containing CuO and Al₂O₃ oxide nanoparticles in water as base fluid in different concentrations produced and the laminar flow convective heat transfer through circular tube with constant wall temperature boundary condition were examined. The experimental results emphasize that the single phase correlation with nanofluids properties (Homogeneous Model) is not able to predict heat transfer coefficient enhancement of nanofluids. The comparison between experimental results obtained for CuO / water and Al₂O₃ / water nanofluids indicates that heat transfer coefficient ratios for nanofluid to homogeneous model in low concentration are close to each other but by increasing the volume fraction, higher heat transfer enhancement for Al₂O₃ / water can be observed.     

Thermal conductivity of Cu/TiO2–water/EG hybrid nanofluid: Experimental data and modeling using artificial neural network and correlation

In the present paper, the thermal conductivity of hybrid nanofluids is experimentally investigated. The studied nanofluid was produced using a two-step method by dispersing Cu and TiO₂ nanoparticles with average diameter of 70 and 40 nm in a binary mixture of water/EG (60:40). The properties of this nanofluid were measured in various solid concentrations (0.1, 0.2, 0.4, 0.8, 1, 1.5, and 2%) and temperatures ranging from 30 to 60 °C. Next, two new correlations for predicting the thermal conductivity of studied hybrid nanofluids, in terms of solid concentration and temperature, are proposed that use an artificial neural network (ANN) and are based on experimental data. The results indicate that these two new models have great ability to predict thermal conductivity and show excellent agreement with the experimental results.     

Simulation of heat transfer enhancement in nanofluids using dissipative particle dynamics

The current paper applied dissipative particle dynamics (DPD) approach to investigate heat transfer within nanofluids. The DPD approach was applied to study natural convection in a differential heated enclosure by considering the viscosity and the thermal conductivity of the nanofluid to be dual function of temperature and volume fraction of nanoparticles. Experimental data for viscosity and thermal conductivity are incorporated in the current DPD model to mimic energy transport within nanofluids. This incorporation is done through the modification of the dissipative weighting function that appears in the dissipative force vector and the dissipative heat flux. For the entire range of Rayleigh number considered in this study, it was found that the DPD results show a deterioration in heat transfer in the enclosure due to the presence of nanoparticles for φ > 4%. However, some slight enhancement is shown to take place for small volume fraction of nanoparticles, φ ≤ 4%. The DPD results experienced some degree of compressibility at high values of Rayleigh number Ra ≥ 10⁵.