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.      

Effect of Nanoparticles on Thermal Properties Enhancement in Different Oils – A Review

The development of stable dispersion of nanoparticles in different oils is gaining momentum for close circuit applications as most of the mineral oils used are not very good thermal conductors. The enhancement of thermal conductivity with optimum enhancement of viscosity of oil with nanoparticles poses a serious challenge for use of such fluids in cooling. Transformer oil, mineral oil, silicon oil, hydrocarbon fuels, biodiesel, and some organic solutions have been used as the base fluids for studying the effect of nanoparticles for improving thermal efficiency. Innovative heat transfer fluids are produced by suspending metallic or nonmetallic nanometer-sized solid particles. Although a large number of sources are available on water-based nanofluids, the number of such reports on oil-based nanofluids is rather limited. The aim of this article is to summarize recent developments on the preparation methods of nanofluids based on oil, its stability, thermal conductivity enhancement, nanoparticle effect on viscosity, heat transfer characteristics, breakdown voltage, dielectric properties, and applications of such nanofluids.     

Physics and mechanics of heat exchange processes in nanofluid flows

Nanofluids present a new type of dispersed fluids consisting of a carrier fluid and solid nanoparticles. Unusual properties of nanofluids, particularly high thermal conductivity, make them eminently suitable for many thermophysical applications, e.g., for cooling of equipment, designing of new heat energy transportation and production systems and so on. This requires a systematic study of heat exchange properties of nanofluids. The present paper contains the measurement results for the heat transfer coefficient of the laminar and turbulent flow of nanofluids on the basis of distilled water with silica, alumina and copper oxide particles in a minichannel with circular cross section. The maximum volume concentration of particles did not exceed 2%. The dependence of the heat transfer coefficient on the concentration and size of nanoparticles was studied. It is shown that the use of nanofluids allows a significant increase in the heat transfer coefficient as compared to that for water. However, the obtained result strongly depends on the regime of flow. The excess of the heat transfer coefficient in the laminar flow is only due to an increase in the thermal conductivity coefficient of nanofluid, while in the turbulent flow the obtained effect is due to the ratio between the viscosity and thermal conductivity of nanofluid. The viscosity and thermal conductivity of nanofluids depend on the volume concentration of nanoparticles as well as on their size and material and are not described by classical theories. That is why the literature data are diverse and contradictory; they do not actually take into account the influence of the mentioned factors (size and material of nanoparticles). It has been shown experimentally and by a molecular dynamics method that the nanofluid viscosity increases while the thermal conductivity decreases with the decreasing dispersed particle size. It is found experimentally for the first time that the nanofluid viscosity coefficient depends on the particle material. The higher is the density of particles, the higher is the thermal conductivity coefficient of nanofluid.     

Investigation of thermal conductivity and rheological properties of vegetable oil based hybrid nanofluids containing Cu–Zn hybrid nanoparticles

Vegetable oils (Ground nut) are being investigated to serve as a possible substitute for non-biodegradable mineral oils, which are currently being used as metal-cutting fluids in machining processes. In this study, thermophysical properties of hybrid nanofluids (vegetable oil) to be used as metalworking cutting fluids are investigated. In-situ synthesis of copper (Cu) and zinc (Zn) combined hybrid particles is performed by mechanical alloying with compositions of 50:50, 75:25, and 25:75 by weight. Characterizations of the synthesized powder were carried out using X-ray diffraction, a particle size analyzer, FE-SEM, and TEM. Hybrid nanofluids with all the three combinations of hybrid nanoparticles were prepared by dispersing them into a base fluid (vegetable oil). The thermophysical properties, such as thermal conductivity and viscosity, were studied for various volume concentrations and at a range of temperatures. Experimental results have shown enhancement in thermal conductivity in all cases and also an increase in viscosity. The enhancement in viscosity is similar in all three combinations, as the particle size and shape are almost identical. The enhancement in thermal conductivity is higher in Cu–Zn (50:50), resulting in better enhancement in thermal conductivity due to the Brownian motion of the particles and higher thermal conductivity of the nanoparticles incorporated.     

Modeling of thermal conductivity of nanofluids by modifying Maxwell’s equation using cell model approach

Nanofluid is an innovative heat transfer fluid with superior potential for enhancing the heat transfer performance of conventional fluids. Though many attempts have been made to investigate the abnormal high thermal conductivity of nanofluids, the existing models cannot precisely predict the same. An attempt has been made to develop a model for predicting the thermal conductivity of different types of nanofluids. The model presented here is derived based on the fact that thermal conductivity of nanofluids depends on thermal conductivity of particle and fluid as well as micro-convective heat transfer due to Brownian motion of nanoparticles. Novelty of the article lies in giving a unique equation which predicts thermal conductivity of nanofluids for different concentrations and particle sizes which also correctly predicts the trends observed in experimental data over a wide range of particle sizes, temperatures, and particle concentrations.     

抛物槽式太阳能集热器内合成油基纳米流体传热特性的数值模拟

对Al₂O₃-合成油纳米流体在槽式太阳能集热管内的传热特性进行流体动力学数值模拟,重点考察纳米流体导热系数模型的影响。通过与管内Nusselt数半经验模型的预测结果对比,表明使用考虑布朗运动的纳米流体导热系数模型可较好地预测集热管内传热特性。研究表明纳米颗粒与流体基液的相对运动具有促进集热管内传热的作用。最后,定量研究纳米颗粒添加量对提高基础流体平均传热系数的影响,显示纳米流体在太阳能集热器中具有巨大应用潜力。     

纳米流体对流换热系数增大机理

纳米流体流动换热能力优于传统流体介质.研究了纳米流体热物性的提升和热散射对其对流换热系数的影响.结果表明,纳米颗粒的加入,优化了介质的热物性,增大了导热系数,强化了纳米流体内颗粒、流体以及流道管壁碰撞和相互作用,同时加强了流体的混合脉动和湍流,从而增大了对流换热系数. 关键词： 纳米流体 换热系数 热散射     

基于基液连续假设的大体系Cu-H2O纳米流体输运特性的模拟研究

分子动力学模拟是研究纳米流体的输运特性的重要手段, 但计算量庞大. 为研究能体现流动传热过程的大体系纳米流体的输运特性, 本文对基液采用连续介质假设, 将基液的势能拟合在纳米团簇的势能中, 大幅度减小了计算量, 使得大体系输运特性的模拟成为可能, 且模拟结果与多组实验结果吻合较好. 采用此方法模拟研究了速度梯度剪切对Cu-H₂O纳米流体颗粒聚集过程和聚集特性的影响, 进而对Cu-H₂O纳米流体在流动传热过程中的热导率和黏度进行了模拟计算, 定量揭示了宏观流动传热过程中不同的速度梯度、速度、平均温度和温度梯度对于Cu-H₂O纳米流体热导率和黏度的影响.     

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.     

Prediction of thermal conductivity and viscosity of nanofluids by molecular dynamics simulation

Limitations of conventional heat transfer fluids in different industries because of their poor thermal conductivity made heat transfer improvement in working fluids was performing, as a new method of advanced heat transfer. Therefore, the dispersion solid particle idea in fluids, which has been started with mili- and micrometer particles, completed by using nanoparticles and today nanofluids have been found to provide a considerable heat transfer and viscosity enhancement in comparison to conventional fluids such as water, ethylene glycol, and engine oil. In this study, molecular dynamics simulation was used to predict thermal conductivity and viscosity of nanofluids. Water was used as a base fluid. The simple point charge-extended (SPC/E) model was used for simulation of water and Ewald sum method for electrostatic interactions. Lennard–Jones potential for Van der Waals interactions, KTS potential for water and SiO₂ and Spor and Heinzinger correlation for water and Pt were used. The results were compared with experimental data. For investigation of the effect of temperature, simulation was done for three temperatures of 20, 30, and 50?C. The results showed that the ratio of thermal conductivity of nanofluid to base fluid and viscosity will decrease as the temperature increases. The effect of the concentration of nanoparticle was studied for three different concentrations, namely, 0.45, 1.85, and 4%. The thermal conductivity of nanofluid increases with increasing the concentration. Moreover, the effect of two nanoparticle sizes (i.e., 5 and 7 nm) on the thermal conductivity of nanofluid was investigated. It was shown that an increase in the size causes a decrease in the thermal conductivity. Finally, by replacing the SiO₂nanoparticle with a Pt nanoparticle in the nanofluid, it was observed that the kind of nanoparticle had not a considerable effect on increasing the thermal conductivity of nanofluid.     

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.     

Effect of Ag nanoparticle addition and ultrasonic treatment on a stable TiO2 nanofluid

Nanoparticles, when homogeneously dispersed in a base fluid, e.g. water, ethylene glycol etc. are commonly known as nanofluids. Nanofluids have gained attention in the scientific community for their enhanced thermal properties. One of the major problems in using nanofluids as a heat transfer medium for commercial applications is that, in most of the closed circuit industrial cooling processes, the cooling fluid has to be replaced after several cycles of cooling operation because of an increased presence of contaminants. If nanofluids were used as a coolant, it would be very hard to separate the nanoparticles from the waste fluid. The present work is aimed at the separation and recycling of nanoparticles from fluid waste by means of quick settling of titanium dioxide nanoparticles using silver nanoparticles along with ultrasonic treatment. It is observed that with increasing silver concentration and time of ultrasonication, the stability of the dispersion decreases. There is a value for both the silver concentration and ultrasonication time above which the settling time decreases drastically.     

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%.     

Investigation of Laminar Convective Heat Transfer of a Novel Tio2–Carbon Nanotube Hybrid Water-Based Nanofluid

The current study was conducted to investigate the convective heat transfer coefficient of a novel TiO₂–CNT hybrid nanofluid through the shell-and-tube heat exchanger under a laminar flow and the effects of temperature and mass fraction on it. TiO₂–CNT hybrid nanofluids were prepared using a new and modified hydrolysis technique. The thermal conductivity of the TiO₂–CNT hybrid nanofluid and other thermo-physical properties were assessed. Results indicate that the effective thermal conductivity and heat transfer coefficient of the base fluid was influenced significantly and increased by the 0.2 wt% of this novel hybrid nanofluid in distilled water.     

Effect of multipolar interaction on the effective thermal conductivity of nanofluids

Nanofluids or liquids with suspended nanoparticles are likely to be the future heat transfer media, as they exhibit higher thermal conductivity than those of liquids. It has been proposed that nanoparticles are apt to congregate and form clusters, and hence the interaction between nanoparticles becomes important. In this paper, by taking into account the interaction between nearest-neighbour inclusions, we adopt the multiple image method to investigate the effective thermal conductivity of nanofluids. Numerical results show that then the thermal conductivity ratio between the nanoparticles and fluids is large, and the two nanoparticles are close up and even touch, and the point-dipole theory such as Maxwell--Garnett theory becomes rough as many-body interactions are neglected. Our theoretical results on the effective thermal conductivity of CuO/water and Al$_{2}$O$_{3}$/water nanofluids are in good agreement with experimental data.     

Application of SAXS to the study of particle-size-dependent thermal conductivity in silica nanofluids

Knowledge of the size and distribution of nanoparticles in solution is critical to understanding the observed enhancements in thermal conductivity and heat transfer of nanofluids. We have applied small-angle X-ray scattering (SAXS) to the characterization of SiO₂ nanoparticles (10–30 nm) uniformly dispersed in a water-based fluid using the Advanced Photon Source at Argonne National Laboratory. Size distributions for the suspended nanoparticles were derived by fitting experimental data to an established model. Thermal conductivity of the SiO₂ nanofluids was also measured, and the relation between the average particle size and the thermal conductivity enhancement was established. The experimental data contradict models based on fluid interfacial layers or Brownian motion but support the concept of thermal resistance at the liquid–particle interface.     

A fractal model for heat transfer of nanofluids by convection in a pool

Based on the fractal distribution of nanoparticles, a fractal model for heat transfer of nanofluids is presented in the Letter. Considering heat convection between nanoparticles and liquids due to the Brownian motion of nanoparticles in fluids, the formula of calculating heat flux of nanofluids by convection is given. The proposed model is expressed as a function of the average size of nanoparticle, concentration of nanoparticle, fractal dimension of nanoparticle, temperature and properties of fluids. It is shown that the fractal model is effectual according to a good agreement between the model predictions and experimental data.     

Particle agglomeration and properties of nanofluids

The present study demonstrates the importance of actual agglomerated particle size in the nanofluid and its effect on the fluid properties. The current work deals with 5 to 100 nm nanoparticles dispersed in fluids that resulted in 200 to 800 nm agglomerates. Particle size distributions for a range of nanofluids are measured by dynamic light scattering (DLS). Wet scanning electron microscopy method is used to visualize agglomerated particles in the dispersed state and to confirm particle size measurements by DLS. Our results show that a combination of base fluid chemistry and nanoparticle type is very important to create stable nanofluids. Several nanofluids resulted in stable state without any stabilizers, but in the long term had agglomerations of 250 % over a 2 month period. The effects of agglomeration on the thermal and rheological properties are presented for several types of nanoparticle and base fluid chemistries. Despite using nanodiamond particles with high thermal conductivity and a very sensitive laser flash thermal conductivity measurement technique, no anomalous increases of thermal conductivity was measured. The thermal conductivity increases of nanofluid with the particle concentration are as those predicted by Maxwell and Bruggeman models. The level of agglomeration of nanoparticles hardly influenced the thermal conductivity of the nanofluid. The viscosity of nanofluids increased strongly as the concentration of particle is increased; it displays shear thinning and is a strong function of the level of agglomeration. The viscosity increase is significantly above of that predicted by the Einstein model even for very small concentration of nanoparticles.     

Convective Heat Transfer of a Cu/Water Nanofluid Flowing Through a Circular Tube

Abstract

Fluids in which nanometer-sized solid particles are suspended are called nanofluids. These fluids can be employed to increase the heat transfer rate in various applications. In this study, the convective heat transfer for Cu/water nanofluid through a circular tube was experimentally investigated. The flow was laminar, and constant wall temperature was used as thermal boundary condition. The Nusselt number of nanofluids for different nanoparticle concentrations, as well as various Peclet numbers, was obtained. Also, the rheological properties of the nanofluid for different volume fractions of nanoparticles were measured and compared with theoretical models. The results show that the heat transfer coefficient is enhanced by increasing the nanoparticle concentrations as well as the Peclet number.