Experimental investigation toward obtaining the effect of interfacial solid-liquid interaction and basefluid type on the thermal conductivity of CuO-loaded nanofluids (original) (raw)
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Experimental Investigation on Viscosity of the Nanofluids with Different Parameters
— In this experimental investigation, the effect of concentration, size, and temperature on the viscosity of Al 2 O 3-water nanofluid has been studied. The experiments performed on the various concentration of Al 2 O 3-water nanofluid with particle size 13 nm, 50 nm and 150 nm in the temperature range of 25-80 ℃. The viscosity data were collected using stress-controlled Bohlin Gemini rheometer. The effect of pH value on the viscosity has also been studied. Exponentially decrease in viscosity with an increase in temperature was observed. It has been analyzed and found that the viscosity decreases with temperature and follow the same pattern of decrement for all concentration and size of nanofluid. Al 2 O 3-water nanofluid has been found Newtonian behavior for 50 nm and 150 nm particle size samples at the ambient temperature in the shear rate range 100 s-1 to 250 s-1 .
A brief review on viscosity of nanofluids
International Nano Letters, 2014
Since the past decade, rapid development in nanotechnology has produced several aspects for the scientists and technologists to look into. Nanofluid is one of the incredible outcomes of such advancement. Nanofluids (colloidal suspensions of metallic and nonmetallic nanoparticles in conventional base fluids) are best known for their remarkable change to enhanced heat transfer abilities. Earlier research work has already acutely focused on thermal conductivity of nanofluids. However, viscosity is another important property that needs the same attention due to its very crucial impact on heat transfer. Therefore, viscosity of nanofluids should be thoroughly investigated before use for practical heat transfer applications. In this contribution, a brief review on theoretical models is presented precisely. Furthermore, the effects of nanoparticles' shape and size, temperature, volume concentration, pH, etc. are organized together and reviewed.
The viscosity of nanofluids: a review of the theoretical, empirical and numerical models.
The enhanced thermal characteristics of nanofluids have made it one of the most raplidly growing research areas in the last decade. Numerous researches have shown the merits of nanofluids in heat transfer equipment. However, one of the problems is the increase in viscosity due to the suspension of nanoparticles. This viscosity increase is not desirable in the industry, especially when it involves flow, such as in heat exchanger or microchannel applications where lowering pressure drop and pumping power are of significance. In this regard, a critical review of the theoretical, empirical, and numerical models for effective viscosity of nanofluids is presented. Furthermore, different parameters affecting the viscosity of nanofluids such as nanoparticle volume fraction, size, shape, temperature, pH, and shearing rate are reviewed. Other properties such as nanofluid stability and magnetorheological characteristics of some nanofluids are also reviewed. The important parameters influencing viscosity of nanofluids are temperature, nanoparticle volume fraction, size, shape, pH, and shearing rate. Regarding the composite of nanofluids, which can consist of different fluid bases and different nanoparticles, different accurate correlations for different nanofluids need to be developed. Finally, there is a lack of investigation into the stability of different nanofluids when the viscosity is the target point.
Latest developments on the viscosity of nanofluids
International Journal of Heat and Mass Transfer, 2012
The past decade has seen the rapid development of nanofluids science in many aspects. Number of research is conducted that is mostly focused on the thermal conductivity of these fluids. However, nanofluid viscosity also deserves the same attention as thermal conductivity. In this paper, different characteristics of viscosity of nanofluids including nanofluid preparation methods, temperature, particle size and shape, and volume fraction effects are thoroughly compiled and reviewed. Furthermore, a precise review on theoretical models/correlations of conventional models related to nanofluid viscosity is presented. The existing experimental results about the nanofluids viscosity show clearly that viscosity augmented accordingly with an increase of volume concentration and decreased with the temperature rise. However, there are some contradictory results on the effects of temperature on viscosity. Moreover, it is shown that particle size has some noteworthy effects over viscosity of nanofluids.
International Communications in Heat and Mass Transfer, 2022
In practice, nanofluids’ thermal conductivity and viscosity are the most important parameters in engineering applications. Viscosity affects pumping performance. Theoretical viscosity correlations are widely used in numerical studies. However, existing correlations show an underestimation of the actual viscosity compared to the measurement results. Although many nanofluid viscosity correlations have been developed, there is no generally accepted correlation. This paper reviews the theoretical, numerical, and experimental viscosity correlations and proposes a new correlation based on an analysis of approximately 1200 experimental and 4000 theoretical data tested for about 50 types of nanofluids in the temperature range 273–333 K and particle diameters 2–300 nm. The studied volume fraction range for the nanofluids was up to 10%. Existing correlations take into account the impact of up to two to three parameters The new viscosity correlation is proposed to predict the effective viscosity of nanofluids based on regression analysis of theoretical and experimental viscosity results, and it considers several factors that significantly affect the effective viscosity of nanofluids, such as nanoparticle diameter, density, temperature, types of nanoparticles, and base fluid.
A new model for calculating the effective viscosity of nanofluids
Journal of Physics D: Applied Physics, 2009
In this paper a new equation for calculating the nanofluid viscosity by considering the Brownian motion of nanoparticles is introduced. The relative velocity between the base fluid and nanoparticles has been taken into account. This equation presents the nanofluid viscosity as a function of the temperature, the mean nanoparticle diameter, the nanoparticle volume fraction, the nanoparticle density and the base fluid physical properties. In developing the model a correction factor is introduced to take into account the simplification that was applied on the boundary condition. It is calculated by using very limited experimental data for nanofluids consisting of 13 nm Al 2 O 3 nanoparticles and water and 28 nm Al 2 O 3 nanoparticles and water. The predicted results are then compared with many other published experimental results for different nanofluids and very good concordance between these results is observed. Compared with the other theoretical models that are available in the literature, the presented model, in general, has a higher accuracy and precision.
Experimental investigations of the viscosity of nanofluids at low temperatures
Applied Energy, 2012
The effects due to temperature and shearing time on viscosity for Al 2 O 3 /water and CNT/water based nanofluids at low concentration and low temperatures are experimentally investigated. The viscosity data were collected using a stress-controlled rheometer equipped with parallel plate geometry under up and down shear stress ramp. CNT and Al2O3 water based nanofluids exhibited hysteresis behaviour when the stress is gradually loaded and unloaded, depending also on shearing time. Experiments also showed that the nanofluid suspensions indicated either Newtonian or non-Newtonian behaviour, depending on shear rate. CNT water based nanofluid behaves as Newtonian fluid at high shear rate whereas Al 2 O 3 water based nanofluid is non-Newtonian within the range of low temperatures investigated.
A review and analysis on influence of temperature and concentration of nanofluids
The Prandtl number, Reynolds number and Nusselt number are functions of thermophysical properties of nanofluids and these numbers strongly influence the convective heat transfer coefficient. The pressure loss and the required pumping power for a given amount of heat transfer depend on the Reynolds number of flow. The thermophysical properties vary with temperature and volumetric concentration of nanofluids. Therefore, a comprehensive analysis has been performed to evaluate the effects on the performance of nanofluids due to variations of density, specific heat, thermal conductivity and viscosity, which are functions of nanoparticle volume concentration and temperature. Two metallic oxides, aluminum oxide (Al 2 O 3 ), copper oxide (CuO) and one nonmetallic oxide silicon dioxide (SiO 2 ), dispersed in an ethylene glycol and water mixture (60:40 by weight) as the base fluid have been studied.
A model for temperature and particle volume fraction effect on nanofluid viscosity
Journal of Molecular Liquids, 2010
A theory based model is presented for viscosity of nanofluids and evaluated over the entire range of temperature and volume fraction of nanoparticles. The model is based on Eyring's viscosity model and the nonrandom two liquid (NRTL) model for describing deviations from ideality (Eyring-NRTL model). The equation for viscosity is composed of a contribution due to nonrandom mixing on the local level and another energetic section related to the strength of intercomponent interactions which inhibit components from being removed from their most favorable equilibrium position in the mixture. The experimental data were used to evaluate existing models which do not contain adjustable parameters and Eyring-NRTL model. The Eyring-NRTL model was found to agree well with the experimental data with the restriction that contains adjustable parameters which were interactions in the form of NRTL constants. However, the agreement was even better if temperature dependent interaction parameters were used. Comparisons of predicted and actual viscosity over the entire temperature and volume fraction range illustrate an improvement over the conventional nanofluid viscosity models with 2.91% AAD.