Search

In this study, the stability and viscosity of four different nanoparticles are discussed in conjunction with the physical properties of these nanoparticles. The aim is to provide guidance for nanoparticle selection in future nanofluid applications. Additionally, our goal is to examine hybrid nanofluids in comparison to single nanofluids, exploring their potential benefits and evaluating their industrial applications. A two-stage approach was employed, using ethylene glycol (EG) as a base fluid, to create these nanofluids. Single nanofluids were formed with SiO2, TiO2, MWCNT, and ZnO nanoparticles at 0.1%, 0.5%, and 1% volume concentrations. Additionally, binary (SiO2–TiO2/EG), ternary (SiO2–TiO2–MWCNT/EG), and quaternary (SiO2–TiO2–MWCNT–ZnO/EG) hybrid nanofluids were formed with 0.1% volume concentrations. The dynamic viscosity of all nanofluids was evaluated over the temperature range of 20–50 °C. Analysis of nanofluids was extended by characterization studies using field emission transmission electron microscopy (FE-SEM), field emission scanning electron microscopy (FE-TEM), Zeta potential testing, and visual inspection. SiO2 nanoparticles exhibited the greatest stability, remaining in suspension for more than 28 days without sedimentation, while ZnO nanoparticles were the least stable, collapsing in < 7 days. Compared to ethylene glycol, ZnO/EG had the most increased viscosity (42.79%) at 20 °C and a 1% volume concentration. However, SiO2–TiO2–MWCNT/EG showed the largest decrease in viscosity (9.99%) at 20 °C. Hybrid nanofluids exhibit better viscosity performance compared to their base fluids and single nanofluids, enhancing the thermal efficiency of these heat transfer fluids. Additionally, this study is groundbreaking research as it emphasizes the efficiency of hybrid nanofluids as well as introducing quaternary nanofluids to the literature. [ABSTRACT FROM AUTHOR]

This paper presents a new way to hyper-optimise a flat plate solar collector using a combination of regenerated point clouds, constructal theory, and physics-informed machine learning (PIML). The behaviour of the flat plate solar collector is studied as solar radiation and ambient temperature change, using both precise numerical simulation and PIML. The novel hyper-optimisation method integrates these two approaches to improve the performance of the solar collector. In this method, the volume of fluid and solid structure of the flat plate solar collector (FPSC) is transformed into point clouds based on constructal theory. The point clouds are then regenerated into a continuous and uniform 3D geometry using optimised parameters. To put the modified version of the flat plate solar collector (FPSC) into practice, a computational method is used to generate a training data set for machine learning, specifically for neural networks. After thoroughly verifying the computational results, the PIM is trained using the generated training data set. This study marked the first time that a regular computational method is replaced with PIML output to reduce the computational cost of prediction. In the second layer of calculation, a deep neural network is used to make predictions based on the outputs generated by PIML. Seven independent parameters are used to predict heat transfer and efficiency over time, including time, heat flux, mass flow rate, inlet temperature, number of pairs and clusters, and volume fraction of nanofluid, while 16 hidden layers and 63 learnable neurons are engaged in this prediction layer. The geometry matrix is redefined by constructal theory principles in a series of iteration loops to generate the first flat plate solar collector based on constructal theory (CTFPSC). The results indicated that the hyper-optimisation method could reduce calculation costs by 18.31% compared with the regular computational method. In addition, the results reveal that maximum outlet temperatures are possible when Nc > 3 and Np> 5. [ABSTRACT FROM AUTHOR]

The heat transfer performance of a closed-loop pulsating heat pipe (CLPHP) having 2.2 mm inner diameter is experimentally studied at different filling ratios (40%, 50%, 60% and 70%) in a heat load range of 50–300 W using distilled water as the PHP fluid in vertical orientation with evaporator at the bottom. This experimental study validate that the optimum charging ratio is 50% for CLPHP while 40% filling ratio is good at lower heat inputs. Optimum filling ratio gives an average reduction of 26.0% and 14.8% in thermal resistance compared to 70% and 60% fill ratios. The heat transfer performance of the CLPHP is also studied at various volume fractions of graphene–water nanofluid using 50% filling ratio. This study shows that the optimum volume fraction for this CLPHP is 0.045%. The volume fraction of 0.045% gives an average reduction of 27.3% in thermal resistance for all heat inputs and a maximum temperature reduction of 24 °C for the evaporator wall temperature at 275 W heat input. When optimum values of filling ratio and volume fraction are used, CLPHP gives the best heat transfer performance. A correlation is also developed for CLPHP by considering the influential parameters. [ABSTRACT FROM AUTHOR]

Preparing and defining of thermal properties of new type hybrid nanofluids are essential to understand the fluidity mechanism of hybrid nanofluids and select suitable nanofluids in terms of application. This research aims to provide an alternative fluid for different applications and complete the new type of nanofluid necessity in the literature that has been reported by different research groups. In this current investigation, water-based ZnO–SiO2 hybrid nanofluid is prepared by using the two-step method, and thermal conductivity and dynamic viscosity values are experimentally specified. ZnO–SiO2 hybrid nanofluid has 0.5%, 0.75%, and 1% with 50% ZnO-50% SiO2; 33.3% ZnO-66.6% SiO2, and 66.6% ZnO-33.3% SiO2 nanoparticle mixtures. Thermal conductivity and dynamic viscosity are experimentally measured from 20 to 60 °C. Maximum thermal conductivity rising is 2.26%, and it is obtained for 1% ZnO0.66–SiO20.33 at 50 °C. Maximum dynamic viscosity increment is measured as 1.36 times of base fluid for 1% ZnO0.33–SiO20.66 at 50 °C. Changes in thermal properties are reasonable to use ZnO–SiO2 hybrid nanofluid in different thermal applications to increase system heat transfer rate and efficiency and reduce pressure drop and power consumption. Finally, two different regression equations are developed to predict the thermal conductivity and dynamic viscosity, respectively. [ABSTRACT FROM AUTHOR]

This study examined a room with a surface of 1.8 × 1.8 × 2.85 (m) and a well-insulated floor (adiabatic condition) and examined the heat exchange from the side surfaces and ceiling. In this closed room, the heat transfer effects with radiation were investigated while bringing them to comfort conditions ranging from 30 (°C) air temperature to 20–24 (°C). A computer with a power of 25 (W) as a source of heat, a person with an average metabolic activity of 50–70 (W) and a table were found in this closed room. In this study, the cooling of the room from the floor, ceiling and air conditioner was inquired while the computer was running, in a closed area under the specified heat transfer conditions. As a scenario, the air exchange coefficient was modeled via Ansys Fluent, fed with air of 15 (°C) with 1, 3, 5, 10, 15 air. In addition, the comfort values of the human wrist (the distance of 0.1 m) and the shoulder (the distance of 1.1 m) were researched according to ASHRAE-55. The obtained results were analyzed as a comparison of ACH results, and the comfort parameter values were analyzed by reading the sections taken from the ankle shoulder level and velocity, temperature, values according to ANSI/ASHRAE-55. The relative humidity was 50% in the room, while the metabolic activity is 1.2 (met). These parameters corresponded to the sitting position; the clothing effect was found to be 0.67 (clo). The novelty of this study encourages the production of the ideal CFD analysis on the thermal comfort conditions of a cooled room, the task of engineering. [ABSTRACT FROM AUTHOR]

We investigate, in this analysis, the entropy generation characteristics associated with the transport of nanofluid in a microfluidic channel under the combined influences of applied pressure gradient and electrical forcing. In our study, the nanofluid is subjected to an asymmetric cooling at the channel walls, while the conductive transport of heat through the channel walls is also taken into account. We show that the underlying thermo-electro-hydrodynamics of nanofluids in the channel lead to entropy generation, attributed to the irreversibilities associated with heat transfer, viscous dissipation, and Joule heating effects. We establish that a non-trivial interplay among these irreversibilities gives rise to an optimum value of the geometrical parameter, viz. the channel wall thickness (δ ), and the thermophysical parameters, viz. the thermal conductivity of the wall (γ) , Biot number (Bi), and the modified Peclet number ( Pe ¯ ), leading to a minimum entropy generation rate of the system. Also, we unveil through this study that changes in the electroosmotic parameter κ ¯ (representative of the EDL thickness) or the composition of the fluid (ϕ , the volume fraction of nanoparticles agglomerates) non trivially alter the optimum values of these parameters. Inferences drawn from this analysis may have consequences in the optimum design of thermal systems/devices, typically used for thermal management in micro-heat exchangers, micro-reactors, and micro heat pipes. [ABSTRACT FROM AUTHOR]

Thermal performance evaluation of TiO2-coated copper mesh wick in a cylindrical heat pipe with graphite nanofluid is experimentally analyzed at various inclinations, nanoparticle concentrations and power levels. Boiling heat transfer from the evaporator of a heat pipe depends on both thermal conductivity of the nanoparticle and suspension stability of the nanofluid. The lower the density of the nanoparticle, the better the suspension stability. Spherical graphite nanoparticles having lower density and good thermal conductivity quicken the heat transfer rate and hence the vaporization of base fluid. A hydrophilic coating of TiO2 is done on the copper wick structure to reduce the contact angle of graphite nanofluid. Results showed that the heat pipe worked well at 60° inclination compared to the other tested orientations. For this optimum condition, a reduction in 168.75% of thermal resistance is obtained compared with DI water with uncoated wick at horizontal position and also an improvement in thermal efficiency of 94.07% for 1.0 mass% particle loading. The enhancement in equivalent thermal conductivity is 90.87% for 1.0 mass% compared with DI water. Results from the repeatability test also confirm that the hydrophilic coating over the wick is stable, and results are repeatable. [ABSTRACT FROM AUTHOR]

Over many years, great efforts have been made to develop new fluids for heat transfer applications. In this paper, the thermal conductivity (TC) and viscosity of SiO2–P25 TiO2 (SiO2–P25) hybrid nanofluids were investigated for different nanoparticle volume concentrations (0.5, 1.0 and 1.5 vol%) at five various temperatures (20, 30, 40, 50 and 60 °C). The mixture ratio (SiO2:P25) in all prepared hybrid nanofluids was 1:1. Besides, pure SiO2, P25 nanofluids were prepared with the same concentrations for comparison with the hybrid nanofluids. The base fluid used for the preparation of nanofluids was a mixture of deionized water and ethylene glycol at a ratio of 5:1. Before preparing the nanofluids, the nanoparticles were analyzed with energy-dispersive X-ray analysis, scanning electron microscope, X-ray powder diffraction, and Fourier transform infrared spectroscopy. The zeta potentials of the prepared nanofluids except SiO2 nanofluids were above 30 mV. These nanofluids were visually observed for stability in many days. The TC enhancement of the hybrid nanofluid was higher than the pure nanofluid. In particular, with 1.0 vol% concentration, the maximum enhancement of SiO2, P25 and SiO2–P25 nanofluids were 7.5%, 9.9% and 10.5%, respectively. The rheology of the nanofluids was Newtonian. The viscosity increment of SiO2, P25 and hybrid nanofluids were 19%, 32% and 24% with 0.5 vol% concentration. A new correlation was developed for the TC and dynamic viscosity of SiO2–P25 hybrid nanofluid. [ABSTRACT FROM AUTHOR]

Magnetic cooling at room temperature is one of the world's newest technologies that can be considered as an alternative for vapor compression refrigeration systems. Magnetic cooling follows the magnetocaloric effect (MCE) phenomenon, which is justified by the change in entropy with respect to magnetic flux changes. In this research, a computational fluid dynamic (CFD) simulation of the magnetic refrigeration system is conducted in COMSOL Multiphysics 5.5 software with the geometry of sandwiched gadolinium layers and water channels. The magnetic cooling system can be analyzed in two aspects i.e. constant cooling load and zero cooling load. For this purpose, two performance indicators including the exergy efficiency and the minimum achievable temperature, can be defined for constant and zero cooling loads, respectively. Sensitivity analysis is used as a tool to understand the importance of operating parameters such as frequency, passing fluid's velocity, cold heat exchanger temperature, magnetization, or demagnetization time. The parametric study of the zero cooling load simulation reveals that high operating frequency ( f = 0.5 Hz ) besides low fluid velocity ( V = 0.05 m s - 1 ) results in a 51 °C temperature span. In addition, the exergy efficiency can reach the maximum value of 30 percent with respect to various velocity and frequency variables for laminated geometry. [ABSTRACT FROM AUTHOR]

Conical enclosures rely on the conical cavity and can be used as radiation concentrators. Two circular cross-section baffles were used to improve the heat transfer of this geometry. By changing the rigid fins to porous, it could improve the heat transfer. Al2O3/water nanofluid was also employed to enhance the heat transfer performance of the cavity. For this purpose, numerical analysis of three-dimensional natural convection heat transfer was performed in a conical cavity with two types of fins. The best combination of fins arrangement for the next step was selected using the differential evolutionary optimization method (D.E). In this case study, a new combination of laminar and turbulence methods was employed for the first time to increase the accuracy of the natural convection solution. This combination is based on the laminar solution by suppressing the perturbation parameter in the turbulence method which led to more accurate results. The analysis results showed that a conical cavity with optimized fin geometry can lead to a 23% increase in Nu. The best porosity for the inner fin was calculated 40% in the case of constant porosity. Ascending porosity along the fin, whose increase was more intense near the base and slower near the cone's tip, was the best variable porosity for the inner fin. [ABSTRACT FROM AUTHOR]

The heat exchanger pipe diameter has a significant effect on the flow characteristics as well as on the initial investment, operation and overall cost. Increasing fin dimensions increases the annulus hydraulic diameters. Even though the total volume of the heat exchanger remains unchanged between the finned and bare designs, the heat duty increases with increased heat transfer area for the finned design. The fins should be designed, and the dimensions should be calculated with special attention for different flow rates and heat exchanger dimensions. In this study, number, geometry and dimensions of the fins are determined using the algorithms available in the literature. The operational condition optimization is carried out accompanied with the cost analysis. In addition, the effects of the types of working fluids and fouled and clean cases are investigated for the total heat transfer enhancement in parallel with performance, lifetime and cost issues. A detailed analysis is presented for finned and unfinned double-pipe heat exchanger models for pure engine oil and its nanofluid mixtures with Ti, TiO2, Cu, CuO, Al and Al2O3 nanoparticles, multi-wall carbon nanotubes and graphene nanosheet having a constant particle concentration in the liquid phase. The nanofluid is flowing in annulus side, whereas the seawater is flowing in the tube side. It is observed that both the pressure drop and the pumping power increase with the increasing fin number and decrease with the cleanliness factor, whereas the total tube number decreases with increasing fin number. It is found that different types of nanofluids affect the cost and optimum annulus side velocity significantly. The results are summarized in several figures that consider the increasing Reynolds number with the cleanliness factor, the heat transfer coefficient and the pressure drop, the friction factor with changing mass flow rate and the cost values with corresponding annulus side velocities. Finally, the overall characteristics of the trend lines are provided in the figures. [ABSTRACT FROM AUTHOR]

The hybridization of nanoparticles is a concept employed for the improvement of the thermal properties of nanofluids. Presently, there is a scarcity of studies in the open literature concerning the influence of particle mass ratios of hybrid nanofluids on the thermal properties. Thus, this paper investigated the effect of temperatures (15–55 °C) and particle mass ratios (90:10, 80:20, 60:40, 40:60, and 20:80) on the viscosity and electrical conductivity of deionized water (DIW)-based γ-Al2O3 and MWCNT hybrid nanofluids. A two-process strategy was deployed to prepare the hybrid nanofluids at a volume concentration of 0.1%. The hybrid nanofluids were characterized for their morphology using a transmission electron microscope. Hybrid nanofluid stability was monitored using UV visible spectrophotometer, viscosity, and visual inspection methods. The prepared nanofluids were observed to be stable with relatively constant viscosity and absorbance values. At 55 °C, maximum enhancements of 442.9% and 26.3%, and 288.0% and 19.3% were recorded for the electrical conductivity and viscosity of Al2O3–MWCNT/DIW nanofluids at particle mass ratios of 90:10 and 20:80, respectively, in relation to DIW. Temperature increase was observed to significantly reduce the viscosity of hybrid nanofluids while the particle mass ratio considerably and positively impacted the electrical conductivity. The relatively low viscosity of the hybrid nanofluids coupled with its reduction under increasing temperature and its insignificance increase as the particle mass ratio of the Al2O3 nanoparticles increased to make them viable coolants for engineering applications. New correlations were proposed to accurately estimate the viscosity and electrical conductivity of the hybrid nanofluids. [ABSTRACT FROM AUTHOR]

Numerous researches to prepare and stabilize graphene-based nanofluids have been developed. [ABSTRACT FROM AUTHOR]

Graphene has attracted much attention from the science world because of its mechanical, thermal, and physical properties. Graphene nanofluid is well known for its easy synthesis, longer suspension stability, higher heat conductivity, lower erosion, corrosion, larger surface area/volume ratio, and lower demand for pumping power. This article is an audit of experimental outcome about the preparation and stability of graphene-based nanofluids. Numerous researches to prepare and stabilize graphene-based nanofluids have been developed, and it is indispensable to create a complete list of the approaches. This research work outlines the advancement on preparation and assessment methods and the techniques to enhance the stability of graphene nanofluids and outlook prospects. [ABSTRACT FROM AUTHOR]

Nowadays, various types of engine oils are widely used in lubricating and cooling internal combustion engines. In this study, the behavior of MWCNTs–SiO2 (30–70)/10W40 hybrid nanofluid as part of a new generation of engine oil is investigated experimentally. A mixture of SiO2, with 20–30 nm particle diameter, and MWCNT, with 3–5 nm inner and 5–15 nm outer nanoparticle diameter was dispersed into a base fluid of 10W40 engine oil. Then, the viscosity of the product was measured at nanofluid concentrations and temperatures, respectively, ranging from 0.05 to 1% and 5 to 55 °C, for different values of shear rate. Also, a sensitivity analysis to the solid volume fraction was performed at different temperatures. The results show that the behavior of the samples is well fitted with the pseudo-plastic Ostwald de Waele non-Newtonian model. The viscosity of the produced hybrid nano-lubricant is found to be 35% greater than that of pure engine oil. Because of the significant deviation between the measured viscosity and the values predicted by existing classical viscosity models, a new regression model is obtained. The R2 and adj. R2 for the model are computed as 0.988 and 0.977, respectively, signifying strong predictability with ± 3% margin of deviation. [ABSTRACT FROM AUTHOR]

The natural heat convection within a square enclosure filled with water–Al2O3 nanofluid has been studied numerically in the presence of a magnetic field. The effect of heat source geometry attached to the bottom wall on the Nusselt number was investigated by changing its nondimensional width and height, and side walls thickness of the enclosure ranging from 0.1 to 0.5, 0.1 to 0.8 and 0.05 to 0.2, respectively. A regression model has been obtained along with conducting a sensitivity analysis seeking an optimal heat transfer. Results, reveal that Nusselt number increases by enlarging the fin, and reaching a peak point before it declines. Thus, interestingly, the ever-increasing heat transfer by means of fin size does not retain and there is an optimal point wherein the maximum heat transfer occurs. Moreover, the thermal performance of the system largely depends on the fin size rather than the relative side walls thickness. However, its effect intensifies as the fin width increases. Results of optimization show that the maximum heat transfer occurs at W = 0.4615 , H = 0.6467 and L b = 0.2 . [ABSTRACT FROM AUTHOR]

A numerical investigation is carried out to assess the hydrothermal performance of a water-based hybrid nanofluid containing both Fe3O4 (magnetite) nanoparticles and carbon nanotubes (CNTs) in a heated tube in the presence of a constant non-uniform magnetic field. The magnetic field is created by three pairs of permanent magnets. The effects of Reynolds number, magnetite, and CNT volume concentrations as well as magnetic field strength are investigated. The acquired data for the case of without magnetic field confirmed higher values of heat transfer and pressure drop as a result of utilizing nanofluid compared with water. Additionally, it was found that the Nusselt number and pressure drop of the studied nanofluid samples increase significantly under the magnetic field. Moreover, the influence of magnetic field increases with an increase in the nanoparticle concentrations and magnetic field strength and decrease in the Reynolds number. The maximum increments of 109.31% and 25.02% in comparison with the case of without field were obtained in the average Nusselt number and pressure drop for hybrid nanofluid containing 0.9% magnetite and 1.35% CNT at Reynolds number of 500. [ABSTRACT FROM AUTHOR]

This article studies buoyancy-driven natural convection of a nanofluid affected by a magnetic field within a square enclosure with an individual conductive pin fin. The effects of electromagnetic forces, thermal conductivity, and inclination angle of pin fin were investigated using non-dimensional parameters. An extensive sensitivity analysis was conducted seeking an optimal heat transfer setting. The novelty of this work lies in including different contributing factors in heat transfer analysis, rigorous analysis of design parameters, and comprehensive mathematical analysis of solution domain for optimization. Results showed that magnetic strength diminished the heat transfer efficacy, while higher relative thermal conductivity of pin fin improved it. Based on the problem settings, we also obtained the relative conductivity value in which the heat transfer is optimal. Higher sensitivity of heat transfer was, though, noticed for both magnetic strength and fin thermal conductivity in comparison to fin inclination angle. Further studies, specifically with realistic geometrical configurations and heat transfer settings, are urged to translate current findings to industrial applications. [ABSTRACT FROM AUTHOR]

This paper assesses the contribution of TiO2 nanoparticles on thermal performance of a 0.5 mass% aqueous solution of carboxymethyl cellulose (CMC) in a square channel. In this regard, a neural network model is firstly developed for modeling of power law index, consistency index, and thermal conductivity of the aqueous solution of TiO2/CMC-water non-Newtonian nanofluid in terms of the nanoparticle concentration and temperature. Then, an attempt is made to evaluate the friction factor and heat transfer coefficient relative values. According to the results, it is found that the friction factor ratio is directly proportional to the temperature and nanoparticle content, while it inversely varies relative to the shear rate. Moreover, heat transfer coefficient ratio is improved at elevated nanoparticle content, and this improvement is much more profound at higher temperature conditions. For practical purposes, the nanofluid hydrothermal performance index is examined since the addition of nanoparticles increases both heat transfer and friction factor. The corresponding data disclose that the performance index is directly proportional to the nanoparticle content, especially at decreased shear rate and elevated temperature conditions. The application of TiO2/CMC-water nanofluid is found to be more favorable for applications with elevated shear rate conditions. [ABSTRACT FROM AUTHOR]

The present work deals with numerical investigations on heat transfer characteristics and friction factor of aqueous CuO nanofluids flow in a set of four microchannels connected in parallel under laminar regime. For each single phase, volume of fluid, mixture and Eulerian models, a particular computer code is developed to carefully simulate this problem. The three-dimensional steady-state governing equations are solved through finite volume method. The primary aim of this study is to comparatively distinguish the most appropriate and accurate model for numerical studies of nanofluids in microchannels. The results are compared with one another and the data obtained from an experimental work. Regarding the results, an acceptable consistency is observed for all models with the experimental data. The current study truly demonstrates that applying single-phase model to simulate and evaluate the laminar flow of CuO-water nanofluid inside microchannels with uniform wall temperature is more modest, precise and reliable compared with two-phase models. [ABSTRACT FROM AUTHOR]

The present study deals with the entropy generation analysis of a flat-plate solar collector using SiO/ethylene glycol-water nanofluids. For this purpose, available experimental data on the performance of a flat-plate solar collector are exploited for estimating the entropy generation in the system. Ethylene glycol-water (EG-water) and EG-water-based nanofluids having three different nanoparticle volume fractions including 0.5, 0.75, and 1 % are considered as the working fluids. The results are presented in terms of exergy efficiency, entropy generation parameter, and Bejan number for three different mass flow rates and various solar radiation intensities. It is found that when nanofluid concentration increases from 0 to 1 %, exergy efficiency enhances up to 62.7 % for a mass flow rate of 1 L min, whereas the corresponding increases in mass flow rates of 1.75 and 2.5 L min are 45.2 and 39.7 %, respectively. The results also elucidate that entropy generation parameter, which is a function of entropy generation, ambient temperature, and solar radiation, reduces with increasing the nanofluid concentration. [ABSTRACT FROM AUTHOR]

In the present study, the effect of volume concentration (0.05, 0.1 and 0.15 %) and temperature (10-90 °C) on viscosity and surface tension of graphene-water nanofluid has been experimentally measured. The sodium dodecyl benzene sulfonate is used as the surfactant for stable suspension of graphene. The results showed that the viscosity of graphene-water nanofluid increases with an increase in the volume concentration of nanoparticles and decreases with an increase in temperature. An average enhancement of 47.12 % in viscosity has been noted for 0.15 % volume concentration of graphene at 50 °C. The enhancement of the viscosity of the nanofluid at higher volume concentration is due to the higher shear rate. In contrast, the surface tension of the graphene-water nanofluid decreases with an increase in both volume concentration and temperature. A decrement of 18.7 % in surface tension has been noted for the same volume concentration and temperature. The surface tension reduction in nanofluid at higher volume concentrations is due to the adsorption of nanoparticles at the liquid-gas interface because of hydrophobic nature of graphene; and at higher temperatures, is due to the weakening of molecular attractions between fluid molecules and nanoparticles. The viscosity and surface tension showed stronger dependency on volume concentration than temperature. Based on the calculated effectiveness of graphene-water nanofluids, it is suggested that the graphene-water nanofluid is preferable as the better coolant for the real-time heat transfer applications. [ABSTRACT FROM AUTHOR]

The addition of nanoparticles to a base fluid is one of the significant issues to enhance heat transfer. In this study, different nanofluids were developed by mixing a water base fluid with magnetic nanoparticles. Thermophysical properties such as thermal conductivity and viscosity of the obtained nanofluid were investigated. The effect of different nominal diameters of nanoparticles and concentrations of nanoparticles on the thermal conductivity and viscosity of nanofluids have been examined. Three different diameters of magnetic nanoparticles (about 37 nm, 71 nm, and 98 nm) have been tested in this experimental investigation. Experimental results indicate that thermal conductivity increases as volume fraction increases, and thermal conductivity of the nanofluid increases with a decrease of nanoparticle's size. Moreover, the nanofluid dynamics viscosity ratio increases with an increase in particle concentration and nanoparticle's diameter. This paper identifies several important issues that should be considered in future work. [ABSTRACT FROM AUTHOR]

The application of nanofluids in energy systems is developing day by day. Before using a nanofluid in an energy system, it is necessary to measure the properties of nanofluids. In this paper, first the results of experiments on the thermal conductivity of MgO/ethylene glycol (EG) nanofluids in a temperature range of 25-55 °C and volume concentrations up to 5 % are presented. Different sizes of MgO nanoparticles are selected to disperse in EG, including 20, 40, 50, and 60 nm. Based on the results, an empirical correlation is presented as a function of temperature, volume fraction, and nanoparticle size. Next, the model of thermal conductivity enhancement in terms of volume fraction, particle size, and temperature was developed via neural network based on the measured data. It is observed that neural network can be used as a powerful tool to predict the thermal conductivity of nanofluids. [ABSTRACT FROM AUTHOR]

A considerable number of studies can be found on the thermal conductivity of nanofluids in which AlO nanoparticles are used as additives. In the present study, the aim is to measure the thermal conductivity of very narrow AlO nanoparticles with the size of 5 nm suspended in water. The thermal conductivity of nanofluids with concentrations up to 5 % is measured in a temperature range between 26 and 55 °C. Using the experimental data, a correlation is presented as a function of the temperature and volume fraction of nanoparticles. Finally, a sensitivity analysis is performed to assess the sensitivity of thermal conductivity of nanofluids to increase the particle loading at different temperatures. The sensitivity analysis reveals that at a given concentration, the sensitivity of thermal conductivity to particle loading increases when the temperature increases. [ABSTRACT FROM AUTHOR]