Thermal conductivity modeling of MgO/EG nanofluids using experimental data and artificial neural network

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.     

Microwave synthesis of silver nanofluids with polyvinylpyrrolidone (PVP) and their transport properties

Microwave synthesis has been applied to prepare stable silver nanofluids in ethanol by reduction of AgNO₃ with polyvinylpyrrolidone (PVP), used as stabilizing agent, having Ag concentrations of 1% by volume. The nanofluids were characterized by UV-vis spectroscopy, Fourier transform infrared, energy-dispersive X-ray spectroscopy, and transmission electron microscopy and systematically investigated for refractive index, electrical and thermal conductivity, and viscosity for different polymer concentrations. The size of nanoparticles was found to be in the range of 30–60 nm for two different salt-to-PVP ratios. For higher concentration of polymer in nanofluid, nanoparticles were 30 nm in size showing increase in thermal conductivity but a decrease in viscosity and refractive index, which is due to the polymer structure around nanoparticles. Thermal conductivity measurements of nanofluids show substantial increment in the thermal conductivity of nanofluid relative to the base fluid and nonlinear enhancement over the 283–323 K temperature range. Rheology of nanofluids was studied at room temperature showing effect of polymer on viscosity and confirming the Newtonian behavior of nanofluid.     

Estimation of thermal conductivity of ethylene glycol-based nanofluid with hybrid suspensions of SWCNT–Al<Subscript>2</Subscript>O<Subscript>3</Subscript> nanoparticles by correlation and ANN methods using experimental data

In the present paper, the effects of temperature and volume fraction on thermal conductivity of SWCNT–Al₂O₃/EG hybrid nanofluid are investigated. Single-walled carbon nanotube with outer diameter of 1–2 nm and aluminum oxide nanoparticles with mean diameter of 20 nm with the ratio of 30 and 70%, respectively, were dispersed in the base fluid. The measurements were conducted on samples with volume fractions of 0.04, 0.08, 0.15, 0.3, 0.5, 0.8, 1.5 and 2.5. In order to investigate the effects of temperature on thermal conductivity of the nanofluid, this characteristic was measured in five different temperatures of 30, 35, 40, 45 and 50 °C. The results indicate that enhancement of nanoparticles’ thickness in low volume fractions and at any temperature causes a considerable increment in thermal conductivity of the nanofluid. In this study, the highest enhancement of thermal conductivity was 41.2% which was achieved at the temperature of 50 °C and volume fraction of 2.5%. Based on the experimental data, an experimental correlation and a neural network are presented and for thermal conductivity of the nanofluid in terms of volume fraction and temperature. Comparing outputs of the experimental correlation and the designed artificial neural network with experimental data, the maximum error values for the experimental correlation and the artificial neural network were, respectively, 2.6 and 1.94% which indicate the excellent accuracy of both methods in prediction of thermal conductivity.     

Synthesis of metal-based nanofluids and their thermo-hydraulic performance in compact heat exchanger with multi-louvered fins working under laminar conditions

Present experimental investigation incorporates characterization of Al nanopowder, synthesis of Al/water nanofluids, and effect of these nanofluids on thermal performance of compact heat exchanger. Al nanoparticles are characterized using TEM and XRD. Al/water nanofluid is prepared by dispersing metal basis aluminium nanoparticles of average 100 nm size into double distilled water at two different particle volume concentrations of 0.1 and 0.2%. The nanofluids are prepared by two-step method and cetyl trimethyl ammonium bromide surfactant is used to stabilize the nanofluid. Thermo-physical properties of nanofluids at two different concentrations and their variation with fluid temperature are measured experimentally. It is examined that thermal conductivity, viscosity, and density of the nanofluid increased with the increase of volume concentrations. Furthermore, by increasing the fluid temperature, thermal conductivity is intensified, while the viscosity and density are decreased. Heat transfer parameters are strong functions of these thermo-physical properties. Therefore, comprehensive findings on heat transfer coefficient, Nusselt number, colburn factor, friction factor, and effectiveness are determined experimentally for prepared nanofluids passing under laminar conditions through single-pass cross-flow compact heat exchanger attached with multi-louvered fins.

     

Synthesis and thermo-physical properties of water-based novel Ag/ZnO hybrid nanofluids

The comparative study on the thermo-physical properties of water-based ZnO nanofluids and Ag/ZnO hybrid nanofluids is reported in the present study. The outer surface of ZnO nanoparticles was modified with a thin coating of Ag nanoparticles by a wet chemical method for improved stability and heat transfer properties. The ZnO and Ag/ZnO nanofluids were prepared with varying volume concentration (??=?0.02–0.1%). The synthesized nanoparticles and nanofluids were characterized with different characterization methods viz., scanning electron microscopy, X-ray diffraction, dynamic light scattering, thermal conductivity measurement, and viscosity measurement. Results show that thermal conductivity of Ag/ZnO hybrid nanofluids is found to be significantly higher compared to ZnO nanofluids. The maximum thermal conductivity an enhancement for Ag/ZnO nanofluid (??=?0.1%) is found to 20% and 28% when it compared with ZnO nanofluid (??=?0.1%) and water, respectively.     

Diminishing vortex intensity and improving heat transfer by applying magnetic field on an injectable slip microchannel containing FMWNT/water nanofluid

In this study, heat transfer and entropy generation were investigated in a microchannel containing FMWNT/water nanofluids given the slip condition. The main focus was on utilizing injection technique in the presence of the magnetic field. The injection from the upper high-temperature wall was incorporated into the flow field. Injection at high Reynolds number causes vortex formation, which ultimately reduces local heat transfer in the adjacent injection zone. By applying the magnetic field, the vortex intensity as well as boundary layer thickness was diminished which in turn improved the heat transfer. Based on numerical results, at higher nanoparticle volume fraction, the effect of the magnetic field on heat transfer enhancement was amplified. Moreover, at higher Reynolds numbers, the magnetic field efficacy is more obvious. The highest heat transfer occurred at the highest values of the Hartmann and Reynolds numbers and eventually the nanoparticle volume fraction. Owing to applying the magnetic field on the injectable microchannel containing nanofluid, heat transfer improvement can reach up to 79%. From the second law prospective, the entropy generation intensified by 82.8%.

     

Green synthesis,crystal growth,and some physicochemical studies on an inter-molecular compound of anthranilic acid and <Emphasis Type="Italic">m</Emphasis>-nitro-benzoic acid system

Nanofluids are prepared by suspending the nanoparticles in the base fluid and can be substantially enhanced the heat transfer rate compared to the pure fluids. In this paper, experimental investigation of the effects of volume concentration and temperature on dynamic viscosity of the hybrid nanofluid of multi-walled carbon nanotubes and aluminum oxide in a mixture of water (80%) and ethylene-glycol (20%) has been presented. The nanofluid was prepared with solid volume fractions between 0.0625 and 1%, and experiments were performed in the temperature range of 25–50 °C. The measurement results at different shear rates showed that the base fluid and nanofluid samples with solid volume fractions of less than 0.5% had Newtonian behavior, while those with higher solid volume fractions (0.75 and 1%) exhibit a pseudoplastic rheological behavior with a power law index of less than unity. The results showed that viscosity has a direct relationship with solid volume fraction of the nanofluid. The value of maximum enhancement is which occurred in 25 °C. Moreover, the consistency index and power law index have been obtained by accurate curve fitting for samples with non-Newtonian behavior of nanofluids. The results also revealed that the apparent viscosity generally increases with an increase in the solid volume fraction.     

Forced convection magnetohydrodynamic Al2O3–Cu/water hybrid nanofluid flow over a backward-facing step

Forced convection hybrid nanofluid flow over a backward-facing step under a non-uniform magnetic field is numerically studied using a finite volume method. The external magnetic source is placed in the step edge. The study is performed for a range of nanoparticles volume fraction, φ, from 0 to 2%, Hartmann number, Ha, from 0 to 50, and Reynolds number, Re, from 100 to 300. Results show that the reattachment length reduces by increasing volume fraction of nanoparticles and by decreasing Reynolds number. The recirculation bubble weakens and the conductive heat transfer mode growth by increasing Hartmann number at weak magnetic field intensity. It totally disappears at high Hartmann number when the convective mode dominates. The average Nusselt number increases by increasing volume fraction of nanoparticles and varies with the Hartmann number. The effects of Lorentz force and hybrid nanoparticles on the heat transfer enhancement rates are strongly linked with volume fraction of nanoparticles and Hartmann and Reynolds numbers.

     

The noble effect of aging on the thermal conductivity of modified CNTs-ethylene glycol nanofluids

In order to improve the heat transfer process by using nanofluids, different nanoparticles and base fluids have been studied. In this work, stability and effect of aging and temperature on the thermal conductivity of CNTs-ethylene glycol (EG) nanofluids were investigated. Chemical functionalisation was used to oxidise the surface of CNTs. The functionalised CNTs were used to prepare the nanofluids by a two-step method. The stability of nanofluids was measured by UV-vis spectroscopy and the results showed that the nanofluids had a good stability over several days. Immediately after nanofluid preparation not too much increase was observed for thermal conductivity but the nanofluid aging had a great influence on the improvement of the thermal conductivity, as after 65 days, about 50% increase was observed. The increase has been attributed to forming an ordered nanolayer of EG molecules around the CNTs. Also no significant temperature dependence of thermal conductivity was observed up to 50°C possibly due to the lack of temperature dependence of CNTs Brownian motions.     

ANSYS simulation study of a low volume fraction CuO–ZnO/water hybrid nanofluid in a shell and tube heat exchanger

For the first time, the heat transfer performance of a CuO–ZnO (80:20)/water hybrid has been studied experimentally and numerically in a shell and tube heat exchanger under turbulent flow conditions nanofluid (STHE). All experiments are carried out with 0.01 ​vol% CuO–ZnO (80:20)/water hybrid nanofluid at Reynolds numbers (N_Re) ranging from 1900 to 17,500. The stabilized hybrid nanofluids (30 ​°C-Tube side) are then used as a coolant to reduce the hot fluid (60 ​°C-shell side) temperature using a STHE, with the results for the convective heat transfer coefficient, Nusselt number, friction factor, and pressure drop reported. The primary goal of this paper is to investigate the impact of hybrid nanoparticle mixing ratio optimization on STHE heat transfer efficiency under various operating conditions. According to the findings, the CuO–ZnO (80:20)/water hybrid nanofluid improved the heat transfer performance of the STHE at all Reynolds numbers. When using nanofluid over water, the Nusselt number and pressure drop were improved by approximately 33% and 13%, respectively. The hybrid nanofluid's maximum thermal performance factor and thermal efficiency enhancement were 1.45 and 7%, respectively, at N_Re ​= ​17,500. According to the study, the thermal conductivity of nanofluid varies by only 5% after ten trials. Furthermore, the ANSYS Fluent program was used to predict the behavior of the hybrid nanofluid in STHE, and the simulation results fit the experimental values very well.     

A new semi-analytical model for effective thermal conductivity of nanofluids

A new theoretical model for thermal conductivity of nanofluids is developed incorporating effective medium theory, interfacial layer, particle aggregation and Brownian motion-induced convection from multiple nanoparticles/aggregates. The predicated result using aggregate size, which represents the particle size in the actual condition of nanofluids, fits well with the experimental data for water-, R113- and ethylene glycol (EG)-based nanofluids. The present model also gives much better predictions compared to the existing models. A parametric analysis, particularly particle aggregation, is conducted to investigate the dependence of effective thermal conductivity of nanofluids on the properties of nanoparticles and fluid. Aggregation is the main factor responsible for thermal conductivity enhancement. The dynamic contribution of Brownian motion on thermal conductivity enhancement is surpassed by that of static mechanisms, particularly at high volume fraction. Predication also indicated that the viscosity increases faster than the thermal conductivity, causing the highly aggregated nanofluids to become unfavourable, especially for d_f = 1.8.     

Combination of RSM and NSGA-II algorithm for optimization and prediction of thermal conductivity and viscosity of bioglycol/water mixture containing SiO2 nanoparticles

The fluids containing nanoparticles have enhanced thermo-physical characteristics in comparison with conventional fluids without nanoparticles. Thermal conductivity and viscosity are thermo-physical properties that strongly determine heat transfer and momentum. In this study, the response surface method was firstly used to derive an equation for the thermal conductivity and another one for the viscosity of bioglycol/water mixture (20:80) containing silicon dioxide nanoparticles as a function of temperature as well as the volume fraction of silicon dioxide. Then, NSGA-II algorithm was used for the optimization and maximizing thermal conductivity and minimizing the nanofluid viscosity. Different fronts were implemented and 20th iteration number was selected as Pareto front. The highest thermal conductivity (0.576 W/m.K) and the lowest viscosity (0.61 mPa.s) were obtained at temperature on volume concentration of (80 °C and 2%) and (80 °C without nanoparticle) respectively. It was concluded that the optimum thermal conductivity and viscosity of nanofluid could be obtained at maximum temperature (80 °C) or a temperature close to this temperature. An increase in the volume fraction of silicon dioxide led to the enhancement of thermal conductivity but the solution viscosity was also increased. Therefore, the optimum point should be selected based on the system requirement.     

Nitrogen-doped carbon nanotubes for heat transfer applications

In this research, it is aimed to enhance the heat transfer properties of the carbon nanotubes through nitrogen doping. To this end, nitrogen-doped multiwall carbon nanotubes (N-CNTs) were synthesized via chemical vapor deposition method. For supplying carbon and nitrogen during the synthesis of N-CNTs, camphor and urea were used, respectively, at 1000 °C over Co–Mo/MgO nanocatalyst in a hydrogen atmosphere. N-CNTs with three different nitrogen loadings of 0.56, 0.98, and 1.38 mass% were synthesized, after which, water/N-CNT nanofluids of these three samples with concentrations of 0.1, 0.2, and 0.5 mass% were prepared. To obtain a stable nanofluid, N-CNTs were functionalized by nitric acid followed by stabilizing in water by employing the ultrasonic bath. Investigation on the stability of the samples showed a high stability level for the prepared water/N-CNT nanofluids in which the zeta potential of ??43.5 mV was obtained for the best sample. Also for studying the heat transfer properties, the thermal conductivity in the range of 0.1–0.5 mass% and convection heat transfer coefficients of nanofluids in the range of 0.1–0.5 mass%, and Reynolds number in the range of 4000–9000 were evaluated. The results showed 32.7% enhancement of the convection heat transfer coefficients at Reynolds number of 8676 and 27% increase in the thermal conductivity at 0.5 mass% and 30 °C.

     

Pressure Drop and Performance Characteristics of Water-Based Al2O3 and CuO Nanofluids in a Triangular Duct

An experimental study is performed to determine the pressure drop and performance characteristics of Al₂O₃/water and CuO/water nanofluids in a triangular duct under constant heat flux where the flow is laminar. The effects of adding nanoparticles to the base fluid on the pressure drop and friction factor are investigated at different Reynolds numbers. The results show that at a specified Reynolds number, using the nanofluids can lead to an increase in the pressure drop by 35%. It is also found that with increases in the Reynolds number, the rate of increase in the friction factor with the volume fraction of nanoparticles is reduced. Finally, the performance characteristics of the two nanofluids are investigated using the data of pressure drop and convective heat transfer coefficient. The results show that the use of Al₂O₃/water nanofluid with volume fractions of 1.5% and 2% is not helpful in the triangular duct. It is also concluded that at the same volume fraction of nanoparticles, using Al₂O₃ nanoparticles is more beneficial than CuO nanoparticles based on the performance index.     

Effect of volume concentration and temperature on viscosity and surface tension of graphene–water nanofluid for heat transfer applications

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.     

Viscosity and thermal conductivity of MgO–EG nanofluids

Nanofluids are a group of novel engineering materials that are increasingly being used, particularly in the processes of heat exchange. One of the most promising materials in this group is magnesium oxide–ethylene glycol (MgO–EG) nanofluid. The literature informs that this material is characterized by an significant increase in thermal conductivity with low dynamic viscosity increase. The aim of this paper is to provide experimental data on the dynamic viscosity and thermal conductivity of nanofluids containing MgO nanoparticles with 20 nm average size and ethylene glycol as base fluid. To determine dynamic viscosity and thermal conductivity of samples, a HAAKE MARS 2 rheometer (Thermo Electron Corporation, Karlsruhe, Germany) and KD2 Pro Thermal Properties Analyzer (Decagon Devices Inc., Pullman, Washington, USA) were used. Additionally, a comparison of the experimental results and the predictions of theoretical models was presented. It was presented that the vast majority of theoretical models does not describe in a correct way both viscosity and thermal conductivity. It was also shown that the enhancement of this basic physical properties might be described with good result with second degree polynomials. Finally, evaluation of the heat transfer performance was presented.     

A model of nanofluids effective thermal conductivity based on dimensionless groups

Thermal conductivity is an important parameter in the field of nanofluid heat transfer. This article presents a novel model for the prediction of the effective thermal conductivity of nanofluids based on dimensionless groups. The model expresses the thermal conductivity of a nanofluid as a function of the thermal conductivity of the solid and liquid, their volume fractions, particle size and interfacial shell properties. According to this model, thermal conductivity changes nonlinearly with nanoparticle loading. The results are in good agreement with the experimental data of alumina-water and alumina-ethylene glycol based nanofluids.     

Effect of the reaction temperature on the morphology of nanosized HAp

The main purpose of this study is numerically investigating the flow and heat transfer of nanofluid flow inside a microchannel with L-shaped porous ribs as well as studying the effect of porous media properties on the performance evaluation criterion (PEC) of the fluid. In the present paper, in addition to the pure water fluid, the effect of using water/CuO nanofluid on the PEC of microchannel was investigated. The flow was simulated in four Reynolds numbers and two different volume fractions of nanoparticles in laminar flow regime. The investigated parameters are the thermal conductivity and the porosity rate of porous medium. The results indicate that with the existence of porous ribs, the nanofluid does not have a significant effect on heat transfer increase. By using porous ribs in flow with Reynolds number of 1200, the heat transfer rate increases up to 42% and in flow with Reynolds number of 100, this rate increases by 25%.

     

Thermal conductivity of Al2O3/water nanofluids

A considerable number of studies can be found on the thermal conductivity of nanofluids in which Al₂O₃ nanoparticles are used as additives. In the present study, the aim is to measure the thermal conductivity of very narrow Al₂O₃ 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.     

Thermal performance improvement in water nanofluid/GNP–SDBS in novel design of double-layer microchannel heat sink with sinusoidal cavities and rectangular ribs

In this numerical study, laminar flow of water nanofluid/GNP–SDBS (graphene nanoplatelet–sodium dodecylbenzene sulfonate) for 0–0.1% solid nanoparticles mass fraction was investigated for Reynolds numbers of 50–1000 in 3D space via finite volume method. In the newly proposed microchannel design, the cooling fluid is moving in countercurrent in the upper and lower layers of the microchannels, and there are cavities and sinusoidal routes on the solid walls of the microchannel, and the presence of rectangular ribs on the flow centerline along the fluid path enhances mixing for cooling fluid and creates better heat transfer for warm surfaces. The results of this study show that this special design of the microchannel can have a substantial increase in Nusselt number and heat transfer so that in the considered geometry by adding solid nanoparticles mass fraction it is possible to increase average Nusselt number for each Reynolds number by approximately 20%. Also, the mixing of the fluid because of formation of secondary flows has a strong effect on making the temperature distribution uniform in the cooling fluid and solid bed (wall) of the microchannel, especially in the lower layer. The upper layer of the microchannel always has a lower temperature due to indirect contact with heat flux compared with the lower layer. In this study, by increasing Reynolds number and mass fraction of solid nanoparticles the Nusselt number is increased and heat resistance of the lower wall of the microchannel is reduced. Based on the investigation of flow field and heat transfer, the use of the proposed design of the microchannel is recommended for Reynolds number less than 300.