Glycol-water Mixture Research Articles

Effect of particle concentration and temperature on the thermo-physical properties of ethylene glycol–water mixture based boron nitride nanofluids

Present article focusses on the thermal and rheological characteristics of ethylene glycol–water mixture (volume = 60/40) based boron nitride (h-BN) nanofluids measured at different volume concentrations (0.5–2 vol% h-BN) between temperatures 30–60 °C. X-ray diffraction and TEM analysis have confirmed the hexagonal structure of h-BN nanoparticles and the size range of the nanoparticles is within 90–170 nm. To optimize the ultrasonication time, the thermal conductivity of h-BN nanofluids has been monitored after each 30 min of sonication until a maximum thermal conductivity increase is achieved. The thermal conductivity of h-BN nanofluids shows an increasing trend with respect to particle concentration. Also, the thermal conductivity enhancement exhibits a temperature independent nature. The viscosity studies carried out over a shear rate of 0.612–122 s−1 revealed an increasing trend with the increasing concentration of h-BN loading. For all the volume concentrations, at lower shear rates, the viscosity initially decreased, displaying a non-Newtonian nature, and with a further increase in shear rate, the viscosity stays constant exhibiting a Newtonian nature. Based on the experimental outcomes, a correlation is introduced. The correlation showed a strong agreement with the current results, with an R2 value of 0.99.

The effect of ethylene glycol concentration on the interfacial dynamics of the successive droplets impacting onto a horizontal hot solid surface

The present work aimed to conduct the visualization study on the effect of the ethylene glycol concentration on the interfacial behavior of successive droplets during the impacting onto a horizontal hot solid surface. The tested liquid droplets were pure water and two ethylene glycol-water mixtures, which contain 10% and 20% of ethylene glycol. A polished cylindrical plate of stainless steel (SUS 304), with the surface roughness of 0.06 μm, was utilized as a solid surface. The surface varies for temperatures of about 110 °C–240 °C. The detailed phenomena during the droplet impact were recorded by using a high-speed video camera with the frame speed of 2000 fps and the resolution of the 1024 × 768. In addition, an own developed image processing technique was also implemented to obtain the quantitative parameters, such as the spreading ratio and the apex height during the droplet impacting onto a hot solid surface. As a result, the interfacial dynamics of the successive droplets were clarified. The addition of the concentration of ethylene glycol leads to the decrease of droplet oscillation during the spreading phase and delays both the bubble formation and the presence of secondary droplets. In addition, the research also reveals that the presence of the second droplet successfully improves the wetting area of the droplet.

Rate and equilibrium based modeling with the sequential quadratic programming optimization method for glycol dehydration of produced natural gas

Determining the optimum temperature and pressure for the dehydration of natural gas in a glycol absorption unit and the recovery of the glycol from the glycol water mixture in a desorption unit is of great importance. Although, the equilibrium base model for the absorption column design had been in use, the rate based model for the absorption unit offers a promising technique and had been proven to be more accurate in determining the parameters for the design. In this study, dehydration of a natural gas plant was modelled with optimization of its parameters. The effects on cost were adequately studied. Sensitivity analysis resulting from the simulation showed that a lower temperature for effective absorption of the water from the gas stream by triethylene glycol (TEGlycol) solvent is expected, while a higher temperature and higher reboiler duty is required for the regeneration of the solvent from the Rich TEGlycol stream in a distillation column. The sequential quadratic programming (SQP) direct optimization method was employed to optimize the major parameters of the natural gas dehydration plant. The optimum temperature of 267 °F and Reboiler duty of 169,789 Btu/h gave a 0.99 TEGlycol recovery purity. A minimized capital cost of 3.73 million US Dollars and operating cost of approximately 1 million US dollars was also observed.

Modeling and experimental validation and thermal performance assessment of a sun-tracked and cooled PVT system under low solar irradiation

The PV panels cooling allows one to increase the photovoltaic conversion efficiency, as well as to obtain the waste heat, which can be utilized for various purposes. This paper presents the model of the radiator used for photovoltaic (PV) panels cooling. The cooling liquid is a water-glycol mixture, the PV panel electrical power output is 280 W. The radiator consists of a various number of segments (U-tube), that are located at the PV panel width. The three-dimensional control volume method formulation is used to calculate the temperature distribution within the PV panel surface (glass, silica layer, protective foil), and aluminum radiator. The one-dimensional energy equation is used to calculate the cooling liquid outlet temperature. The effect of an increasing number of radiator segments and the mass flow rate is studied to optimize the heat transfer performance and decrease the manufacturing costs. The simulations are conducted for various conditions, including the cloudy and sunny days. The simulation results are compared with experimental data collected at a stand installed at the laboratory of the Department of Energy at the Cracow University of Technology. The measurement results and the numerical simulation shows quite good agreement. For the studied case, it is shown that lowering the temperature of the panels increases the gross efficiency of the entire system. Moreover, the waste heat obtained from the PV cooling may be utilized as low-temperature heat for domestic hot water preheating or heat pump system applications.

Investigation on the heat transfer characteristics of propylene glycol–water mixture in the shell side of a spiral‐wound heat exchanger

AbstractThe heat transfer characteristics of propylene glycol–water (PG–W) mixture (10%, 20%, and 30% propylene glycol) on the shell side of a spiral‐wound heat exchanger (SWHE) were investigated experimentally. Among the SWHE selected, there are 18 twined tubes with a diameter of 8 mm. PG–W mixture is on the shell side and water is on the tube side. The results show that the heat transfer coefficient of PG–W mixture flowing downwards is higher than upwards under countercurrent conditions. The heat transfer coefficient decreases with the increasing of concentration of PG–W mixture. When the inclination angle of the SWHE is 90°, the heat transfer coefficient of PG–W mixture is the largest; and when the inclination angle is less than 90°, the heat transfer coefficient decreases with the decrease of inclination angle. The inclination angle has a great effect on the heat transfer coefficient at a high concentration. The fitting correlation equations between Nu, Re, Pr, and inclination angles of SWHE are established.

The effect of geometrical modifications to a shell and tube heat exchanger on performance and freezing risk during LNG regasification

The regasification of LNG is a crucial process in a majority of LNG applications and can be conducted in various types of heat exchangers. The low boiling temperature of LNG makes the vaporization process prone to the risk of ice formation, which can obstruct the flow of the heating fluid. This, in turn, can lead to a significant drop in pressure, decrease in heat transfer or even to the destruction of the heat exchanger itself. In a wide range of important applications, the heating fluid is often water or a water-glycol mixture, characterized by a freezing temperature that is substantially higher than the boiling temperature of LNG. Consequently, this can intensify the ice formation process. In the current research, a numerical model was proposed and developed to analyze the risk of ice formation during the LNG vaporization process within a shell-and-tube type of heat exchanger (STHX). The model consists of two distinct parts: heat transfer through the boiling LNG and the freezing dynamics of the heating fluid. To generalize the developed model for various boiling regimes a continuous and differentiable expression of the boiling curve of LNG was proposed. The expression smoothly connected the nucleate with the film boiling regions and methodically filled the gap of the transition region. The developed numerical model was used to investigate a wide range of flow conditions and various shapes and spacing of tubes within the STHX. It was shown that the risk of total freezing could be indicated by a critical value of the Reynolds number. The conducted study made it possible to define a heat-flux-to-pump-duty-ratio coefficient, which showed that flattened tubes could ensure better heat transfer, higher reliability and also decrease the pump duty needed to supply the STHX.

Characterization of thermal and electrical properties of hybrid nanofluids prepared with multi-walled carbon nanotubes and Fe2O3 nanoparticles

The thermal and electrical features of fluids are the most important parameters for designing suitable nanofluids to be used as coolants in automotive systems, transportation, power plants, industrial facilities, as well as oil, gas, petrochemical and electronic industries. This research aims at the thermal, electrical and physical properties of hybrid nanofluids that consist of multi-walled carbon nanotube (MWCNT) and Fe2O3 nanoparticles in ethylene glycol/water as base fluid. The conditions for nanofluid preparation were optimized through the response surface methodology. EG, MWCNT, Fe2O3 nanoparticles proportion and solution pH were chosen as parameters of effect on Thermal conductivity. The experimental data point out that Thermal conductivity would increase proportional to increase the amount of nanoparticle, but it would decrease in alkaline environments. Also, highest electrical conductivity (545 [μS/cm]) was observed at 0.69 [%w.v] of MWCNT and 1.67 [% w.v] of Fe2O3 nanoparticles dispersed in a 44:56 ethylene glycol-water mixture, as compared to other base fluids. The synergetic effect of both nanoparticles added to the base fluid on the thermos-electrical property was confirmed by the measurement of thermal and electrical conductivities and electrochemical impedance spectroscopy (EIS).

Shear flow behavior and dynamic viscosity of few-layer graphene nanofluids based on propylene glycol-water mixture

We report the shear flow behavior of few layer graphene (FLG) based nanofluids produced with a commercial mixture of water and propylene glycol and three nonionic surfactants, Triton X-100, Pluronic® P123, and Gum Arabic respectively. The flow properties of these nanofluids were experimentally investigated between 283.15 and 323.15 K and for FLG content from 0.05 to 0.5 wt%. The nanofluids were subjected to different experiments, at rest at fixed temperature, under steady shear flow at fixed temperature and under temperature ramp at fixed shear rate in order to evaluate their stability and behavior under shear and temperature influence. These results were compared and correlated to visual aspect of the samples at the end of measurements. This experimental study evidences that the temperature, the shearing and the shearing duration have an important influence on the stability under shear of nanofluids in function of concentration and surfactant used. Finally, for all stable nanofluids under shear, the dynamic viscosity evolution of nanofluids with temperature is correlated to Vogel-Fulcher-Tammann model.

Experimental investigation of pressure drop and cooling performance of an automobile radiator using Al2O3-water + ethylene glycol nanofluid

In this study, the cooling capacity and the pressure drop variation in an automobile radiator using nanofluid instead of water with antifreeze that are investigated experimentally. The nanofluid consisted of 50% Ethylene Glycol–Water mixture including Al2O3 nanoparticles with 0.5% volumetric concentration was used as coolant. In all experiments, the inlet temperature of the cooling fluid into the radiator was held constant at 95 C. The tests were carried out at the air inlet temperature between 23.4–28.6 °C, the air velocity between 1.7–4.3 m/s, the cooling loads between 2.5–15 kW and the cooling fluid flow rates between 10 and 25 L/min. Results demonstrate that 50% Ethylene Glycol–Water based 0.5% vol. Al2O3 nanofluid increased the cooling capacity of the radiator up to 15% compared to the fluid with only 50% Ethylene Glycol–Water mixture. Instead of 15% increment, radiator can make with smaller surface area up to 15%, or the flow rate can be decreased for same heat transfer rate, so fluid pumping power consumption can be reduced in order to save fuel as much as pumping power economy. In addition, it has not been observed a remarkable increase in the pressure drop.

Design of an innovative PV/T and heat pump system for greenhouse heating

The very high annual heat demand of greenhouses is the most critical factor that increases production costs. Conventional methods are generally used to obtain the optimum temperature required for greenhouses. In these systems, greenhouse air is heated by a boiler and pipe networks are connected to it, and in this way, most of the heat energy is transferred from the greenhouse ceiling to the atmosphere. In addition, in the greenhouse, not only the air but also the soil should be heated in order not to spoil the roots of the plants. The objective of this research is to provide sustainable heating for greenhouse applications. For this purpose, an innovative heating system has been designed for greenhouse heating by using of solar energy and heat pump technologies. In this study, a new approach was presented by designing a novelty heat pump flow for the heat required in the greenhouse. With this design, not only greenhouse air but also the soil will be heated and the best conditions for the development of plants will be provided. In the system, an ethylene glycol water mixture was used to prevent damage caused by freezing. In addition, it is designed to provide sustainability with an auxiliary heater when solar radiation is insufficient. It is highly recommended to apply this presented system for all greenhouse types.

Effect analysis on energy efficiency enhancement of controlled cylinder liner temperatures in marine diesel engines with model based approach

In recent years, growing interest in engine efficiency, because of international regulations in the maritime sector, necessitates studies about new operational techniques. Ships have been operating at reduced speeds in recent years and, the liner temperatures of marine diesel engines vary significantly at reduced loads, which increase the heat loss from main engine. The research focuses on revealing the energy efficiency enhancement potential by decreasing heat loss through jacket water during reduced loads without any permanent modification. The heat loss reduction is achieved by means of higher coolant (glycol–water mixture) temperatures, to keep the liner temperatures at their maximum permissible temperatures. The methodology is calculating the energy balance and efficiency increment at reduced loads of main engine by modelling. The model have been validated with the digital twin of a two-stroke Sulzer-12RTA84C marine diesel engine. The simulated results comprise in-cylinder pressures, exhaust gas temperature and pressure, scavenge pressure, engine speed, turbo-charger, indicated power and heat transfer rate. Liner temperatures, affecting the heat transfer rate, are investigated in variable operating loads of the main engine. The study shows that keeping the liner temperature of the engine at the maximum continuous rating’s temperature, has respectable efficiency advantages under different operating loads. 0.5% reduction in fuel consumption could be achieved, coming with 127.8 tons fuel and 398 tons CO2 reduction in a year. Additionally, waste heat recovery system calculations were carried out and additional 48.8 tons of fuel could be saved in the generation of electricity. In total 176.6 tons of fuel and 550 tons of CO2 emission reduction could be achieved. As a result, the controlled cylinder wall temperatures can be considered as one of the methods to solve the efficiency and emission problems in ships in the near future.

Application of M5 tree regression, MARS, and artificial neural network methods to predict the Nusselt number and output temperature of CuO based nanofluid flows in a car radiator

In the current study, CuO nanoparticles were dispersed in a mixture of Ethylene Glycol-Water (60/40 wt. %) to prepare stable nanofluid in different concentrations (0.05 − 0.8 vol. %). The samples were used as the coolant fluid in a specific car radiator to evaluate the thermal performance of nanofluid and base fluid in the system. Five different and novel Machine-learning methods were applied over experimental data to predict the Nusselt number and output temperature of the coolant in the system. These methods are M5 tree regression, Linear and Cubic Multi-Variate Adaptive Regression Splines (MARS), Radial Basis Function (RBF), and Artificial Neural Network-Levenberg Marquardt Algorithm (ANN-LMA). Although all studied methods show acceptable accuracy in predicting experimental data, the ANN-LMA method in output temperature modeling and the MARS-Linear method in Nusselt number modeling has more precision.

Forced Convection of Al2O3–Cu, TiO2–SiO2, FWCNT–Fe3O4, and ND–Fe3O4 Hybrid Nanofluid in Porous Media

Adding nanoparticles to fluid has led to a new class of fluids named as nanofluids. Different concentrations and its effective cooling have attracted many engineering applications to test this new fluid. Lately, important heat enhancement has been observed by dispersing two distinct nanoparticles in the regular fluid. This type of hybrid nanofluid has led researchers to study its effectiveness in the cooling process. Here, we experimentally studied the forced convection of Al2O3–Cu hybrid nanofluid in porous media at a constant flow rate and heating condition. The numerical code after being calibrated with the experimental results is used to predict the effectiveness in cooling by using a set of hybrid fluid of TiO2–SiO2, MWCNT–Fe3O4, and ND–Fe3O4 at different concentrations. In the experiment, we used water and a water–ethylene glycol mixture as base fluids. The results revealed that the hybrid fluid contributed to heat enhancement levied increased pumping power. However, the index of efficiency, obtained by combining the Nusselt number and pressure drop, indicated that the best hybrid fluid for such an application is ND–Fe3O4 in the water–ethylene glycol mixture.

Applying different types of artificial neural network for modeling thermal conductivity of nanofluids containing silica particles

Nanofluids are widely applicable in thermal devices with porous structures. Silica nanoparticles have been dispersed in different heat transfer fluids in order to increase their thermal conductivity and heat transfer capability. In this study, group method of data handling (GMDH) and multilayer perceptron artificial neural networks are applied for determining thermal conductivity of nanofluids with silica particles and different base fluids such as ethylene glycol, glycerol, water and ethylene glycol–water mixture. For cases with multilayer perceptron models, trained by applying scaled conjugate gradient (SCG) and Levenberg–Marquardt (LM) have been tested as two different training algorithms. The outputs of the applied models have good agreement with the values obtained in experimental studies. The values of $${R}^{2}$$ in the optimum conditions of using GMDH, LM and SCG are 0.9997, 0.9991 and 0.9998, respectively. In addition, the MSE values of the mentioned methods are approximately 0.000010, 0.000032 and 0.0000078, respectively.

Thermal conductivity and structuring of multiwalled carbon nanotubes based nanofluids

Abstract the thermal conductivity of OH functionalized multiwalled carbon nanotube and its composites with Ag, Au and Pd in water, ethylene glycol and ethylene glycol-water (60:40 vol%) mixtures is studied using a combined experimental and theoretical approach. The experimental study was carried out in the 0.01 to 0.20 solid mass fraction range from 10 °C to 60 °C. The results show a large effect of the considered solvent on the thermal conductivity as well as increasing values with solid mass fraction and temperature. Artificial neural network (ANN) methods were successfully applied for the prediction of thermal conductivity of the considered nanofluids. The nanoscopic structuring of the studied nanofluids was analyzed by using molecular dynamics simulations, with particular attention to the nanotubes' solvation as well as the changes in the base fluids by the presence of the nanomaterials.

Analysis of freezing risk during LNG evaporation process

Liquid natural gas (LNG) boiling process concerns majority of LNG applications because of a need of its regasification. Depending on pressure an equilibrium temperature of LNG is 112-160K. The low boiling temperature of LNG makes the vaporisation process complicated. An important risk of the regasification is related to a possibility of a solid phase formation (freezing of a heating fluid). For a range of important applications the heating fluid is water or water-glycol mixture, characterized by freezing temperature considerably higher than the boiling temperature of LNG. The solid phase formation can lead to an increase of hydraulic pressures losses, deterioration of the heat transfer or even to the destruction of a heat exchanger and any accompanying device. It motivates a need for better understanding and control of a heat transfer related to the regasification to avoid the solid phase formation. The current work analyses a LNG regasification and a risk of solidification in a generalized shell and tube heat exchanger. The conducted study helped to define a critical Reynolds number below which the solidified ice totally blocks the flow.

The experimental investigation concerning the heat transfer enhancement via a four-point star swirl generator in the presence of water–ethylene glycol mixtures

In the present study, a new swirling flow generator is studied which aims to enhance the convective heat transfer rate in a heat exchanger tube. This device has a four-point star cross section. The study mainly investigates the effect of swirl generator on heat transfer rate and pressure drop along the test tube which is under a constant and uniform heat flux. The working fluid in the experiments is the water–ethylene glycol mixtures with Prandtl numbers ranging from 5 to 150 at different Reynolds numbers from 12,000 to 27,000. The results clarify the potential of the applied swirl generator to make a significant enhancement in the heat transfer rate with a satisfactory rise in the pressure drop. Based on studies of different cases, it is found that the swirl generator enhances the heat transfer and also the pressure drop up to 75% and 55%, respectively. The results show that the swirl generator is more efficient at lower Reynolds numbers. Moreover, the results lead to this finding that the swirl generator has a better performance for water and consequently for water–ethylene glycol mixtures with lower ethylene glycol percentage. In other words, the swirl generator has a better performance for the working fluids with a lower Prandtl number.

Hydrodynamic and thermal analysis of water, ethylene glycol and water-ethylene glycol as base fluids dispersed by aluminum oxide nano-sized solid particles

PurposeThe purpose of this paper is to carry out a hydrodynamic and thermal analysis of turbulent forced-convection flows of pure water, pure ethylene glycol and water-ethylene glycol mixture, as base fluids dispersed by Al2O3 nano-sized solid particles, through a constant temperature-surfaced rectangular cross-section channel with detached and attached obstacles, using a computational fluid dynamics (CFD) technique. Effects of various base fluids and different Al2O3 nano-sized solid particle solid volume fractions with Reynolds numbers ranging from 5,000 to 50,000 were analyzed. The contour plots of dynamic pressure, stream-function, velocity-magnitude, axial velocity, transverse velocity, turbulent intensity, turbulent kinetic energy, turbulent viscosity and temperature fields, the axial velocity profiles, the local and average Nusselt numbers, as well as the local and average coefficients of skin friction, were obtained and investigated numerically.Design/methodology/approachThe fluid flow and temperature fields were simulated using the Commercial CFD Software FLUENT. The same package included a preprocessor GAMBIT which was used to create the mesh needed for the solver. The RANS equations, along with the standard k-epsilon turbulence model and the energy equation were used to control the channel flow model. All the equations were discretized by the finite volume method using a two-dimensional formulation, using the semi-implicit method for pressure-linked equations pressure-velocity coupling algorithm. With regard to the flow characteristics, the interpolation QUICK scheme was applied, and a second-order upwind scheme was used for the pressure terms. The under-relaxation was changed between the values 0.3 and 1.0 to control the update of the computed variables at each iteration. Moreover, various grid systems were tested to analyze the effect of the grid size on the numerical solution. Then, the solutions are said to be converging when the normalized residuals are smaller than 10-12 and 10-9 for the energy equation and the other variables, respectively. The equations were iterated by the solver till it reached the needed residuals or when it stabilized at a fixed value.FindingsThe result analysis showed that the pure ethylene glycol with Al2O3 nanoparticles showed a significant heat transfer enhancement, in terms of local and average Nusselt numbers, compared with other pure or mixed fluid-based nanofluids, with low-pressure losses in terms of local and average skin friction coefficients.Originality/valueThe present research ended up at interesting results which constitute a valuable contribution to the improvement of the knowledge basis of professional work through research related to turbulent flow forced-convection within channels supplied with obstacles, and especially inside heat exchangers and solar flat plate collectors.

Prediction of the pressure drop for CuO/(Ethylene glycol-water) nanofluid flows in the car radiator by means of Artificial Neural Networks analysis integrated with genetic algorithm

In this investigation, neural networks were used to predict pressure drop of CuO-based nanofluid in a car radiator. For this purpose, the neural network with the multilayer perceptron structure was used to formulate a model for estimating the pressure drop In this way, different concentrations of copper oxide-based nanofluid were prepared. The base fluid was the mixture of ethylene glycol and pure water (60:40 wt%) which usually used as the cooling fluid in automotive industries. The prepared nanofluid samples were used in a car radiator and the pressure drop of nanofluid flows in the system at different Reynolds were measured. The main purpose of this study was developing the optimized neural networks for predicting the pressure drop of the system with sufficient precision. For the aim of designing the model’s structure, different neural networks were constructed and applied by changing the adjustable parameters (containing the transfer function, training rule, momentum’s amount, hidden layers’ number and the neurons’ number in hidden layer). In each case, the structure with the highest correlation coefficient was chosen as the final model. The selection of each parameters in the neural network model requires repeated tests and errors. So, genetic algorithm was used to optimize these parameters. Additionally, the pressure drop in the radiator of this method was investigated in neural network optimization. The outcomes indicated which a high accuracy in modeling and estimating the pressure drop of nanofluid flows in the studied system can be achieved by the neural network.

Nano-to-meso structure of cellulose nanocrystal phases in ethylene-glycol-water mixtures.

The self-assembly and phase behavior of cellulose nanocrystals (CNCs) in binary liquid mixtures of ethylene-glycol (EG):water was investigated. Our findings indicate that a small fraction of water delays the onset of colloidal jammed states previously reported in water-free organic solvents. Here the full phase diagram of CNCs evolves, including the chiral nematic phase (N*), characterized by long-range orientational order and non-isotropic macroscopic properties. Furthermore, the effect of the solvent-mixture composition on the properties of the CNC mesophases is found to be scale-dependent: the micron-size pitch of the N* phase decreases as the dielectric constant (εr) of the solvent mixture is reduced (higher EG content). Yet the nanometric inter-particle spacing of the CNC rods (measured using SAXS and cryo-TEM) is almost independent on the EG content. Also, unlike theoretical predictions, the transition to the biphasic regime is not sensitive to εr of the solvent mixtures and takes place at a higher CNC volume fraction than in aqueous suspensions. These observations may be rationalized by hypothesizing that vicinal water, adsorbed at the CNC surface, prevents kinetic arrest, and dictates the local dielectric constant and thus the effective diameter of the rods (via the Debye length), while εr of the liquid-mixture dominates the pitch length (micron scale) and the optical properties. These findings indicate that the water content of EG:water mixtures may be used for engineering colloidal inks where delayed kinetic arrest and jamming of the CNCs enable printing and casting of tunable, optically-active thin films and coatings.