Experimental investigation of nanofluid stability on thermal performance and flow regimes in pulsating heat pipe

Pulsating heat pipe (PHP) is a type of wickless heat pipe that has a simple structure and an outstanding thermal performance. Nanofluid is a type of fluid in which nanoparticles are dispersed in a base fluid and have generally a better thermal conductivity in comparison with its base fluid. In this article, the performance of a nanofluid PHP is investigated. Graphene/water nanofluid with a concentration of 1 mg mL^?1 and TiO₂ (titania)/water nanofluid with a concentration of 10 mg mL^?1 are used as the working fluids. To simultaneously investigate the thermal performance and flow regimes in the PHP, a one-turn copper PHP with a Pyrex glass attached to its adiabatic section is used. A one-turn Pyrex PHP is also used to fully visualize flow patterns in the PHP. Our results show that the material for the fabrication of a PHP and temperature of the working fluid are the most important parameters that affect the stability of a nanofluid in the PHP. The more stable nanofluid keeps its stability in the cupper PHP, while the less stable nanofluid starts to aggregate right after the injection to the cupper PHP. The more stable nanofluid has a better thermal performance than water, while the less stable nanofluid has a worse thermal performance than water. In the case of flow regimes, no significant differences are observed between the nanofluid PHP and the water PHP which is different from the previous observations. These results can help researchers to choose the best working fluid for PHPs.

     

β-FeOOH纳米流体的制备及其热容的绝热量热法研究

本文介绍了用FeCl3•6H2O和尿素为反应物,在不添加表面活性剂等添加剂的条件下,制备纳米流体（纳米颗粒悬浮液）的新方法。通过XRD和TEM表征技术,表明得到的固体样品是纺锤形的纳米β–FeOOH颗粒。由于反应体系中含有NH3分子,其中在N原子和Fe原子之间可能存在弱的相互作用,因此,可以获得稳定的β–FeOOH纳米流体。该体系超额热容的研究也支持这一观点。应用绝热量热仪测量了制备的固体β–FeOOH颗粒和其纳米流体在不同温度下的摩尔热容。建立了摩尔热容与温度的函数关系。由此可获得所研究样品的焓、熵等热力学函数相对于298 .15 K的改变量。     

An overview on the effect of ultrasonication duration on different properties of nanofluids

Journal of Thermal Analysis and Calorimetry - Preparation of nanofluid is of prime importance to obtain better thermal and physical properties. Different preparation parameters used in nanofluid...     

A review on fuel cell types and the application of nanofluid in their cooling

Journal of Thermal Analysis and Calorimetry - The application of nanofluid in cooling systems is increasing. The nanofluid consists of a mixture of nanometallic and nonmetallic particles, which...     

Mixed convective slip flow of hybrid nanofluid (MWCNTs + Cu + Water), nanofluid (MWCNTs + Water) and base fluid (Water): a comparative investigation

Journal of Thermal Analysis and Calorimetry - Here, we addressed comparative investigation of hybrid nanofluid (MWCNTs?+?Cu?+?Water), nanofluid (MWCNTs?+?Water)...     

On the hydrothermal features of radiative Fe3O4–graphene hybrid nanofluid flow over a slippery bended surface with heat source/sink

Journal of Thermal Analysis and Calorimetry - The present investigation concentrates on the hydrothermal features of both hybrid nanofluid and usual nanofluid flow over a slippery permeable bent...     

Turbulent combined forced and natural convection of nanofluid in a 3D rectangular channel using two-phase model approach

Journal of Thermal Analysis and Calorimetry - The nanofluid is a mixture of base fluid and solid nanoparticles in nanosize. The heat transfer generated by the nanofluid is more than the base fluid...     

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.     

Wetting and spreading of nanofluids on solid surfaces driven by the structural disjoining pressure: statics analysis and experiments

The wetting and spreading of nanofluids composed of liquid suspensions of nanoparticles have significant technological applications. Recent studies have revealed that, compared to the spreading of base liquids without nanoparticles, the spreading of wetting nanofluids on solid surfaces is enhanced by the structural disjoining pressure. Here, we present our experimental observations and the results of the statics analysis based on the augmented Laplace equation (which takes into account the contribution of the structural disjoining pressure) on the effects of the nanoparticle concentration, nanoparticle size, contact angle, and drop size (i.e., the capillary and hydrostatic pressure); we examined the effects on the displacement of the drop-meniscus profile and spontaneous spreading of a nanofluid as a film on a solid surface. Our analyses indicate that a suitable combination of the nanoparticle concentration, nanoparticle size, contact angle, and capillary pressure can result not only in the displacement of the three-phase contact line but also in the spontaneous spreading of the nanofluid as a film on a solid surface. We show here, for the first time, that the complete wetting and spontaneous spreading of the nanofluid as a film driven by the structural disjoining pressure gradient (arising due to the nanoparticle ordering in the confined wedge film) is possible by decreasing the nanoparticle size and the interfacial tension, even at a nonzero equilibrium contact angle. Experiments were conducted on the spreading of a nanofluid composed of 5, 10, 12.5, and 20 vol % silica suspensions of 20 nm (geometric diameter) particles. A drop of canola oil was placed underneath the glass surface surrounded by the nanofluid, and the spreading of the nanofluid was monitored using an advanced optical technique. The effect of an electrolyte, such as sodium chloride, on the nanofluid spreading phenomena was also explored. On the basis of the experimental results, we can conclude that a nanofluid with an effective particle size (including the electrical double layer) of about 40 nm, a low equilibrium contact angle (<3°), and a high effective volume concentration (>30 vol %) is desirable for the dynamic spreading of a nanofluid system with an interfacial tension of 0.5 mN/m. Our experimental observations also validate the major predications of our theoretical analysis.     

Melting heat transfer in squeezing flow of basefluid (water), nanofluid (CNTs + water) and hybrid nanofluid (CNTs + CuO + water)

Journal of Thermal Analysis and Calorimetry - Unsteady squeezed flow of hybrid nanofluid is investigated in this analysis. Comparison of hybrid nanofluid (using CNTs?+?CuO) and...     

Flow and heat transfer in non-Newtonian nanofluids over porous surfaces

In the present study, heat transfer and fluid flow of a pseudo-plastic non-Newtonian nanofluid over permeable surface has been solved in the presence of injection and suction. Similarity solution method is utilized to convert the governing partial differential equations into ordinary differential equations, which then is solved numerically using Runge–Kutta–Fehlberg fourth–fifth order (RKF45) method. The Cu, CuO, TiO₂ and Al₂O₃ nanoparticles are considered in this study along with sodium carboxymethyl cellulose (CMC)/water as base fluid. Validation has been done with former numerical results. The influence of power-law index, volume fraction of nanoparticles, nanoparticles type and permeability parameter on nanofluid flow and heat transfer was investigated. The results of the study illustrated that the flow and heat transfer of non-Newtonian nanofluid in the presence of suction and injection has different behaviors. For injection and the impermeable plate, the non-Newtonian nanofluid shows a better heat transfer performance compared to Newtonian nanofluid. However, changing the type of nanoparticles has a more intense influence on heat transfer process during suction. It was also observed that in injection, contrary to the other two cases, the usage of non-Newtonian nanofluid can decrease heat transfer in all cases.

     

Hybrid thermal management of lithium-ion batteries using nanofluid,metal foam,and phase change material: an integrated numerical–experimental approach

Safety issues of Li-ion batteries imposed by unfavorable thermal behavior accentuate the need for efficient thermal management systems to prevent the runaway conditions. To that end, a hybrid thermal management system is designed and further investigated numerically and experimentally in the present study. The passive cooling system is fabricated by saturating copper foam with paraffin as the phase change material (PCM) and integrated with an active cooling system with alumina nanofluid as the coolant fluid. Results for various Reynolds numbers and different heating powers indicate that the hybrid nanofluid cooling system can successfully fulfill safe operation of the battery during stressful operating conditions. The maximum time in which all PCM field is changed to the liquid phase is defined as the onset of the stressful conditions. Therefore, the start time of stressful conditions at 41 W and Re 420 is increased from 3700 s with nanofluid composed of 1% volume fraction nanoparticles (VF-1%) to 4600 s with nanofluid VF-2% during high current discharge rates. Nanofluid cooling extends the operating time of the battery in comparison with the water-based cooling system with 200-s (nanofluid with volume fraction of 1%) and 900-s (nanofluid with volume fraction of 2%) increases in operating time at Reynolds of 420. Using nanofluid, instead of water, postpones the onset of paraffin phase transition effectively and prolongs its melting time which consequently leads to a decrease in the rate of temperature rise.

     

Experimental investigation and modeling of thermal conductivity of CuO–water/EG nanofluid by FFBP-ANN and multiple regressions

The purpose of this study is to predict the thermal conductivity of copper oxide (CuO) nanofluid by using feed forward backpropagation artificial neural network (FFBP-ANN). Thermal conductivity of CuO nanofluid is measured experimentally using transient hot-wire technique in temperature range of 20–60 °C and in volume fractions of 0.00125, 0.0025, 0.005 and 0.01% for neural network training and modeling. In addition, in order to evaluate accuracy of modeling in predicting the coefficient of nanofluid thermal conductivity, indices of root-mean-square error, coefficient of determination (R ²) and mean absolute percentage error have been used. FFBP-ANN with two input parameters (volume fraction and nanofluid temperature) and one output parameter (nanofluid thermal conductivity) in addition to two hidden layers and one outer layer which purelin, logsig and tansig functions are used was considered as the most optimum structure for modeling with neuron number of 4–10–1. In this study, among common methods of theoretical modeling of nanofluid thermal conductivity, theoretical method of Maxwell and also multivariate linear regression model was used for explaining the importance of modeling and predicting the results using neural network. According to this research, the results of indices and predictions show high accuracy and certainty of ANN modeling in comparison with empirical results and theoretical models.     

Modelling and measuring the thermal conductivity of multi-metallic Zn/Cu nanofluid

A metallic nanofluid is a suspension of metallic nanoparticles in a base fluid. Multi-metallic nanoparticles are a combination of two or more types of metallic particles. Such multi-metallic nanoparticles were suspended in water using an ultrasonic vibrator for different total volume fractions and different ratios of metallic/metallic nanoparticles. A transient hot wire setup was built to measure the thermal conductivity of the nanofluid at different temperatures. The experimental results were in good agreement with the results in the literature. Then, the experimental results were used as input data for an adaptive neural fuzzy inference system (ANFIS) to predict the thermal conductivity of the multi-metallic nanofluid. The maximum deviation between the ANFIS results and experimental measurements was 1 %. The predicted results and the experimental data were compared with other models. The ANFIS model was found to have good ability to predict the thermal conductivity of the multi-metallic nanofluid over the range of the experimental results.     

Experimental investigation of first and second laws in a direct absorption solar collector using hybrid Fe3O4/SiO2 nanofluid

In this study, energy and entropy analysis of a residential-type direct absorption solar collector using hybrid Fe₃O₄/SiO₂ nanofluid is evaluated experimentally. The hybrid nanofluid samples are prepared in the different volume ratios of Fe₃O₄/SiO₂ (25:75, 50:50 and 75:25) and different volume fractions (500 ppm, 1000 ppm and 2000 ppm). The appropriate nanofluid samples for using as the working fluid of the collector are chosen based on the results of stability and optical properties of nanofluid. Then, outdoor thermal performance of collector is investigated using the experimental setup based on EN12975-2. Measurement of nanofluid optical properties using the spectrophotometry method shows that the extinction coefficient of 2000 ppm hybrid Fe₃O₄/SiO₂ nanofluid is on average 10 cm^?1 higher than that of the base fluid. Results of energy analysis display that the collector efficiency is increased by mass flow rate and volume fraction of nanofluid asymptotically. The asymptotic value is about 83% for 2000 ppm hybrid Fe₃O₄/SiO₂ nanofluid. The findings indicate that the variation of exergy efficiency of a direct absorption solar collector with the volume fraction and mass flow rate is similar to energy efficiency. The enhancement of exergy efficiency is 66.4% for mass flow rates of 0.0225 kg s^?1 by increasing the volume fraction from 0 to 2000 ppm. It is also observed that dimensionless entropy generation number is decreased by nanofluid volume fraction and by mass flow rate. The lowest entropy generation number is obtained in the mass flow rate of 0.0225 kg s^?1 and the volume fraction of 2000 ppm. The variation of Bejan number by volume fraction shows that the contribution of pressure drop in entropy generation is insignificant.

     

基于二维材料的仿生纳流体通道在能量转化中的应用

生物启发的仿生人工纳流体通道以其可控的几何结构和可调的化学性质而迅速发展成为一个热门研究领域, 其中, 基于二维(2D)纳米材料的二维纳流体通道具有易于制造、 高效的化学改性和致密堆积的片层通道结构以及流体阻力小等优势而受到广泛关注, 预期在渗透能转换方面具有巨大的潜力. 本文简要介绍了二维纳流体通道的特征及优势; 基于二维仿生能量转换体系最新进展以及对二维纳流体通道能量转化发展前景进行了展望.     

Evaluation of the effects of the presence of ZnO -TiO2 (50 %–50 %) on the thermal conductivity of Ethylene Glycol base fluid and its estimation using Artificial Neural Network for industrial and commercial applications

In this study, the thermal conductivity (k_nf) of ZnO -TiO₂ (50 %–50 %)/ Ethylene Glycol hybrid nanofluid using Artificial Neural Networks (ANNs) was predicted. The nanofluid was prepared at different volume fractions (φ) of nanoparticles (φ = 0.001 to 0.035) and temperatures (T = 25 to 50 °C). In this study, an algorithm is presented to find the best neuron number in the hidden layer. Also, a surface fitting method has been applied to predict the k_nf of nanofluid. Finally, the correlation coefficients, performances, and Maximum Absolute Error (MAE) for both methods have been presented and compared. It could be understood that the ANN method had a better ability in predicting the k_nf of nanofluid compared to the fitting method. This method not only showed better performance but also reached a better MAE and correlation coefficient.     

Deep eutectic solvent based magnetic nanofluid in the development of stir bar sorptive dispersive microextraction: An efficient hyphenated sample preparation for ultra‐trace nitroaromatic explosives extraction in wastewater

A deep eutectic solvent based magnetic nanofluid was coupled with stir bar sorptive dispersive microextraction as a hyphenated sample preparation technique. The neodymium core magnetic stir bar was coated physically with nanofluid of magnetic carbon nanotube nanocomposites and deep eutectic solvents. The prepared nanofluid has magnetic and strong sorbing properties and is compatible with gas chromatography. In this nanofluid, the deep eutectic solvent acts simultaneously as both carrier and stabilizer for magnetic nanotubes. The predominant experimental variables affecting the extraction efficiency of nitroaromatic compounds were evaluated. Under the optimized conditions, the limit of detection and enrichment factor were in the range of 0.2–4.9 ng/L and 852–1480, respectively. The relative standard deviations were between 5.6 and 10.2% (n  = 6). Method validation was performed by both spiking–recovery method and comparison of results with other methods. Finally, the proposed method was successfully applied for the extraction and pre‐concentration of nitroaromatic explosives in water samples, followed by determination by gas chromatography with micro‐electron capture detection.     

Bioconvective Homann flow of tangent hyperbolic nanofluid due to spiraling disk with convective and zero mas flux constraints

The phenomenon of bioconvection in nanomaterials presents novel applications in the biotechnology, biofuels, enzymes, biomedical engineering and energy systems. Current exploration explores the applications of bioconvection in Homann flow of nanofluid due to spiraling of disk theoretically. The generalized model namely tangent hyperbolic fluid is used to predicts the rheological and thermal impact. The stability of nanofluid is ensured with interaction of motile microorganisms. The Boungrino nanofluid model with thermophoresis and Brownian motion features is used to perform the analysis The thermal distribution of nanofluids is proceeded by utilizing the zero mass thermal constraints. The similarity variables are introduced in order to estimating the dimensionless formulation. The Keller Box method with higher efficiency is imposed with implicit finite difference numerical algorithm. The main observations reveal that with enhancing the radial velocity and azimuthal velocity decreases with increasing sparling angle. For highly viscous case, a decrement in the azimuthal velocity has been observed.     

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.