Study of Iron Nanopowders into Fluids of Industrial Lubrication

2012 ◽  
Vol 727-728 ◽  
pp. 1654-1659 ◽  
Author(s):  
Mabelle Biancarde Oliveira ◽  
Maryana Antonia Braga Batalha Souza ◽  
José Adilson de Castro ◽  
Alexandre José da Silva
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Effective Viscosity ◽  
Heat Transfer Performance ◽  
Volume Fraction ◽  
Cell Model ◽  
Heat Extraction ◽  
Unit Cell Model ◽  
Metal Parts ◽  
Heat Transfer Fluids

The machines and equipment has required increasing performance of lubricating fluids and coolants which plays important role on reducing friction with the metal parts and heat extraction. Viscosity and thermal conductivity are the most important properties of lubricants, in relation to the friction between the fluid molecules. This paper presents two useful models to predict this properties and their relation with the particles volume fraction and temperature in the nanofluid formed by adition of iron or particles produced by friction. Nanofluids are innovative heat transfer fluids with superior potential for enhancing the heat transfer performance of conventional fluids. In this paper the Unit Cell Model (UCM) which considers the Brownian movement experienced by the nanoparticles are adapt to predict the increment of thermal conductivity of iron nanopowders and standard lubrication oil. The viscosity of the nanofluids was adapt from a model usually suitable for predict the effective viscosity of emulsions. Model results indicated a strong effect of the particle size and volume fractions on the increment of thermal conductivity.

scholarly journals A predictive model of thermal conductivity of plain woven fabrics

2017 ◽  
Vol 21 (4) ◽  
pp. 1627-1632 ◽  
Author(s):  
Jia-Jia Wu ◽  
Hong Tang ◽  
Yu-Xuan Wu
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Numerical Simulation ◽  
Heat Flux ◽  
Thermal Comfort ◽  
Cell Model ◽  
Woven Fabrics ◽  
Woven Fabric ◽  
Unit Cell Model ◽  
Fabric Structure

This paper proposes an effective method to predict the thermal conductivity of plain woven blended fabric to optimize woven fabric structure, and to evaluate thermal comfort. The unit cell model of fabric is established for numerical simulation of heat transfer through thickness. The thermal conductivity of blended yarns is calculated by a series model. The temperature and heat flux distributions are verified experimentally.

Studies on few Water Based Nanofluids Behavior at Heating

2015 ◽  
Vol 1128 ◽  
pp. 384-389
Author(s):  
Madalina Georgiana Moldoveanu ◽  
Alina Adriana Minea
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Unsolved Problem ◽  
Volume Fraction ◽  
Transfer Enhancement ◽  
Two Phase ◽  
Heat Transfer Fluids ◽  
Surface Areas ◽  
Water Based ◽  
Semi Empirical

Application of nanoparticles provides an effective way of improving heat transfer characteristics of fluids. Particles less than 100 nm in diameter exhibit different properties from those of conventional solids. Compared with micron-sized particles, nanophase powders have much larger relative surface areas and a great potential for heat transfer enhancement. Some researchers tried to suspend nanoparticles into fluids to form high effective heat transfer fluids. Some preliminary experimental results showed that increase in thermal conductivity of approximately 60% can be obtained for some nanofluids consisting of water and 5 vol% CuO nanoparticles. So, the thermal conductivity of nanofluid was found to be strongly dependent on the nanoparticle volume fraction. So far it has been an unsolved problem to develop a sophisticated theory to predict thermal conductivity of nanofluids, although there are some semi empirical correlations to calculate the apparent conductivity of two-phase mixture. In this article, several correlations for predicting the nanofluid thermal conductivity will be compared and results will be discussed for three water based nanofluids.

Parametric Experimental Study of Viscosity of Nanofluids

2006 ◽  
Author(s):  
Ravi Prasher ◽  
David Song ◽  
Jinlin Wang ◽  
Patrick Phelan
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Experimental Study ◽  
Pressure Drop ◽  
Volume Fraction ◽  
Systematic Investigation ◽  
Research Community ◽  
Transfer Enhancement ◽  
Heat Transfer Fluids ◽  
Potential Applications

There is a lot of interest in the research community about nanofluids due to their high thermal conductivity and potential applications as heat transfer fluids, however a systematic investigation on the viscosity of the nanofluids is still lacking from the literature. Any heat transfer enhancement due to force convention, also leads to increase in the pressure drop. Knowledge of the pressure drop is very important to understand the pumping requirements. Pressure drop is directly proportional to the viscosity of the liquid. Addition of nanoparticles will enhance the viscosity of the nanofluids. In this paper experimental results on the viscosity of propylene glycol based nanofluids are reported for various parameters such as nanoparticle size, temperature and volume fraction. Effect of Brownian motion on the viscosity of nanofluids is also explored.

Preparation and Characterization of Rutile Titania Nanofluids Stabilized in Different Surfactants Base Fluids

2020 ◽  
Vol 10 (5) ◽  
pp. 682-695
Author(s):  
Radwa A. El-Salamony ◽  
Mohamed Z. Abd-Elaziz ◽  
Rania E. Morsi ◽  
Ahmed M. Al-Sabagh ◽  
Saad S.M. Hassan
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Performance ◽  
Sodium Dodecyl ◽  
Transfer Performance ◽  
Heat Transfer Fluids ◽  
Transmission Electron ◽  
Performance Of Heat Transfer ◽  
Rutile Titania ◽  
The Stability

Background: Improvement of conventional heat transfer fluids for achieving higher energy efficiencies in thermal equipment is a key parameter to conserve energy in industries. The heat transfer fluids such as water, oil and ethylene glycol greatly suffer low heat transfer performance in industrial processes. There is a need to develop new types of heat transfer fluids that are more effective in terms of heat transfer performance. Nanofluids enhance thermal conductivity and improve the thermal performance of heat transfer systems. Methods: New titania nanofluid samples consisting of 0.0625 to 1% TiO2 nanoparticles were prepared and characterized. The method of preparation was based on prior precipitation of TiO2 from an ammoniacal solution of pH 9 and calcination at 900°C. Solubilization, homogenization and stabilization of the of the nanoparticles were performed by sonication in the presence of sodium dodecyl sulfate (SDS) anionic surfactant and cetyltrimethylammonium bromide (CTAB) cationic surfactant. Results: This treatment was also utilized to increase the stability and improve the thermal properties of the fluid. Conclusion: Several characterization techniques including measurements of hydrodynamic size distribution, zeta potential, transmission electron microscopy (TEM), viscosity, density, specific heat, thermal conductivity, and sedimentation photo capturing were used to measure and confirm the stability and sedimentation rate of the prepared nanofluids.

A Study on Uncertainties in Estimations of Thermal Conductivity of Alumina Nanofluids

2015 ◽  
Vol 809-810 ◽  
pp. 525-530 ◽  
Author(s):  
Madalina Georgiana Moldoveanu ◽  
Alina Adriana Minea
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Performance ◽  
Unsolved Problem ◽  
Volume Fraction ◽  
Solid Particles ◽  
Two Phase ◽  
Polymeric Particles ◽  
Semi Empirical ◽  
Thermal Conductivities

An innovative way of improving the thermal conductivities of fluids is to suspend small solid particles in the fluids. Various types of powders such as metallic, non-metallic and polymeric particles can be added into fluids to form slurries. The thermal conductivities of fluids with suspended particles are expected to be higher than that of common fluids. Application of nanoparticles provides an effective way of improving heat transfer characteristics of fluids. By suspending nanophase particles in heating or cooling fluids, the heat transfer performance of the fluid can be significantly improved. Moreover, the thermal conductivity of nanofluid is strongly dependent on the nanoparticle volume fraction. So far it has been an unsolved problem to develop a sophisticated theory to predict thermal conductivity of nanofluids, although there are some semi empirical correlations to calculate the apparent conductivity of two-phase mixture. In this article few correlations were considered and differences were noted between different theories. In conclusion, a lot of uncertainties in determining thermal conductivity were noticed.

scholarly journals Characterization of Local Nano-Heat Transfer Fluids for Solar Thermal Collection

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Kawira Millien
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Exchanger ◽  
Copper Nanoparticles ◽  
Energy Demand ◽  
Volume Fraction ◽  
Local Heat Transfer ◽  
Local Heat ◽  
Solar Thermal ◽  
Heat Transfer Fluids

Performance of organic oils in solar thermal collection is limited due to their low thermal conductivity when they are compared to molten salt solutions. Extraction of organic oils from plants can be locally achieved. The purpose of this study was to investigate the effect of use of copper nanoparticles in some base local heat transfer fluids (HTFs). Addition of volume fraction of 1.2% of the copper nanoparticles to oil-based heat transfer fluids improved their thermal conductivity as deduced from the thermal heat they conducted from solar radiation. The oil-based copper nanofluids were obtained by preparation of a colloidal solution of the nanoparticles. Impurities were added to increase the boiling point of the nano-heat transfer fluids. Stabilizers were used to keep the particles suspended in the oil-based fluids. The power output of the oil-based copper nano-heat transfer fluids was in the range of 475.4 W to 1130 W. The heat capacity of the steam in the heat exchanger was 93.7% dry and had a thermal capacity of 5.71 × 103 kJ. The heat rate of flow of the oil-based copper nano-heat transfer fluids was an average of 72.7 Js−1·kg−1 to 89.1 Js−1·kg−1. The thermal efficiency for the oil-based copper nano-heat transfer fluids ranged from 0.85 to 0.91. The average solar thermal solar intensity was in the range 700 Wm−2 to 1180 Wm−2. The heat exchanger used in this study was operating at 4.15 × 103 kJ and a temperature of 500.0°C. The heat transfer fluids entered the exchanger at an average temperature of 381°C and exited at 96.3°C and their heat coefficient ranged between 290.1 Wm−2°C and 254.1 Wm−2°C. The average temperatures of operation ranged between 394.1°C and 219.7°C with respective temperature efficiencies ranging between 93.4% and 64.4%. It was established that utilization of copper nanoparticles to enhance heat transfer in oil-based local heat transfer fluids can mitigate energy demand for meeting the world’s increasing energy uses, especially for areas inaccessible due to poor land terrain.

scholarly journals Effect of Variable Fluid Properties on Natural Convection of Nanofluids in a Cavity with Linearly Varying Wall Temperature

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
M. Bhuvaneswari ◽  
Poo Balan Ganesan ◽  
S. Sivasankaran ◽  
K. K. Viswanathan
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Heat Transfer Rate ◽  
Wall Temperature ◽  
Transfer Rate ◽  
Effective Viscosity ◽  
Numerical Solutions ◽  
Volume Fraction ◽  
Left Wall

The present study analyzed convective heat transfer and fluid flow characteristics of nanofluid in a two-dimensional square cavity under different combinations of thermophysical models of nanofluids. The right vertical wall temperature is varying linearly with height and the left wall is maintained at low temperature whereas the horizontal walls are adiabatic. Finite volume method is used to solve the governing equations. Two models are considered to calculate the effective thermal conductivity of the nanofluid and four models are considered to calculate the effective viscosity of the nanofluid. Numerical solutions are carried out for different combinations of effective viscosity and effective thermal conductivity models with different volume fractions of nanoparticles and Rayleigh numbers. It is found that the heat transfer rate increases for Models M1 and M3 on increasing the volume fraction of the nanofluid, whereas heat transfer rate decreases for Model M4 on increasing the volume fraction of the nanoparticle. The difference among the effective dynamic viscosity models of nanofluid plays an important role here such that the average Nusselt number demonstrates an increasing or decreasing trend with the concentration of nanoparticle.

Nanoparticles Shape Effect on Thermal Conductivity of Nanofluids: A Molecular Dynamics Study

2019 ◽  
Author(s):  
Md. Rakibul Hasan Roni ◽  
AKM M. Morshed ◽  
Amitav Tikadar ◽  
Titan C. Paul ◽  
Jamil A. Khan
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Performance ◽  
Volume Fraction ◽  
Thermal Conductivity Enhancement ◽  
Shape Effect ◽  
Cylindrical Shape ◽  
Transfer Performance ◽  
Conductivity Enhancement ◽  
System Temperature

Abstract Nanofluids have become the subject of theoretical and experimental researches over the few decades due to their enhanced heat transfer performance. In this study, thermal conductivity of copper argon nanofluids is determined through MD simulation. Different types of nanoparticles based on shape was used to make nanofluids. Role of different shape of nanoparticles such as cylindrical, cubical and spherical was disused. Green Kubo method is employed to determine the thermal conductivity of the nanofluids. Result shows that, for volume fraction 3% and 86 K system temperature, thermal conductivity enhancement of nanofluid containing spherical, cubical and cylindrical shape is 15%, 40% and 50% respectively compared with that of base fluid. Thermal conductivity enhancement of nanofluid for spherical particle at 86 K, 94 K and 102 K is 15%, 30% and 40% respectively while for volume fraction 3%, 6% and 9%, the enhancement is 15%, 35% and 45% respectively. The mechanism of increased heat transfer performance for different shape of the nanoparticles is discussed in this paper.

Molecular Dynamical Study on the Nanoscale Effect of Particles on the Thermal Conductivity and Viscosity in Nanofluids

2007 ◽  
Author(s):  
Wen-Qiang Lu ◽  
Qing-Mei Fan
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Volume Fraction ◽  
Simulation Method ◽  
Numerical Results ◽  
Dynamical Study ◽  
Heat Transfer Fluids ◽  
Heat Transfer Efficiency ◽  
Transfer Capability ◽  
Nanoscale Effect

Molecular dynamics (MD) simulation method is used to simulate the thermophysical properties of nanofluids: thermal conductivity and viscosity. This paper reports a better agreement between present numerical results and experimental data. It shows MD to be an effective method to forecast some thermal properties of nanofluids. Many former experiments have shown that this new heat transfer fluids - nanofluids can greatly enhance the heat-transfer efficiency. This work further gives the effects of the volume fraction and the size of nanoparticles on the thermal conductivity and the viscosity of nanofluids. Numerical results show that, decreasing size of nanoparticle or increasing the volume fraction can increase thermal conductivity with increasing viscosity; for suitable volume fraction and size, increasing viscosity with improving heat transfer capability is acceptable.

scholarly journals Testing algorithm for heat transfer performance of nanofluid-filled heat pipe based on neural network

Open Physics ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 751-760
Author(s):  
Lei Lei
Keyword(s):  
Neural Network ◽  
Heat Transfer ◽  
Heat Pipe ◽  
Heat Transfer Performance ◽  
Volume Fraction ◽  
Heat Pipes ◽  
Transfer Performance ◽  
Analysis Model ◽  
Accurate Analysis ◽  
Testing Algorithm

AbstractTraditional testing algorithm based on pattern matching is impossible to effectively analyze the heat transfer performance of heat pipes filled with different concentrations of nanofluids, so the testing algorithm for heat transfer performance of a nanofluidic heat pipe based on neural network is proposed. Nanofluids are obtained by weighing, preparing, stirring, standing and shaking using dichotomy. Based on this, the heat transfer performance analysis model of the nanofluidic heat pipe based on artificial neural network is constructed, which is applied to the analysis of heat transfer performance of nanofluidic heat pipes to achieve accurate analysis. The experimental results show that the proposed algorithm can effectively analyze the heat transfer performance of heat pipes under different concentrations of nanofluids, and the heat transfer performance of heat pipes is best when the volume fraction of nanofluids is 0.15%.

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