Convective Transport in Nanofluids

2005 ◽  
Vol 128 (3) ◽  
pp. 240-250 ◽  
Author(s):  
J. Buongiorno
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Boundary Layer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Base Fluid ◽  
Convective Transport ◽  
Brownian Diffusion ◽  
Nanoparticle Dispersion ◽  
Transfer Coefficients

Nanofluids are engineered colloids made of a base fluid and nanoparticles (1-100nm). Nanofluids have higher thermal conductivity and single-phase heat transfer coefficients than their base fluids. In particular, the heat transfer coefficient increases appear to go beyond the mere thermal-conductivity effect, and cannot be predicted by traditional pure-fluid correlations such as Dittus-Boelter’s. In the nanofluid literature this behavior is generally attributed to thermal dispersion and intensified turbulence, brought about by nanoparticle motion. To test the validity of this assumption, we have considered seven slip mechanisms that can produce a relative velocity between the nanoparticles and the base fluid. These are inertia, Brownian diffusion, thermophoresis, diffusiophoresis, Magnus effect, fluid drainage, and gravity. We concluded that, of these seven, only Brownian diffusion and thermophoresis are important slip mechanisms in nanofluids. Based on this finding, we developed a two-component four-equation nonhomogeneous equilibrium model for mass, momentum, and heat transport in nanofluids. A nondimensional analysis of the equations suggests that energy transfer by nanoparticle dispersion is negligible, and thus cannot explain the abnormal heat transfer coefficient increases. Furthermore, a comparison of the nanoparticle and turbulent eddy time and length scales clearly indicates that the nanoparticles move homogeneously with the fluid in the presence of turbulent eddies, so an effect on turbulence intensity is also doubtful. Thus, we propose an alternative explanation for the abnormal heat transfer coefficient increases: the nanofluid properties may vary significantly within the boundary layer because of the effect of the temperature gradient and thermophoresis. For a heated fluid, these effects can result in a significant decrease of viscosity within the boundary layer, thus leading to heat transfer enhancement. A correlation structure that captures these effects is proposed.

A Non-Homogeneous Equilibrium Model for Convective Transport in Flowing Nanofluids

2005 ◽  
Author(s):  
J. Buongiorno
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Equilibrium Model ◽  
Base Fluid ◽  
Convective Transport ◽  
Brownian Diffusion ◽  
Transfer Coefficients ◽  
Homogeneous Equilibrium

A base fluid (e.g., water, ethanol, oil) in which nano-sized (1–100 nm) particles of a different material are dispersed, is known as a nanofluid. Nanofluids are attractive because the presence of the nanoparticles enhances energy transport considerably. As a result, nanofluids have higher thermal conductivity and single-phase heat transfer coefficients than their base fluids. In particular, the heat transfer coefficient increases appear to go beyond the mere thermal-conductivity effect, and cannot be predicted by traditional pure-fluid correlations such as Dittus-Boelter’s. In the nanofluid literature this behavior is generally attributed to thermal dispersion and intensified turbulence, brought about by nanoparticle motion. To test the validity of this assumption, we have considered seven slip mechanisms that can produce a relative velocity between the nanoparticles and the base fluid. These are inertia, Brownian diffusion, thermophoresis, diffusiophoresis, Magnus effect, fluid drainage and gravity. We concluded that, of these seven, only Brownian diffusion and thermophoresis are important slip mechanisms in nanofluids. Based on this finding, we developed a two-component four-equation non-homogeneous equilibrium model for mass, momentum and heat transport in nanofluids. A non-dimensional analysis of the equations suggests that energy transfer by nanoparticle dispersion is negligible, and thus cannot explain the abnormal heat transfer coefficient increases. Furthermore, a comparison of the nanoparticle and turbulent eddy scales clearly indicates that the nanoparticles move homogeneously with the fluid in the presence of turbulent eddies, so an effect on turbulence intensity is also doubtful.

scholarly journals Enhancement of heat transfer coefficient multi-metallic nanofluid with ANFIS modeling for thermophysical properties

2015 ◽  
Vol 19 (5) ◽  
pp. 1613-1620 ◽  
Author(s):  
Hyder Balla ◽  
Shahrir Abdullah ◽  
Wan Faizal ◽  
Rozli Zulkifli ◽  
Kamaruzaman Sopian
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Thermophysical Properties ◽  
Dynamic Viscosity ◽  
Base Fluid ◽  
Volume Fractions ◽  
The Heat Transfer Coefficient ◽  
Cu And Zn

Cu and Zn-water nanofluid is a suspension of the Cu and Zn nanoparticles with the size 50 nm in the water base fluid for different volume fractions to enhance its Thermophysical properties. The determination and measuring the enhancement of Thermophysical properties depends on many limitations. Nanoparticles were suspended in a base fluid to prepare a nanofluid. A coated transient hot wire apparatus was calibrated after the building of the all systems. The vibro-viscometer was used to measure the dynamic viscosity. The measured dynamic viscosity and thermal conductivity with all parameters affected on the measurements such as base fluids thermal conductivity, volume factions, and the temperatures of the base fluid were used as input to the Artificial Neural Fuzzy inference system to modeling both dynamic viscosity and thermal conductivity of the nanofluids. Then, the ANFIS modeling equations were used to calculate the enhancement in heat transfer coefficient using CFD software. The heat transfer coefficient was determined for flowing flow in a circular pipe at constant heat flux. It was found that the thermal conductivity of the nanofluid was highly affected by the volume fraction of nanoparticles. A comparison of the thermal conductivity ratio for different volume fractions was undertaken. The heat transfer coefficient of nanofluid was found to be higher than its base fluid. Comparisons of convective heat transfer coefficients for Cu and Zn nanofluids with the other correlation for the nanofluids heat transfer enhancement are presented. Moreover, the flow demonstrates anomalous enhancement in heat transfer nanofluids.

An Experimental Study on the Convective Heat Transfer Behaviour of Diamond Nanofluids in Electronic Cooling Applications

2018 ◽  
Author(s):  
Farzin Mashali ◽  
Ethan M. Languri ◽  
Jim Davidson ◽  
David Kerns ◽  
Fahad Alkhaldi
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Experimental Study ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Base Fluid ◽  
Convective Heat Transfer Coefficient ◽  
Cold Plate

This study presents the convective heat transfer coefficient of 0.05 wt.% diamond nanofluids containing functionalized nanodiamond dispersed in a base fluid deionized (DI) water flowing in a conduction cold plate under turbulent flow conditions, experimentally. The conduction cold plate was heated via six cartridge heaters with a constant heat transfer rate. The primary experimental study has been implemented to investigate the thermal conductivity of diamond nanofluids which showed a higher effective thermal conductivity than that of the base fluid. In addition, nanofluid was flowed in a closed system with heating at the heat exchanger and cooling via a cooling tank to keep the inlet temperature constant to explore the convection heat transfer properties of diamond nanofluids. Results indicate that the convective heat transfer coefficient and Nusselt number of diamond nanofluid are higher than that of the DI water in a same flow rate, and these properties increased with increase in Reynolds number.

scholarly journals Effect of Saw Type Corrugated Pipe on Laminar Convective Heat Transfer by Using SiC-Water Nanofluid: A Numerical Study

2021 ◽  
Author(s):  
Md Insiat Islam Rabby ◽  
◽  
Farzad Hossain ◽  
Raihan M M ◽  
Afrina Khan Piya ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Reynolds Number ◽  
Nusselt Number ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Pressure Loss ◽  
Transfer Rate ◽  
Base Fluid ◽  
Heat Transfer Area

Enhancing the heat transfer rate is highly required to remove excessive heat load from the heat transfer apparatus, which may cause massive damage to the equipment. Thus, increment of heat transfer area is one of the prime solutions for this issue. The increment of heat transfer area can be done by enhancing the pipe wall and incorporating nanoparticles with working fluids because nanoparticles showed much faster heat dispersion due to a vast surface area for heat transfer and increased thermal conductivity. Also, small molecules of nanoparticles are allowed for free movement and thus micro-convection, promoting high thermal conductivity. Higher thermal conductivity is mainly the result of a higher heat transfer rate. Therefore, in this study, a saw-type corrugated tube was considered along with the SiC-water nanofluid as the working fluid to determine the improvement of laminar convective heat transfer in terms of the Nusselt number, heat transfer coefficient, and pressure loss. The result demonstrated that by increasing the Reynolds number, the Nusselt number, heat transfer coefficient, and pressure loss were increased significantly with the enhancement of SiC-water concentration. At a Reynolds number of 1200, the maximum increment of Nusselt number in comparison to the base fluid was 9.15% when the corrugated pipe was considered. Meanwhile, the maximum improvement of heat transfer coefficient for SiC-water nanofluid in comparison to the base fluid was 37.66%.

Heat Transfer Augmentation Downstream of Rows of Various Dimple Geometries on the Suction Side of a Gas Turbine Airfoil

2010 ◽  
Vol 132 (3) ◽  
Author(s):  
Jason E. Dees ◽  
David G. Bogard ◽  
Ronald S. Bunker
Keyword(s):  
Heat Transfer ◽  
Boundary Layer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Gas Turbine ◽  
Film Cooling ◽  
Suction Side ◽  
Boundary Layer Transition ◽  
Transfer Coefficients ◽  
Film Cooling Holes

Heat transfer coefficients were measured downstream of a row of shaped film cooling holes, as well as elliptical, diffuser, and teardrop shaped dimples, simulating depressions due to film coolant holes of different shapes. These features were placed on the suction side of a simulated gas turbine vane. The dimples were used as approximations to film cooling holes after the heat transfer levels downstream of active fan shaped film cooling holes was found to be independent of film cooling. The effects of the dimples were tested with varying approach boundary layers, freestream turbulence intensity, and Reynolds numbers. For the case of an untripped (transitional) approach boundary layer, all dimple shapes caused approximately a factor of 2 increase in heat transfer coefficient relative to the smooth baseline condition due to the dimples effectively causing boundary layer transition downstream. The exact augmentation varied depending on the dimple geometry: diffuser shapes causing the largest augmentation and teardrop shapes causing the lowest augmentation. For tripped (turbulent boundary layer) approach conditions, the dimple shapes all caused the same 20% augmentation relative to the smooth tripped baseline. The already turbulent nature of the tripped approach flow reduces the effect that the dimples have on the downstream heat transfer coefficient.

scholarly journals The Heat Transfer Coefficient Predictions in Engineering Applications

2021 ◽  
Vol 2108 (1) ◽  
pp. 012022
Author(s):  
Junchi Wan
Keyword(s):  
Heat Transfer ◽  
Boundary Layer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Temperature Ratio ◽  
Transfer Coefficients ◽  
Engineering Applications ◽  
Reynolds Analogy ◽  
Heat Transfer Coefficients ◽  
The Heat Transfer Coefficient

Abstract Most engineering applications have boundary layers; the convective transport of mass, momentum and heat normally occurs through a thin boundary layer close to the wall. It is essential to predict the boundary layer heat transfer phenomenon on the surface of various engineering machines through calculations. The experimental, analogy and numerical methods are the three main methods used to obtain convective heat transfer coefficient. The Reynolds analogy provides a useful method to estimate the heat transfer rate with known surface friction. In the Reynolds analogy, the heat transfer coefficient is independent of the temperature ratio between the wall and the fluid. Other methods also ignore the effect of the temperature ratio. This paper summarizes the methods of predicting heat transfer coefficients in engineering applications. The effects of the temperature ratio between the wall and the fluid on the heat transfer coefficient predictions are studied by summarizing the researches. Through the summary, it can be found that the heat transfer coefficients do show a dependence on the temperature ratio. And these effects are more obvious in turbulent flow and pointing out that the inaccuracy in the determination of the heat transfer coefficient and proposing that the conjugate heat transfer analysis is the future direction of development.

Heat Transfer Augmentation Downstream of Rows of Various Dimple Geometries on the Suction Side of a Gas Turbine Airfoil

2008 ◽  
Author(s):  
Jason E. Dees ◽  
David G. Bogard ◽  
Ronald S. Bunker
Keyword(s):  
Heat Transfer ◽  
Boundary Layer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Gas Turbine ◽  
Film Cooling ◽  
Suction Side ◽  
Boundary Layer Transition ◽  
Transfer Coefficients ◽  
Film Cooling Holes

Heat transfer coefficients were measured downstream of a row of shaped film cooling holes as well as elliptical, diffuser, and teardrop shaped dimples simulating depressions due to film coolant holes of different shapes. These features were placed on the suction side of a simulated gas turbine vane. The dimples were used as approximations to film cooling holes after the heat transfer levels downstream of active fan shaped film cooling holes was found to be independent of film cooling. The effects of the dimples were tested with varying approach boundary layers, freestream turbulence intensity, and Reynolds numbers. For the case of an untripped (transitional) approach boundary layer, all dimple shapes caused approximately a factor of two increase in heat transfer coefficient relative to the smooth baseline condition due to the dimples effectively causing boundary layer transition downstream. The exact augmentation varied depending on the dimple geometry: diffuser shapes causing the largest augmentation and teardrop shapes causing the lowest augmentation. For tripped (turbulent boundary layer) approach conditions, the dimple shapes all caused the same 20% augmentation relative to the smooth tripped baseline. The already turbulent nature of the tripped approach flow reduces the effect that the dimples have on the downstream heat transfer coefficient.

Development of a New Correlation and Post Processing of Heat Transfer Coefficient and Pressure Drop of Functionalized COOH MWCNT Nanofluid by Artificial Neural Network

2018 ◽  
Vol 14 (2) ◽  
pp. 104-112 ◽  
Author(s):  
Mohammad Hemmat Esfe ◽  
Somchai Wongwises ◽  
Saeed Esfandeh ◽  
Ali Alirezaie
Keyword(s):  
Neural Network ◽  
Heat Transfer ◽  
Thermal Conductivity ◽  
Artificial Neural Network ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Transfer Coefficient ◽  
Regression Coefficient ◽  
New Correlation ◽  
The Neural Network

Background: Because of nanofluids applications in improvement of heat transfer rate in heating and cooling systems, many researchers have conducted various experiments to investigate nanofluid's characteristics more accurate. Thermal conductivity, electrical conductivity, and heat transfer are examples of these characteristics. Method: This paper presents a modeling and validation method of heat transfer coefficient and pressure drop of functionalized aqueous COOH MWCNT nanofluids by artificial neural network and proposing a new correlation. In the current experiment, the ANN input data has included the volume fraction and the Reynolds number and heat transfer coefficient and pressure drop considered as ANN outputs. Results: Comparing modeling results with proposed correlation proves that the empirical correlation is not able to accurately predict the experimental output results, and this is performed with a lot more accuracy by the neural network. The regression coefficient of neural network outputs was equal to 99.94% and 99.84%, respectively, for the data of relative heat transfer coefficient and relative pressure drop. The regression coefficient for the provided equation was also equal to 97.02% and 77.90%, respectively, for these two parameters, which indicates this equation operates much less precisely than the neural network. Conclusion: So, relative heat transfer coefficient and pressure drop of nanofluids can also be modeled and estimated by the neural network, in addition to the modeling of nanofluid’s thermal conductivity and viscosity executed by different scholars via neural networks.

scholarly journals Systematic heat transfer measurements in highly viscous binary fluids

2021 ◽  
Author(s):  
Ann-Christin Fleer ◽  
Markus Richter ◽  
Roland Span
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Volatile Component ◽  
Test Tube ◽  
Heat Fluxes ◽  
Transfer Coefficients ◽  
Heat Transfer Coefficients ◽  
Low Viscosity ◽  
The Heat Transfer Coefficient

AbstractInvestigations of flow boiling in highly viscous fluids show that heat transfer mechanisms in such fluids are different from those in fluids of low viscosity like refrigerants or water. To gain a better understanding, a modified standard apparatus was developed; it was specifically designed for fluids of high viscosity up to 1000 Pa∙s and enables heat transfer measurements with a single horizontal test tube over a wide range of heat fluxes. Here, we present measurements of the heat transfer coefficient at pool boiling conditions in highly viscous binary mixtures of three different polydimethylsiloxanes (PDMS) and n-pentane, which is the volatile component in the mixture. Systematic measurements were carried out to investigate pool boiling in mixtures with a focus on the temperature, the viscosity of the non-volatile component and the fraction of the volatile component on the heat transfer coefficient. Furthermore, copper test tubes with polished and sanded surfaces were used to evaluate the influence of the surface structure on the heat transfer coefficient. The results show that viscosity and composition of the mixture have the strongest effect on the heat transfer coefficient in highly viscous mixtures, whereby the viscosity of the mixture depends on the base viscosity of the used PDMS, on the concentration of n-pentane in the mixture, and on the temperature. For nucleate boiling, the influence of the surface structure of the test tube is less pronounced than observed in boiling experiments with pure fluids of low viscosity, but the relative enhancement of the heat transfer coefficient is still significant. In particular for mixtures with high concentrations of the volatile component and at high pool temperature, heat transfer coefficients increase with heat flux until they reach a maximum. At further increased heat fluxes the heat transfer coefficients decrease again. Observed temperature differences between heating surface and pool are much larger than for boiling fluids with low viscosity. Temperature differences up to 137 K (for a mixture containing 5% n-pentane by mass at a heat flux of 13.6 kW/m2) were measured.

Sign in / Sign up

Export Citation Format

Share Document