Estimation of Heat Transfer Coefficient and Thermal Performance Factor of TiO2-water Nanofluid Using Different Thermal Conductivity Models

2017 ◽  
Vol 13 (6) ◽  
Author(s):  
Mohammad Hemmat Esfe ◽  
Ali Akbar Abbasian Arani ◽  
Jafar Amani ◽  
Somchai Wongwises
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Thermal Performance ◽  
Performance Factor ◽  
Thermal Performance Factor ◽  
Conductivity Models

Thermal Modeling for High Thermal Conductivity Thermal Ground Planes

2012 ◽  
Author(s):  
Mohammed T. Ababneh ◽  
Pramod Chamarthy ◽  
Shakti Chauhan ◽  
Frank M. Gerner ◽  
Peter de Bock ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Energy Balance ◽  
Transfer Coefficient ◽  
Thermal Performance ◽  
Interfacial Energy ◽  
Interfacial Heat Transfer Coefficient ◽  
Interfacial Heat Transfer ◽  
Vapor Liquid

Thermal ground planes (TGPs) are flat, thin (external thickness of 2 mm) heat pipes which utilize two-phase cooling. The goal is to utilize TGPs as thermal spreaders in a variety of microelectronic cooling applications. TGPs are novel high-performance, integrated systems able to operate at a high power density with a reduced weight and temperature gradient. In addition to being able to dissipate large amounts of heat, they have very high effective axial thermal conductivities and (because of nano-porous wicks) can operate in high adverse gravitational fields. A three-dimensional (3D) finite element model is used to predict the thermal performance of the TGP. The 3D thermal model predicts the temperature field in the TGP, the effective axial thermal conductivity, and the evaporation and the condensation rates. A key feature of this model is that it relies on empirical interfacial heat transfer coefficient data to very accurately model the interfacial energy balance at the vapor-liquid saturated wick interface. Wick samples for a TGP are tested in an experimental setup to measure the interfacial heat transfer coefficient. Then the experimental heat transfer coefficient data are used for the interfacial energy balance. Another key feature of this model is that it demonstrates that for the Jakob numbers of interest, the thermal and flow fields can be decoupled except at the vapor-liquid saturated wick interface. This model can be used to predict the performance of a TGP for different geometries and implementation structures. This paper will describe the model and how it incorporates empirical interfacial heat transfer coefficient data. It will then show theoretical predictions for the thermal performance of TGP’s, and compare with experimental results.

Heat Transfer and Pressure Drop in a Converging Lattice Structure for Airfoil Trailing Edge Cooling

2008 ◽  
Author(s):  
Krishnendu Saha ◽  
Sumanta Acharya ◽  
Chiyuki Nakamata
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Transfer Coefficient ◽  
Turbine Blade ◽  
Thermal Performance ◽  
Lattice Structure ◽  
Lattice Structures ◽  
Performance Factor ◽  
The Heat Transfer Coefficient

Lattice-matrix structures have distinct advantages in enhancing heat transfer in the cooling channels of a gas turbine blade. Lattice structures not only enhance heat transfer coefficient but also provide structural rigidity to the turbine blade. Stationary tests were performed for a 12 times scaled up model at four Reynolds numbers (4,000 < Re < 20,000) in a converging lattice structure. A narrow band liquid crystal technique is used to determine the heat transfer coefficient in the channel. The results shows very high heat transfer coefficient enhancement in the impingement regions. The average heat transfer coefficient enhancement for a channel with lattice structures is also higher (Nu/Nu0 = 1.9–3) than a pin fin cooling configuration channel (Nu/Nu0 = 1.7–2.2). The heat transfer coefficient enhancement decreases with increasing Reynolds number. Pressure data are taken at some specific points throughout the channel. High pressure drop due to the turning of the flow in the lattice structure is observed. Friction factor and overall thermal performance factor are calculated. The overall thermal performance factor lies in the range 0.64–1.

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 Simulation approach on turbulent thermal performance factor of Al2O3-Cu/water hybrid nanofluid in circular and non-circular ducts

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Ing Jiat Kendrick Wong ◽  
Ngieng Tze Angnes Tiong
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Pressure Drop ◽  
Thermal Performance ◽  
Heat Transfer Performance ◽  
Pure Water ◽  
Hybrid Nanofluid ◽  
Performance Factor ◽  
Thermal Performance Factor ◽  
The Heat Transfer Coefficient

AbstractThis paper presents the numerical study of thermal performance factor of Al2O3-Cu/water hybrid nanofluid in circular and non-circular ducts (square and rectangular). Turbulent regime is studied with the Reynolds number ranges from 10000 to 100000. The heat transfer performance and flow behaviour of hybrid nanofluid are investigated, considering the nanofluid volume concentration between 0.1 and 2%. The thermal performance factor of hybrid nanofluid is evaluated in terms of performance evaluation criteria (PEC). This present numerical results are successfully validated with the data from the literature. The results indicate that the heat transfer coefficient and Nusselt number of Al2O3-Cu/water hybrid nanofluid are higher than those of Al2O3/water nanofluid and pure water. However, this heat transfer enhancement is achieved at the expense of an increased pressure drop. The heat transfer coefficient of 2% hybrid nanofluid is approximately 58.6% larger than the value of pure water at the Reynolds number of 10000. For the same concentration and Reynolds number, the pressure drop of hybrid nanofluid is 4.79 times higher than the pressure drop of water. The heat transfer performance is the best in the circular pipe compared to the non-circular ducts, but its pressure drop increment is also the largest. The hybrid nanofluid helps to improve the problem of low heat transfer characteristic in the non-circular ducts. In overall, the hybrid nanofluid flow in circular and non-circular ducts are reported to possess better thermal performance factor than that of water. The maximum attainable PEC is obtained by 2% hybrid nanofluid in the square duct at the Reynolds Number of 60000. This study can help to determine which geometry is efficient for the heat transfer application of hybrid nanofluid.

Experimental Convective Heat Transfer With Nanofluids

2008 ◽  
Author(s):  
S. Kabelac ◽  
K. B. Anoop
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Turbulent Regime ◽  
Heat Transfer Characteristics ◽  
Forced Convective Heat Transfer ◽  
Transfer Characteristics

Nanofluids are colloidal suspensions with nano-sized particles (<100nm) dispersed in a base fluid. From literature it is seen that these fluids exhibit better heat transfer characteristics. In our present work, thermal conductivity and the forced convective heat transfer coefficient of an alumina-water nanofluid is investigated. Thermal conductivity is measured by a steady state method using a Guarded Hot Plate apparatus customized for liquids. Forced convective heat transfer characteristics are evaluated with help of a test loop under constant heat flux condition. Controlled experiments under turbulent flow regime are carried out using two particle concentrations (0.5vol% and 1vol %). Experimental results show that, thermal conductivity of nanofluids increases with concentration, but the heat transfer coefficient in the turbulent regime does not exhibit any remarkable increase above measurement uncertainty.

scholarly journals Augmentation of Heat Transfer in a Circular Channel with Inline and Staggered Baffles

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8593
Author(s):  
Muneerah Al Nuwairan ◽  
Basma Souayeh
Keyword(s):  
Heat Transfer ◽  
Thermal Performance ◽  
Working Fluid ◽  
Solar Air Heater ◽  
Circular Channel ◽  
Maximum Enhancement ◽  
Performance Factor ◽  
Thermal Performance Factor ◽  
Sst Model ◽  
Inlet Length

This numerical investigation presents the effects of the position of baffles in the shape of a circle’s segment placed inside a circular channel to improve the thermal and flow performance of a solar air heater. Three different baffles’ positions with Reynolds number varying between 10,000 to 50,000 were investigated computationally. The k-omega SST model was used for solving the governing equations. Air was taken as the working fluid. Three pitch ratios (Y = 3, 4, and 5) were considered, while the height of the baffles remained fixed. The result showed an enhancement in Nusselt number, friction factor, j-factor, and thermal performance factor. Staggered exit-length baffles showed maximum enhancement in heat transfer and pressure drop, while inline inlet-length baffles showed the least enhancement. For a pitch ratio of Y = 3.0, the enhancement in all parameters was the highest, while for Y = 5.0, the enhancement in all parameters was the least. The highest thermal performance factor of 1.6 was found for SEL at Y = 3.0.

Investigations on Transient Natural Convection in Boron Nitride-Mineral Oil Nanofluid Systems

2012 ◽  
Author(s):  
Shijo Thomas ◽  
C. B. Sobhan ◽  
Jaime Taha-Tijerina ◽  
T. N. Narayanan ◽  
P. M. Ajayan
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Natural Convection ◽  
Boron Nitride ◽  
Transfer Coefficient ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Convective Heat Transfer Coefficient ◽  
Mineral Oil

Nanofluids are suspensions or colloids produced by dispersing nanoparticles in base fluids like water, oil or organic fluids, so as to improve their thermo-physical properties. Investigations reported in recent times have shown that the addition of nanoparticles significantly influence the thermophysical properties, such as the thermal conductivity, viscosity, specific heat and density of base fluids. The convective heat transfer coefficient also has shown anomalous variations, compared to those encountered in the base fluids. By careful selection of the parameters such as the concentration and the particle size, it has been possible to produce nanofluids with various properties engineered depending on the requirement. A mineral oil–boron nitride nanofluid system, where an increased thermal conductivity and a reduced electrical conductivity has been observed, is investigated in the present work to evaluate its heat transfer performance under natural convection. The modified mineral oil is produced by chemically dispersing boron nitride nanoparticles utilizing a one step method to obtain a stable suspension. The mineral oil based nanofluid is investigated under transient free convection heat transfer, by observing the temperature-time response of a lumped parameter system. The experimental study is used to estimate the time-dependent convective heat transfer coefficient. Comparisons are made with the base fluid, so that the enhancement in the heat transfer coefficient under natural convection situation can be estimated.

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