scholarly journals CFD Analysis of Enhancement of Heat Transfer of Automobile Radiator with Hybrid Nanofluid as a Coolant

2021 ◽  
Vol 9 (9) ◽  
pp. 367-376
Author(s):  
Megha Zanzote
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Nusselt Number ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Volume Flow Rate ◽  
Inlet Temperature ◽  
Hybrid Nanofluid ◽  
Cfd Analysis ◽  
Maximum Enhancement

Abstract: The performance of the radiator depends on the fluid used in it as a coolant. The conventional fluids like water, ethylene glycol used as a coolant have low thermal conductivity and are not enough for transferring the heat to more extend. Nanoparticles because of their high thermal conductivity enhances the performance of the radiator when added into the base fluid. In the present work Al2O3-CuO/ Water based hybrid nanofluid is used as a coolant for the CFD analysis of automobile radiator. Different mixing ratios (80:20, 60:40,50:50,40:60 and 20:80) of Al2O3-CuO nanoparticles are used in water with 1% volume concentration. The inlet temperature and volume flow rate of fluid are kept constant. The nanofluid with 20:80 mixing ratio of Al2O3-CuO gives maximum enhancement in heat transfer coefficient and Nusselt number than water by 72% and 65% respectively. Keywords: Coolant, Heat Transfer Coefficient, Nusselt Number, Hybrid Nanofluids, Radiator

Algal Biomass Harvesting Using Low-Grade Waste Heat: Evaluation of Overall Heat Transfer Coefficient in a Heat Exchanger

2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Temesgen Garoma ◽  
Ramin E. Yazdi
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Nusselt Number ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Waste Heat ◽  
Low Grade ◽  
Cfd Analysis ◽  
Overall Heat Transfer Coefficient ◽  
Nusselt Number Correlation

Abstract This study is part of a broader study on a novel method for harvesting algae by evaporation, and it investigated the feasibility of heating algal biomass using low-grade waste heat in a heat exchanger. Computational fluid dynamic (CFD) analysis was performed with ansysfluent, and the results were verified with experiments. The results of CFD analysis showed the overall heat transfer coefficient increased by 4, 13, and 100% as inlet gas temperature increased from 150 to 245 °C, liquid mass flow rate increased from 1.82 to 9.1 g/s, and gas mass flow increased from 2.2 to 13.2 g/s, respectively. It was also observed the overall heat transfer coefficient was not significantly affected with variations of properties of the liquid (thermal conductivity, density, and viscosity), thermal conductivity of the tube wall, and thickness of the tube banks, but it was sensitive to thermal conductivity of the gas. The experimental data were analyzed with logarithmic mean temperature difference (LMTD), number of transfer units (NTU), and Nusselt number correlation methods. There was an excellent agreement between the overall heat transfer coefficient calculated with the LMTD and NTU methods. The coefficients calculated with the LMTD method and Nusselt number correlation exhibited slight variations. This is likely because the LMTD is a theoretical method covering all experimental conditions and material properties, but Nusselt number correlation is an empirical approach based on correlations. The overall heat transfer coefficient calculated by CFD was slightly overestimated because the CFD analysis assumed complete insulation.

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%.

scholarly journals A Hybrid Nanofluid of Alumina and Tungsten Oxide for Performance Enhancement of a Parabolic Trough Collector under the Weather Conditions of Budapest

2021 ◽  
Vol 11 (11) ◽  
pp. 4946
Author(s):  
Otabeh Al-Oran ◽  
Ferenc Lezsovits
Keyword(s):  
Heat Transfer ◽  
Nusselt Number ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Flow Rate ◽  
Thermal Performance ◽  
Radiation Intensity ◽  
Hybrid Nanofluid ◽  
Intensity Level ◽  
Parabolic Trough

Recently, there has been significant interest in the thermal performance of parabolic trough collectors. They are capable of operating and generating highly variable temperature ranges, which can be used in various applications. This paper, therefore, addressed the thermal performance model of using a parabolic trough collector under the radiation intensity level found in Budapest city, as well as the effect of inserting a hybrid nanofluid as the thermal fluid. First, a new modified hybrid nanofluid of alumina and tungsten oxide-based Therminol VP1 is used to enhance the thermal properties of the thermal fluid to be more efficient to use. This enhancement is performed under various volume concentrations and has a volume fraction of 50:50. Second, in order to demonstrate the effectiveness of the thermal element, mathematical energy balance equations were solved and simulated using MATLAB Symbolic Tools. The simulation is presented for two cases: one under a constant radiation intensity and the other under the radiation intensity level of Budapest. For both cases, the results of the dimensionless Nusselt number, heat transfer coefficient, pressure drop, exergy efficiency, and energy efficiency are described. The major findings show that a volume concentration of 4% (Al2O3 and WO3) based Therminol VP1 was the most efficient volume concentrations in both cases. For the first case, the maximum enhancement of the Nusselt number and the heat transfer coefficient are 138% and 169%, respectively. These results enhanced the thermal and exergy efficiencies by 0.39% and 0.385% at a temperature 600 K, flow rate of 150 L/min, and radiation intensity of 1000 W/m2. For the second case, the maximum exergy and energy values are recorded at midday under Budapest’s summer climatic conditions and reach 32.728% and 71.255%, respectively, under the optimum temperature of 500 K and flow rate of 150 L/min. Accordingly, the mean improvement in thermal and exergy efficiencies approximately equal to 0.25% at a high concentration, regardless of the season (summer or winter).

Experimental Investigation of Heat Transfer Coefficient and Correlation Development for Subcooled Flow Boiling of Water–Ethanol Mixture in Conventional Channel

2017 ◽  
Vol 9 (4) ◽  
Author(s):  
B. G. Suhas ◽  
A. Sathyabhama
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Nusselt Number ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Flow Boiling ◽  
Inlet Temperature ◽  
Subcooled Flow Boiling ◽  
Ethanol Mixture ◽  
Subcooled Flow

In this present work, bubble dynamics of subcooled flow boiling in water–ethanol mixture is investigated through visualization using a high-speed camera in horizontal rectangular channels. The heat transfer coefficient of water–ethanol mixture during subcooled flow boiling is determined for various parameters like heat flux, mass flux, and channel inlet temperature. The effect of bubble departure diameter on heat transfer coefficient is discussed. A correlation is developed for subcooled flow boiling Nusselt number of water–ethanol mixture. The parameters considered for correlation are grouped as dimensionless numbers by Buckingham π-theorem. The present correlation is compared with the experimental data. The mean absolute error (MAE) of Nusselt number of water–ethanol mixture calculated from the experimental data and those predicted from the present correlation is 10.39%. The present correlation is also compared with the available literature correlations developed for water. The MAE of Nusselt number of water predicted from the present correlation and those predicted with Papel, Badiuzzaman, Moles–Shaw, and Baburajan correlations is 41%, 19.61%, 29.9%, and 43.1%, respectively.

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.

Energy Efficient Hybrid Nanofluids for Tubular Cooling Applications

2014 ◽  
Vol 592-594 ◽  
pp. 922-926 ◽  
Author(s):  
Devasenan Madhesh ◽  
S. Kalaiselvam
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Volume Concentration ◽  
Thermal Characteristics ◽  
Hybrid Nanofluid ◽  
Tubular Heat Exchanger ◽  
Overall Heat Transfer Coefficient ◽  
Flow Through ◽  
Hybrid Nanofluids

Analysis of heat transfer behaviour of hybrid nanofluid (HyNF) flow through the tubular heat exchanger was experimentally investigated. In this analysis the effects of thermal characteristics of forced convection, Nusselt number, Peclet number, and overall heat transfer coefficient were investigated.The nanofluid was prepared by dispersing the copper-titania hybrid nanocomposite (HyNC) in the water. The experiments were performed for various nanoparticle volume concentrations addition in the base fluid from the range of 0.1% to 1.0%. The experimental results show that the overall heat transfer coefficient was found to increases maximum by 30.4%, up to 0.7% volume concentration of HyNC.

scholarly journals Adiabatic Effectiveness and Heat Transfer Coefficient of Shaped Film Cooling Holes on a Scaled Guide Vane Pressure Side Model

2004 ◽  
Vol 10 (5) ◽  
pp. 345-354 ◽  
Author(s):  
Jan Dittmar ◽  
Achmed Schulz ◽  
Sigmar Wittig
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Film Cooling ◽  
Guide Vane ◽  
Inlet Temperature ◽  
Test Model ◽  
Pressure Side ◽  
Cooling Effectiveness ◽  
Film Cooling Effectiveness

The demand of improved thermal efficiency and high power output of modern gas turbine engines leads to extremely high turbine inlet temperature and pressure ratios. Sophisticated cooling schemes including film cooling are widely used to protect the vanes and blades of the first stages from failure and to achieve high component lifetimes. In film cooling applications, injection from discrete holes is commonly used to generate a coolant film on the blade's surface.In the present experimental study, the film cooling performance in terms of the adiabatic film cooling effectiveness and the heat transfer coefficient of two different injection configurations are investigated. Measurements have been made using a single row of fanshaped holes and a double row of cylindrical holes in staggered arrangement. A scaled test model was designed in order to simulate a realistic distribution of Reynolds number and acceleration parameter along the pressure side surface of an actual turbine guide vane. An infrared thermography measurement system is used to determine highly resolved distribution of the models surface temperature. Anin-situcalibration procedure is applied using single embedded thermocouples inside the measuring plate in order to acquire accurate local temperature data.All holes are inclined 35° with respect to the model's surface and are oriented in a streamwise direction with no compound angle applied. During the measurements, the influence of blowing ratio and mainstream turbulence level on the adiabatic film cooling effectiveness and heat transfer coefficient is investigated for both of the injection configurations.

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.

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