scholarly journals Performance evaluation of Al2O3 nanofluid as an enhanced heat transfer fluid

2020 ◽  
Vol 12 (8) ◽  
pp. 168781402095227
Author(s):  
Minsuk Kong ◽  
Seungro Lee
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Pressure Drop ◽  
Volume Fraction ◽  
Experimental Results ◽  
Heat Transfer Fluid ◽  
Fluid Temperature ◽  
Overall Performance ◽  
C 30 ◽  
The Heat Transfer Coefficient

Thermal performance of Al2O3 nanoparticles dispersed in water was evaluated experimentally in a fully instrumented circular tube under turbulent flow conditions. Thermophysical properties of Al2O3 nanofluids at three different volumetric concentrations (0.38%, 0.81%, and 1.30%) were determined as a function of temperature. Pressure drop and heat transfer experiments were carried out at different volumetric concentrations and inlet fluid temperatures (10°C–30°C). The overall performance of the Al2O3 nanofluids was evaluated by considering both their hydraulic and heat transfer characteristics. The experimental results showed that the use of Al2O3 nanofluids increases the pressure drop by up to about 13% due to the greater viscosity. In addition, the heat transfer coefficient of nanofluids increased with the volumetric concentration by up to approximately 19% induced by the enhanced thermal conductivity. Furthermore, the experimental results indicated that the nanofluid with a volume fraction of 0.81% at the highest inlet fluid temperature increases the overall performance by up to around 8% and performs better than the other volume fractions. Enhancement in the overall performance increases with increasing inlet fluid temperature because of both the enhanced effective thermal conductivity and the decreased viscosity, which increases the energy exchange and decreases the pressure loss, respectively.

scholarly journals Thermal Conductivity of Water Based Magnetite Ferrofluids at Different Temperature for Heat Transfer Applications

2018 ◽  
Vol 280 ◽  
pp. 36-42 ◽  
Author(s):  
H. Haiza ◽  
I.I. Yaacob ◽  
Ahmad Zahirani Ahmad Azhar
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Thermal Properties ◽  
Base Fluid ◽  
Volume Fraction ◽  
Heat Transfer Fluid ◽  
Water Based ◽  
Nanoparticles Concentration ◽  
C 30 ◽  
C 50

Magnetic magnetite, Fe3O4 nanoparticles produced by Massart’s procedure were used to prepare water based magnetite, Fe3O4 ferrofluids without addition of any stabilizing agent or surfactant. The thermal properties and suspension stabilization of the ferrofluids were investigated by varying the magnetite, Fe3O4 nanoparticles concentration in the ferrofluids prepared. The thermal conductivity of water based ferrofluids prepared using five different volume fraction of magnetite, Fe3O4 suspension (0.1, 0.05, 0.02, 0.01 and 0.005) were measured at five different temperature, 25°C, 30°C, 40°C, 50°C and 60°C in order to evaluate its potential application as heat transfer fluid. The results shows that the thermal conductivity of the ferrofluids are higher than the base fluid, and the thermal conductivity of the ferrofluids increased as the magnetite concentration in the ferrofluids decreased however reached its optimum for ferrofluids prepared using 0.01 volume fraction of magnetite suspension over 0.99 volume fraction of water. Accordingly, the thermal conductivity of the ferrofluids significantly increased as the temperature increased where 49.4% enhancement with respect to water were observed at temperature 60°C.

Experimental Investigation of Single-Phase Cooling in Embedded Microchannels: 3D Manifold Heat Exchanger With R-245fa

2019 ◽  
Author(s):  
Ki Wook Jung ◽  
Hyoungsoon Lee ◽  
Chirag Kharangate ◽  
Feng Zhou ◽  
Mehdi Asheghi ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Heat Exchanger ◽  
Pressure Drop ◽  
Single Phase ◽  
Heat Fluxes ◽  
Experimental Results ◽  
Maximum Temperature ◽  
Inlet Temperature ◽  
Fluid Temperature ◽  
Ir Camera

Abstract High performance and economically viable thermal cooling solutions must be developed to reduce weight and volume, allowing for a wide-spread utilization of hybrid electric vehicles. The traditional embedded microchannel cooling heat sinks suffer from high pressure drop due to small channel dimensions and long flow paths in 2D-plane. Utilizing direct “embedded cooling” strategy in combination with top access 3D-manifold strategy reduces the pressure drop by nearly an order of magnitude. In addition, it provides more temperature uniformity across large area chips and it is less prone to flow instability in two-phase boiling heat transfer. Here, we present the experimental results for single-phase thermofluidic performance of an embedded silicon microchannel cold-plate bonded to a 3D manifold for heat fluxes up to 300 W/cm2 using single-phase R-245fa. The heat exchanger consists of a 52 mm2 heated area with 25 parallel 75 × 150 μm2 microchannels, where the fluid is distributed by a 3D-manifold with 4 micro-conduits of 700 × 250 μm2. Heat is applied to the silicon heat sink using electrical Joule-heating in a metal serpentine bridge and the heated surface temperature is monitored in real-time by Infra-red (IR) camera and electrical resistance thermometry. The experimental results for maximum and average temperatures of the chip, pressure drop, thermal resistance, average heat transfer coefficient for flow rates of 0.1, 0.2. 0.3 and 0.37 lit/min and heat fluxes from 25 to 300 W/cm2 are reported. The proposed Embedded Microchannels-3D Manifold Cooler, or EMMC, device is capable of removing 300 W/cm2 at maximum temperature 80 °C with pressure drop of less than 30 kPa, where the flow rate, inlet temperature and pressures are 0.37 lit/min, 25 °C and 350 kPa, respectively. The experimental uncertainties of the test results are estimated, and the uncertainties are the highest for heat fluxes < 50 W/cm2 due to difficulty in precisely measuring the fluid temperature at the inlet and outlet of the micro-cooler.

Finned Metal Foam Heat Sinks for Electronics Cooling in Forced Convection

2002 ◽  
Vol 124 (3) ◽  
pp. 155-163 ◽  
Author(s):  
A. Bhattacharya ◽  
R. L. Mahajan
Keyword(s):  
Heat Transfer ◽  
Porous Medium ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Transfer Coefficient ◽  
Forced Convection ◽  
Metal Foam ◽  
Experimental Results ◽  
Heat Sinks ◽  
The Heat Transfer Coefficient

In this paper, we present recent experimental results on forced convective heat transfer in novel finned metal foam heat sinks. Experiments were conducted on aluminum foams of 90 percent porosity and pore size corresponding to 5 PPI (200 PPM) and 20 PPI (800 PPM) with one, two, four and six fins, where PPI (PPM) stands for pores per inch (pores per meter) and is a measure of the pore density of the porous medium. All of these heat sinks were fabricated in-house. The forced convection results show that heat transfer is significantly enhanced when fins are incorporated in metal foam. The heat transfer coefficient increases with increase in the number of fins until adding more fins retards heat transfer due to interference of thermal boundary layers. For the 20 PPI samples, this maximum was reached for four fins. For the 5 PPI heat sinks, the trends were found to be similar to those for the 20 PPI heat sinks. However, due to larger pore sizes, the pressure drop encountered is much lower at a particular air velocity. As a result, for a given pressure drop, the heat transfer coefficient is higher compared to the 20 PPI heat sink. For example, at a Δp of 105 Pa, the heat transfer coefficients were found to be 1169W/m2-K and 995W/m2-K for the 5 PPI and 20 PPI 4-finned heat sinks, respectively. The finned metal foam heat sinks outperform the longitudinal finned and normal metal foam heat sinks by a factor between 1.5 and 2, respectively. Finally, an analytical expression is formulated based on flow through an open channel and incorporating the effects of thermal dispersion and interfacial heat transfer between the solid and fluid phases of the porous medium. The agreement of the proposed relation with the experimental results is promising.

scholarly journals Thermal-Hydraulic Performance of Graphene Nanoribbon and Silicon Carbide Nanoparticles in the Multi-Louvered Radiator for Cooling Diesel Engine

2020 ◽  
Vol 7 (1) ◽  
pp. F22-F29 ◽  
Author(s):  
E. Nogueira
Keyword(s):  
Heat Transfer ◽  
Silicon Carbide ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Analytical Solution ◽  
Transfer Coefficient ◽  
Mass Flow ◽  
Volume Fraction ◽  
Graphene Nanoribbon ◽  
The Heat Transfer Coefficient

Analytical solution for application and comparison of Graphene Nanoribbon and Silicon Carbide for thermal and hydraulic performance in flat tube Multi-Louvered Finned Radiator is presented. The base fluid is composed of pure water and ethylene glycol at a 50% volume fraction. The results were obtained for Nusselt number, convection heat transfer coefficient and pressure drop, for airflow in the radiator core and nanofluids in flat tubes. The main thermal and hydraulic parameters used are the Reynolds number, the mass flow rate, the Colburn Factor, and Friction Factor. In some situations, under analysis, the volume fraction, for Graphene Nanoribbon and Silicon Carbide, were varied. The value of the heat transfer coefficient obtained for Graphene Nanoribbon, for the volume fraction equal 0.05, is higher than twice the amount received by Silicon Carbide. The flow is laminar, for whatever the fraction value by volume of the Graphene nanoparticles when the mass flow of the nanofluid is relatively low. For turbulent flow and relatively small fractions of nanoparticles, the heat transfer coefficient is significantly high for mass flow rates of Graphene Nanoribbon. The pressure drop, for the same volume fraction of nanoparticles, is slightly higher than the pressure drop associated with Silicon Carbide. These high values for the heat transfer coefficient is a favorable result and of great practical importance, since lower values for the fraction in volume can reduce the costs of the compact heat exchanger (radiator). Keywords: analytical solution, nanofluid, compact exchanger, automotive radiator.

scholarly journals Empirical correlations to predict thermophysical and heat transfer characteristics of nanofluids

2008 ◽  
Vol 12 (2) ◽  
pp. 27-37 ◽  
Author(s):  
Vasu Velagapudi ◽  
Krishna Konijeti ◽  
Kumar Aduru
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Ethylene Glycol ◽  
Volume Fraction ◽  
Solid Particles ◽  
Engine Oil ◽  
Fluid Temperature ◽  
Flow Conditions ◽  
Thermophysical Characteristics ◽  
Laminar And Turbulent Flow

Nanofluids exhibits larger thermal conductivity due to the presence of suspended nanosized solid particles in them such as Al2O3, Cu, CuO,TiO2, etc. Varieties of models have been proposed by several authors to explain the heat transfer enhancement of fluids such as water, ethylene glycol, engine oil containing these particles. This paper presents a systematic literature survey to exploit the thermophysical characteristics of nanofluids. Based on the experimental data available in the literature empirical correlation to predict the thermal conductivity of Al2O3, Cu, CuO, and TiO2 nanoparticles with water and ethylene glycol as base fluid is developed and presented. Similarly the correlations to predict the Nusselt number under laminar and turbulent flow conditions is also developed and presented. These correlations are useful to predict the heat transfer ability of nanofluids and takes care of variations in volume fraction, nanoparticle size and fluid temperature. The improved thermophysical characteristics of a nanofluid make it excellently suitable for future heat exchange applications. .

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.

scholarly journals Non-Isothermal Hydrodynamic Characteristics of a Nanofluid in a Fin-Attached Rotating Tube Bundle

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1153
Author(s):  
Mashhour A. Alazwari ◽  
Mohammad Reza Safaei
Keyword(s):  
Heat Transfer ◽  
Reynolds Number ◽  
Heat Transfer Coefficient ◽  
Pressure Drop ◽  
Transfer Coefficient ◽  
Rotation Speed ◽  
Tube Bundle ◽  
Heat Transfer Fluid ◽  
Hydrodynamic Characteristics ◽  
The Heat Transfer Coefficient

In the present study, a novel configuration of a rotating tube bundle was simulated under non-isothermal hydrodynamic conditions using a mixture model. Eight fins were considered in this study, which targeted the hydrodynamics of the system. An aqueous copper nanofluid was used as the heat transfer fluid. Various operating factors, such as rotation speed (up to 500 rad/s), Reynolds number (10–80), and concentration of the nanofluid (0.0–4.0%) were applied, and the performance of the microchannel heat exchanger was assessed. It was found that the heat transfer coefficient of the system could be enhanced by increasing the Reynolds number, the concentration of the nanofluid, and the rotation speed. The maximum enhancement in the heat transfer coefficient (HTC) was 258% after adding a 4% volumetric nanoparticle concentration to the base fluid and increasing Re from 10 to 80 and ω from 0 to 500 rad/s. Furthermore, at Re = 80 and ω = 500 rad/s, the HTC values measured for the nanofluid were 42.3% higher than those calculated for water, showing the nanoparticles' positive impact on the heat transfer paradigm. Moreover, it was identified that copper nanoparticles' presence had no significant effect on the system's pressure drop. This was attributed to the interaction of the fluid flow and circulated flow around the tubes. Finally, the heat transfer coefficient and pressure drop had no considerable changes when augmenting the rotation speed at high Reynolds numbers.

scholarly journals Thermal and Hydraulic Performance of CuO/Water Nanofluids: A Review

Micromachines ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 416 ◽  
Author(s):  
Mohammad Yacoub Al Shdaifat ◽  
Rozli Zulkifli ◽  
Kamaruzzaman Sopian ◽  
Abeer Adel Salih
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Particle Size ◽  
Volume Fraction ◽  
Hydraulic Performance ◽  
Theoretical Studies ◽  
Pumping Power ◽  
Large Particle Size ◽  
Experimental And Theoretical Studies ◽  
The Heat Transfer Coefficient

This paper discusses the behaviour of different thermophysical properties of CuO water-based nanofluids, including the thermal and hydraulic performance and pumping power. Different experimental and theoretical studies that investigated each property of CuO/water in terms of thermal and fluid mechanics are reviewed. Classical theories cannot describe the thermal conductivity and viscosity. The concentration, material, and size of nanoparticles have important roles in the heat transfer coefficient of CuO/water nanofluids. Thermal conductivity increases with large particle size, whereas viscosity increases with small particle size. The Nusselt number depends on the flow rate and volume fraction of nanoparticles. The causes for these behaviour are discussed. The magnitude of heat transfer rate is influenced by the use of CuO/water nanofluids. The use of CuO/water nanofluids has many issues and challenges that need to be classified through additional studies.

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.

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