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.

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.

Pool Boiling Characteristics of Metallic Nanofluids

2011 ◽  
Vol 133 (11) ◽  
Author(s):  
K. Hari Krishna ◽  
Harish Ganapathy ◽  
G. Sateesh ◽  
Sarit K. Das
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Boiling Heat Transfer ◽  
Volume Fraction ◽  
Pool Boiling ◽  
Heat Fluxes ◽  
Solid Particles ◽  
Heater Surface ◽  
Heat Transfer Characteristics ◽  
Transfer Characteristics

Nanofluids, solid-liquid suspensions with solid particles of size of the order of few nanometers, have created interest in many researchers because of their enhancement in thermal conductivity and convective heat transfer characteristics. Many studies have been done on the pool boiling characteristics of nanofluids, most of which have been with nanofluids containing oxide nanoparticles owing to the ease in their preparation. Deterioration in boiling heat transfer was observed in some studies. Metallic nanofluids having metal nanoparticles, which are known for their good heat transfer characteristics in bulk regime, reported drastic enhancement in thermal conductivity. The present paper investigates into the pool boiling characteristics of metallic nanofluids, in particular of Cu-H2O nanofluids, on flat copper heater surface. The results indicate that at comparatively low heat fluxes, there is deterioration in boiling heat transfer with very low particle volume fraction of 0.01%, and it increases with volume fraction and shows enhancement with 0.1%. However, the behavior is the other way around at high heat fluxes. The enhancement at low heat fluxes is due to the fact that the effect of formation of thin sorption layer of nanoparticles on heater surface, which causes deterioration by trapping the nucleation sites, is overshadowed by the increase in microlayer evaporation, which is due to enhancement in thermal conductivity. Same trend has been observed with variation in the surface roughness of the heater as well.

scholarly journals Buoyancy-induced convection from a pair of heated and cooled horizontal circular cylinders inside an adiabatic tilted cavity filled with alumina/water nanofluids

2019 ◽  
Vol 30 (6) ◽  
pp. 3163-3181
Author(s):  
Massimo Corcione ◽  
Emanuele Habib ◽  
Alessandro Quintino ◽  
Elisa Ricci ◽  
Vincenzo Andrea Spena
Keyword(s):  
Heat Transfer ◽  
Heat Transfer Performance ◽  
Volume Fraction ◽  
Solid Phase ◽  
Suspended Solid ◽  
Circular Cylinders ◽  
Transfer Performance ◽  
Two Phase ◽  
Content Type ◽  
Tilting Angle

Purpose This paper aims to investigate numerically buoyancy-induced convection from a pair of differentially heated horizontal circular cylinders set side by side in a nanofluid-filled adiabatic square enclosure, inclined with respect to gravity so that the heated cylinder is located below the cooled one, using a two-phase model based on the double-diffusive approach assuming that the Brownian diffusion and thermophoresis are the only slip mechanisms by which the solid phase can develop a significant relative velocity with respect to the liquid phase. Design/methodology/approach The system of the governing equations of continuity, momentum and energy for the nanofluid, and continuity for the nanoparticles, is solved by a computational code based on the SIMPLE-C algorithm. Numerical simulations are performed for Al2O3 + H2O nanofluids using the average volume fraction of the suspended solid phase, the tilting angle of the enclosure, the nanoparticle size, the average nanofluid temperature and the inter-cylinder spacing, as independent variables. Findings The main results obtained may be summarized as follows: at high temperatures, the nanofluid heat transfer performance relative to that of the pure base liquid increases with increasing the average volume fraction of the suspended solid phase, whereas at low temperatures it has a peak at an optimal particle loading; the relative heat transfer performance of the nanofluid has a peak at an optimal tilting angle of the enclosure; the relative heat transfer performance of the nanofluid increases notably as the average temperature is increased, and just moderately as inter-cylinder spacing is increased and the nanoparticle size is decreased. Originality/value The two-phase computational code used in the present study incorporates three empirical correlations for the evaluation of the effective thermal conductivity, the effective dynamic viscosity and the coefficient of thermophoretic diffusion, all based on a high number of literature experimental data.

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. .

Comparison of Single and Two-Phase Models for the Study of Mixed Convection Flows With Nanofluids

2010 ◽  
Author(s):  
Mahmood Akbari ◽  
Amin Behzadmehr ◽  
Nicolas Galanis
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Mixed Convection ◽  
Single Phase ◽  
Volume Fraction ◽  
Solid Particles ◽  
Two Phase ◽  
Prediction Ability ◽  
Numerical Predictions ◽  
Phase Models

The single phase and three different two phase models (Volume of fluid, Mixture and Eulerian) are used to analyse laminar mixed convection flow of Al2O3-water nanofluids in a horizontal tube, in order to evaluate their prediction ability. The flow is considered steady and developing. The fluid’s physical properties are temperature dependent whereas those of the solid particles are constant. A uniform heat flux is applied at the fluid-solid interface. Two different Reynolds numbers and three different volume fractions have been considered. The governing three-dimensional partial differential equations are elliptical in all directions and coupled. Predicted convective heat transfer coefficients, velocity, and temperature profiles, as well as secondary flow’s velocity vectors and temperature contours are compared at different axial positions. To validate the comparisons and verify the accuracy of the results, the numerical predictions are compared with corresponding experimental data. There are essentially no differences between the predictions of the two-phase models; however their results are significantly different from those of the single-phase approach. Two-phase model results are closer to the experimental data, but they show an unrealistic increase in heat transfer for small changes of the particle volume fraction. Hydrodynamically, the two-phase and single-phase approaches perform almost the same but their thermal predictions are quite different.

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.

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.

scholarly journals Evaluation model of the steady-state heat transfer performance of two-phase closed thermosyphons

2021 ◽  
pp. 166-166
Author(s):  
Yafeng Wu ◽  
Zhe Zhang ◽  
Wenbin Li ◽  
Daochun Xu
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Steady State ◽  
Heat Transfer Performance ◽  
Transfer Performance ◽  
Two Phase ◽  
Equivalent Thermal Conductivity ◽  
State Heat ◽  
Steady State Heat ◽  
Steady State Heat Transfer

Two-phase closed thermosyphons have good thermal conductivity and are widely used in heat transfer applications. It is essential to establish an effective method for evaluating the steady-state heat transfer performance of two-phase closed thermosyphons, as such a method can help to select appropriate designs and to improve the efficiency of these devices. In this paper, the equivalent thermal conductivity is derived by the principle of equal total thermal resistance, in which the influence of the adiabatic length is eliminated. An evaluation model of the steady-state heat transfer performance of two-phase closed thermosyphons is established. Test results of three two-phase closed thermosyphons with total lengths of 220 mm, 320 mm and 500 mm show that as the heat transfer rate increases, the equivalent thermal conductivity of these devices decreases by 28.91%, increases by 6.10% and increases by 10.02%, respectively, among which the minimum value is 831.63 W?m-1?K-1and the maximum value is 1694.19 W?m-1?K-1. The decrease (increase) in the equivalent thermal conductivity in the evaluation model indicates a decrease (increase) in the heat transfer performance. The results show that the equivalent thermal conductivity of the model can effectively evaluate the heat transfer performance of two-phase closed thermosyphons.

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%.

scholarly journals Conjugate heat transfer performance of stepped lid-driven cavity with Al2O3/water nanofluid under forced and mixed convection

2021 ◽  
Vol 3 (6) ◽  
Author(s):  
Naveen Janjanam ◽  
Rajesh Nimmagadda ◽  
Lazarus Godson Asirvatham ◽  
R. Harish ◽  
Somchai Wongwises
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Mixed Convection ◽  
Conjugate Heat Transfer ◽  
Heat Transfer Performance ◽  
Pure Water ◽  
Interface Temperature ◽  
Transfer Model ◽  
Transfer Performance ◽  
Driven Cavity

AbstractTwo-dimensional conjugate heat transfer performance of stepped lid-driven cavity was numerically investigated in the present study under forced and mixed convection in laminar regime. Pure water and Aluminium oxide (Al2O3)/water nanofluid with three different nanoparticle volume concentrations were considered. All the numerical simulations were performed in ANSYS FLUENT using homogeneous heat transfer model for Reynolds number, Re = 100 to 500 and Grashof number, Gr = 5000, 13,000 and 20,000. Effective thermal conductivity of the Al2O3/water nanofluid was evaluated by considering the Brownian motion of nanoparticles which results in 20.56% higher value for 3 vol.% Al2O3/water nanofluid in comparison with the lowest thermal conductivity value obtained in the present study. A solid region made up of silicon is present underneath the fluid region of the cavity in three geometrical configurations (forward step, backward step and no step) which results in conjugate heat transfer. For higher Re values (Re = 500), no much difference in the average Nusselt number (Nuavg) is observed between forced and mixed convection. Whereas, for Re = 100 and Gr = 20,000, Nuavg value of mixed convection is 24% higher than that of forced convection. Out of all the three configurations, at Re = 100, forward step with mixed convection results in higher heat transfer performance as the obtained interface temperature is lower than all other cases. Moreover, at Re = 500, 3 vol.% Al2O3/water nanofluid enhances the heat transfer performance by 23.63% in comparison with pure water for mixed convection with Gr = 20,000 in forward step.

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