Brownian-Motion-Based Convective-Conductive Model for the Effective Thermal Conductivity of Nanofluids

2005 ◽  
Vol 128 (6) ◽  
pp. 588-595 ◽  
Author(s):  
Ravi Prasher ◽  
Prajesh Bhattacharya ◽  
Patrick E. Phelan
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Particle Sizes ◽  
Brownian Movement ◽  
Liquid Temperature ◽  
Interfacial Resistance ◽  
Conduction Model ◽  
Order Of Magnitude ◽  
Base Liquid ◽  
Good Agreement

Here we show through an order-of-magnitude analysis that the enhancement in the effective thermal conductivity of nanofluids is due mainly to the localized convection caused by the Brownian movement of the nanoparticles. We also introduce a convective-conductive model which accurately captures the effects of particle size, choice of base liquid, thermal interfacial resistance between the particles and liquid, temperature, etc. This model is a combination of the Maxwell-Garnett (MG) conduction model and the convection caused by the Brownian movement of the nanoparticles, and reduces to the MG model for large particle sizes. The model is in good agreement with data on water, ethylene glycol, and oil-based nanofluids, and shows that the lighter the nanoparticles, the greater the convection effect in the liquid, regardless of the thermal conductivity of the nanoparticles.

Brownian-Motion-Based Convective-Conductive Model for the Thermal Conductivity of Nanofluids

2005 ◽  
Author(s):  
Ravi Prasher
Keyword(s):  
Thermal Conductivity ◽  
Research Community ◽  
Particle Sizes ◽  
Brownian Movement ◽  
Liquid Temperature ◽  
Interfacial Resistance ◽  
Conduction Model ◽  
The Past ◽  
Order Of Magnitude ◽  
Base Liquid

The research community has been perplexed for the past five years with the unusually high effective thermal conductivity of nanofluids. Although various mechanisms and models have been proposed in the literature to explain the high conductivity of these nanofluids, no concrete conclusions have been reached. Through an order-of-magnitude analysis of various possible mechanisms, we show that convection caused by the Brownian movement of these nanoparticles is primarily responsible for the enhancement in the thermal conductivity of such colloidal nanofluids. We also introduce a convective-conductive model which accurately captures the effects of particle size, choice of base liquid, thermal interfacial resistance between the particles and liquid, temperature, etc. This model is a combination of the Maxwell-Garnett (MG) conduction model and the convection caused by the Brownian movement of the nanoparticles, and reduces to the MG model for large particle sizes.

Contact Resistance Measurement and Its Effect on the Thermal Conductivity of Packed Sphere Systems

2004 ◽  
Vol 126 (6) ◽  
pp. 886-895 ◽  
Author(s):  
W. W. M. Siu ◽  
S. H.-K. Lee
Keyword(s):  
Thermal Conductivity ◽  
Contact Resistance ◽  
Effective Thermal Conductivity ◽  
Transient Behavior ◽  
Contact Radius ◽  
Transient Temperature ◽  
Interfacial Resistance ◽  
Conduction Model ◽  
Scale Modeling ◽  
Packed Sphere

There has been a growing interest in porous systems with a smaller length-scale modeling requirement on the order of each particle, where the existing tools tend to be inadequate. To address this, a Discrete Conduction Model was recently proposed to allow for the transient temperature calculation of 3D random packed-sphere systems for various microstructures. Since many of the motivating applications involve contacting spheres and since there has been a limited number of contact-resistance studies on spheres undergoing elastic deformation, the objective of this study is to obtain measurements of the contact resistances between metallic spheres in elastic contact, as well as to quantify their influence on the effective thermal conductivity. To accomplish this, an experiment was constructed utilizing air and interfacial resistance to replace the functions of the guard heater and vacuum chamber, and in so doing, enabled transient observations. The overall uncertainty was estimated to be ±6%, and the results were benchmarked against available data. A correlation was obtained relating the contact resistance with the contact radius, and results showed the contact resistance to have minimal transient behavior. The results also showed that the neglect of contact resistance could incur an error in the effective thermal conductivity calculation as large as 800%, and a guideline was presented under which the effect of the contact resistance may be ignored. A correlation accounting for the effect of contact resistance on the effective thermal conductivity was also presented.

Effective Thermal Conductvity of Three-Phase Soils

2012 ◽  
Author(s):  
Fabio Gori ◽  
Sandra Corasaniti
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Heat Fluxes ◽  
Water Volume ◽  
Two Phase ◽  
Empirical Constant ◽  
Three Phase ◽  
Theoretical Predictions ◽  
Porosity Ratio ◽  
Good Agreement

The aim of the present paper is to determine the effective thermal conductivity of three-phase soils, made of a quasi-spherical solid grain, and surrounded by two phase, which can be water and air or water and ice. The effective thermal conductivity is obtained theoretically by integrating the conduction equation under the thermal distribution of parallel heat fluxes in steady-state. The effective thermal conductivity is evaluated at a given degree of porosity (ratio between the void volume and the total one) and different degrees of saturation (ratio between the water volume and the void one) from dryness up to saturation. Comparisons between experimental data and theoretical predictions confirm that the present model can predict the effective thermal conductivity with a fairly good agreement without using any empirical constant.

THE ATTENUATION OF SECOND SOUND IN LIQUID HELIUM II ABOVE 1°K.

1954 ◽  
Vol 32 (6) ◽  
pp. 381-392 ◽  
Author(s):  
K. R. Atkins ◽  
K. H. Hart
Keyword(s):  
Thermal Conductivity ◽  
Continuous Wave ◽  
Pulse Length ◽  
Boundary Effects ◽  
Second Sound ◽  
Sound Beam ◽  
Helium Ii ◽  
Viscosity Effects ◽  
Order Of Magnitude ◽  
Good Agreement

The second sound was in the form of a pulsed continuous wave with a pulse length of 1 to 2 msec, and a carrier frequency of 10 or 20 kc./s. The change in amplitude of the pulse was measured as the distance between the transmitter and the receiver was varied. To avoid boundary effects, no propagation tube was used and allowance had to be made for the spreading of the second sound beam. The attenuation was found to increase with increasing second sound amplitude. The attenuation extrapolated to zero amplitude had a finite value which increased rapidly as the temperature was lowered towards 1°K. Its order of magnitude was too large to be explained by viscosity effects, but was in good agreement with a thermal conductivity effect predicted by Khalatnikov.

scholarly journals Modelling of Effective Thermal Conductivity of Composites Filled with Core-Shell Fillers

Materials ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 5480
Author(s):  
Jan Czyzewski ◽  
Andrzej Rybak ◽  
Karolina Gaska ◽  
Robert Sekula ◽  
Czeslaw Kapusta
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Thermal Conduction ◽  
Hexagonal Boron Nitride ◽  
Core Material ◽  
Core Shell ◽  
Glass Spheres ◽  
Materials Modelling ◽  
Properties Of Materials ◽  
Good Agreement

An effective model to calculate thermal conductivity of polymer composites using core-shell fillers is presented, wherein a core material of filler grains is covered by a layer of a high-thermal-conductivity (HTC) material. Such fillers can provide a significant increase of the composite thermal conductivity by an addition of a small amount of the HTC material. The model employs the Lewis-Nielsen formula describing filled systems. The effective thermal conductivity of the core-shell filler grains is calculated using the Russel model for porous materials. Modelling results are compared with recent measurements made on composites filled with cellulose microbeads coated with hexagonal boron nitride (h-BN) platelets and good agreement is demonstrated. Comparison with measurements made on epoxy composites, using silver-coated glass spheres as a filler, is also provided. It is demonstrated how the modelling procedure can improve understanding of properties of materials and structures used and mechanisms of thermal conduction within the composite.

Effective Thermal Conductivity of Coal Ash Deposits at Moderate to High Temperatures

1987 ◽  
Vol 109 (2) ◽  
pp. 215-221 ◽  
Author(s):  
D. W. Anderson ◽  
R. Viskanta ◽  
F. P. Incropera
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Thermal History ◽  
Coal Ash ◽  
Physical Structure ◽  
Conductivity Measurements ◽  
Wide Range ◽  
Particulate Form ◽  
Order Of Magnitude ◽  
Deposit Structure

The effective thermal conductivity of coal ash deposits strongly influences heat transfer in pulverized coal-fired boilers. In this study thermal conductivity measurements were performed over a wide range of temperatures for fly ash, slagging deposits, and fouling deposits. The effects of ash particle size, thermal history, and physical structure of the deposit are discussed. Thermal history and deposit structure were observed to have the greatest influence on the local thermal conductivty, which increased by an order of magnitude with particle melting. Conductivities for solid-porous deposits were twice those of the same sample in particulate form.

Thermal Conductivity Affected by Temperature and Particle Size in Al2O3-Water Nanofluids

2011 ◽  
Author(s):  
D. Kwek ◽  
A. Crivoi ◽  
Fei Duan
Keyword(s):  
Thermal Conductivity ◽  
Particle Size ◽  
Effective Thermal Conductivity ◽  
Experimental Results ◽  
Al2o3 Nanoparticles ◽  
Particle Sizes ◽  
Transient Hot Wire ◽  
Hot Wire ◽  
Nanoparticle Concentration ◽  
Wire Method

The effective thermal conductivity of Al2O3-water nanofluids has been measured using a transient hot wire method. Experimental results demonstrate that the thermal conductivity of Al2O3 nanofluids increases linearly with increasing nanoparticle concentration. Adding 5 vol % of Al2O3 nanoparticles in water increases the effective thermal conductivity of the nanofluids by 20%. Thermal conductivity of Al2O3 nanofluids increases with an increase of temperature. The enhancement is around 1.7% at 15 °C in comparison with around 16% at 55 °C in a 1 vol % nanofluid. The particle size is another important parameter for the effective thermal conductivity. The increase of thermal conductivity reduces from 30% to 10% as the particle sizes increase from 10 nm to 35 nm. The increase of the effective thermal conductivity starts as the particle size increases above 35 nm, reaching about 27.5% in the nanofluid with the particle size at 150 nm.

Numerical Simulation on the Effective Thermal Conductivity of Porous Material

2012 ◽  
Vol 557-559 ◽  
pp. 2388-2395
Author(s):  
Shan Qi Liu ◽  
Yong Bing Li ◽  
Xu Yao Liu ◽  
Bo Jing Zhu ◽  
Hui Quan Tian ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Numerical Simulation ◽  
Porous Material ◽  
Effective Thermal Conductivity ◽  
Random Distribution ◽  
Simulation Method ◽  
Solid Skeleton ◽  
Material Models ◽  
Application Prospects ◽  
Good Agreement

The thermal conductivity of porous material is an important basic parameter, but it is not easy to study, due to the complexity of the structure of porous material. In the present work, we show a numerical simulation method to study the thermal conductivity of the porous material. We generate 200 material models with random distribution of solid skeleton and air for a fixed porosity, then we get the effective thermal conductivity of the porous material by Monte Carlo statistical analysis. The results are in good agreement with the previous empirical formula. The numerical results show that the effective thermal conductivity of porous material depends on the thermophysical properties of solid skeleton and air, the pore distribution and pore structure, the numerical error decreases with the increase in the number of grids, this finite element method can be used to estimate the effective thermal conductivity of composites and maybe has broad application prospects in terms of computing the effective thermal conductivity and other physical properties of composite material with known components.

scholarly journals Experimental Testing of Thermo Physical Properties of Novel Water and Glycerol Mixture-Based Silica Nano Fluids

2019 ◽  
Vol 8 (2) ◽  
pp. 5299-5305 ◽  
Keyword(s):  
Thermal Conductivity ◽  
Thermal Properties ◽  
Experimental Testing ◽  
Optimum Ratio ◽  
Glycerol Water ◽  
Mixture Ratio ◽  
Thermo Physical Properties ◽  
Nano Fluids ◽  
Base Liquid ◽  
Good Agreement

The main objectives of the present work embrace the preparation of cobalt nanofluids, amalgamation of silica nanofluid with optimum glycerol-water (G-W) mixture ratio and estimation of its thermal properties like thermal conductivity and viscosity experimentally. Optimum ratio of base liquid (G-W mixture) was selected for the preparation of nanofluids. Subsequently, thermophysical properties of the hybrid nano mixture have been determined experimentally using KD2Pro thermal properties analyzer and Brookfield viscometer at different volume concentrations of silica nanofluids. Attained results reveal that, the dynamic viscosity and thermal conductivity are found to be growing remarkably with the increase in nanoparticle weight concentration in base liquid mixture. The results are found to be in good agreement with the available data from the literature.

Computation of Effective Thermal Conductivity of Powders for Selective Laser Sintering Simulations

2016 ◽  
Vol 138 (8) ◽  
Author(s):  
Daniel Moser ◽  
Sreekanth Pannala ◽  
Jayathi Murthy
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Steady State ◽  
Effective Thermal Conductivity ◽  
High Temperatures ◽  
Selective Laser Sintering ◽  
Laser Sintering ◽  
Spherical Particles ◽  
View Factor ◽  
Conduction Model

In this work, a discrete element model (DEM) is developed and implemented in the open source flow solver MFiX to simulate the effective thermal conductivity of powder beds for selective laser sintering (SLS) applications, considering scenarios common in SLS such as thin beds, high temperatures, and degrees of powder consolidation. Random particle packing structures of spherical particles are generated and heat transfer between the particles is calculated. A particle–particle contact conduction model, a particle–fluid–particle conduction model, and a view factor radiation model using ray-tracing for calculation of view factors and assuming optically thick particles are used. A nonlinear solver is used to solve for the particle temperatures that drive the net heat transfer to zero for a steady state solution. The effective thermal conductivity is then calculated from the steady state temperature distribution. Results are compared against previously published experimental measurements for powder beds and good agreement is obtained. Results are developed for the impacts of very high temperatures, finite bed depth, consolidation, Young's modulus, emissivity, gas conductivity, and polydispersity on effective thermal conductivity. Emphasis is placed on uncertainty quantification in the predicted thermal conductivity resulting from uncertain inputs. This allows SLS practitioners to control the inputs to which the thermal response of the process is most sensitive.

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