The Effective Thermal Conductivity of a Packing of Spheres

1990 ◽  
Vol 57 (3) ◽  
pp. 789-791 ◽  
Author(s):  
A. Jagota ◽  
C. Y. Hui
Keyword(s):  
Thermal Conductivity ◽  
Temperature Field ◽  
Closed Form ◽  
Effective Thermal Conductivity ◽  
Granular Materials ◽  
Upper Bound ◽  
Random Packing ◽  
Fabric Tensor ◽  
Mean Temperature

The anisotropic effective thermal conductivity of a random packing of spheres is derived. The conductivity is closely related to the fabric tensor of the theory of granular materials. The derivation involves a mean temperature field assumption which is shown to render the model an upper bound. Closed-form expressions for the conductivity are obtained in the isotropic and axisymmetric cases.

Evaluation of effective thermal conductivity of unsaturated granular materials using random network model

Geothermics ◽  
2017 ◽  
Vol 67 ◽  
pp. 76-85 ◽  
Author(s):  
Chulho Lee ◽  
Li Zhuang ◽  
Dongseop Lee ◽  
Seokjae Lee ◽  
In-Mo Lee ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Effective Thermal Conductivity ◽  
Granular Materials ◽  
Network Model ◽  
Random Network

Effective Thermal Conductivity of Composites Reinforced with Curvilinearly Anisotropic Inclusions with Kapitza Contact Resistance

2006 ◽  
Vol 306-308 ◽  
pp. 775-780
Author(s):  
Tung Yang Chen
Keyword(s):  
Thermal Conductivity ◽  
Contact Resistance ◽  
Closed Form ◽  
Effective Thermal Conductivity ◽  
Thermal Contact Resistance ◽  
Thermal Contact ◽  
Transversely Isotropic ◽  
Closed Form Expression ◽  
Form Expression ◽  
Micromechanical Models

Effective thermal conductivities of composites consisting of curvilinearly anisotropic inclusions with Kapitza thermal contact resistance between the constituents are considered. We show that the effect of these curvilinearly anisotropic inclusions can be exactly simulated by certain equivalent isotropic or transversely isotropic inclusions. Three different micromechanical models are employed to estimate the effective thermal conductivity of the composite. Interestingly, all these methods result in the same simple, closed-form expression.

Effective Thermal Conductivity of Submicron Powders: A Numerical Study

2016 ◽  
Vol 846 ◽  
pp. 500-505
Author(s):  
Wei Jing Dai ◽  
Yi Xiang Gan ◽  
Dorian Hanaor
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Thermal Resistance ◽  
Effective Thermal Conductivity ◽  
Granular Materials ◽  
Gas Phase ◽  
Numerical Study ◽  
Transfer Model ◽  
Size Of Particles ◽  
Contact Unit

Effective thermal conductivity is an important property of granular materials in engineering applications and industrial processes, including the blending and mixing of powders, sintering of ceramics and refractory metals, and electrochemical interactions in fuel cells and Li-ion batteries. The thermo-mechanical properties of granular materials with macroscopic particle sizes (above 1 mm) have been investigated experimentally and theoretically, but knowledge remains limited for materials consisting of micro/nanosized grains. In this work we study the effective thermal conductivity of micro/nanopowders under varying conditions of mechanical stress and gas pressure via the discrete thermal resistance method. In this proposed method, a unit cell of contact structure is regarded as one thermal resistor. Thermal transport between two contacting particles and through the gas phase (including conduction in the gas phase and heat transfer of solid-gas interfaces) are the main mechanisms. Due to the small size of particles, the gas phase is limited to a small volume and a simplified gas heat transfer model is applied considering the Knudsen number. During loading, changes in the gas volume and the contact area between particles are simulated by the finite element method. The thermal resistance of one contact unit is calculated through the combination of the heat transfer mechanisms. A simplified relationship between effective thermal conductivity and loading pressure can be obtained by integrating the contact units of the compacted powders.

scholarly journals Investigation of Effective Thermal Conductivity for Ordered and Randomly Packed Bed with Thermal Resistance Network Method

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1666 ◽  
Author(s):  
Jian Yang ◽  
Yingxue Hu ◽  
Qiuwang Wang
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Thermal Resistance ◽  
Effective Thermal Conductivity ◽  
Packed Bed ◽  
Random Packing ◽  
Packing Factor ◽  
Resistance Network ◽  
Network Method ◽  
Thermal Conductivities

In the present paper, the effective thermal conductivities of Li4SiO4-packed beds with both ordered and random packing structures were investigated using thermal resistance network methods based on both an Ohm’s law model and a Kirchhoff’s law model. The calculation results were also validated and compared with the numerical and experimental results. Firstly, it is proved that the thermal resistance network method based on the Kirchhoff’s law model proposed in the present study is reliable and accurate for prediction of effective thermal conductivities in a Li4SiO4-packed bed, while the results calculated with the Ohm’s law model underestimate both ordered and random packings. Therefore, when establishing a thermal resistance network, the thermal resistances should be connected along the main heat transfer direction and other heat transfer directions as well in the packing unit. Otherwise, both the total heat flux and effective thermal conductivity in the packing unit will be underestimated. Secondly, it is found that the effect of the packing factor is remarkable. The effective thermal conductivity of a packed bed would increase as the packing factor increases. Compared with random packing at similar packing factor, the effective thermal conductivity of packed bed would be further improved with an ordered packing method.

scholarly journals Combined Prediction Method for Thermal Conductivity of Asphalt Concrete Based on Meso-Structure and Renormalization Technology

2022 ◽  
Vol 12 (2) ◽  
pp. 857
Author(s):  
Jiaqi Chen ◽  
Xingzao Chen ◽  
Hancheng Dan ◽  
Lanchun Zhang
Keyword(s):  
Thermal Conductivity ◽  
Temperature Field ◽  
Effective Thermal Conductivity ◽  
Asphalt Concrete ◽  
Coarse Aggregate ◽  
Steel Fiber ◽  
Thermal Environment ◽  
Orientation Angle ◽  
Prediction Method ◽  
Pavement Temperature

Pavement temperature field affects pavement service life and the thermal environment the near road surface; thus, is important for sustainable pavement design. This paper developed a combined prediction method for the thermal conductivity of asphalt concrete based on meso-structure and renormalization technology, which is critical for determining the pavement temperature field. The accuracy of the combined prediction method was verified by laboratory experiments. Using the tested and proven model, the effect of coarse aggregate type, shape, content, spatial orientation, air void of asphalt concrete, and steel fiber on the effective thermal conductivity was analyzed. The analysis results show that the orientation angle and aspect ratio of the aggregate have a combined effect on thermal conductivity. In general, when the aggregate orientation is parallel with the heat conduction direction, the effective thermal conductivity of asphalt concrete in that direction tends to be greater. The effective thermal conductivity of asphalt concrete decreases with the decrease of coarse aggregate content or steel fiber content or with the increase of porosity, and it increases with the increase of the effective thermal conductivity of coarse aggregate.

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