The Influence of Thermal Radiation on Effective Thermal Conductivity in Porous Material

2016 ◽  
Vol 65 (6-7) ◽  
pp. 237-243 ◽  
Author(s):  
Lianhua He ◽  
Meijie Zhang ◽  
Huazhi Gu ◽  
Ao Huang
2003 ◽  
Vol 175 (5) ◽  
pp. 873-900 ◽  
Author(s):  
M. P. Järvinen* ◽  
R. Zevenhoven ◽  
E. K. Vakkilainen ◽  
M. Forssén

2012 ◽  
Vol 557-559 ◽  
pp. 2388-2395
Author(s):  
Shan Qi Liu ◽  
Yong Bing Li ◽  
Xu Yao Liu ◽  
Bo Jing Zhu ◽  
Hui Quan Tian ◽  
...  

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.


2009 ◽  
Vol 20 (04) ◽  
pp. 513-526 ◽  
Author(s):  
SHOUJU LI ◽  
YUEFANG WANG ◽  
YINGXI LIU ◽  
WEI SUN

The relationship between thermal conductivity of porous material and fractal dimension is numerically simulated by using the finite element method. The solid matrix and pore space are generated randomly according to material porosity. Material parameters and element properties are changed by using ANSYS parameter design language. The effective thermal conductivity is derived according to thermal flux through some sections computed by FEM and Fourier heat transform law. The investigation shows that the effective thermal conductivity decreases with increasing porosity. The effective thermal conductivity will decrease exponentially with increasing fractal dimension of porosity space and increase exponentially with increasing fractal dimension of solid matrix.


2017 ◽  
Vol 140 (4) ◽  
Author(s):  
Hao Wu ◽  
Nan Gui ◽  
Xingtuan Yang ◽  
Jiyuan Tu ◽  
Shengyao Jiang

In nuclear packed pebble beds, it is a fundamental task to model effective thermal conductivity (ETC) of thermal radiation. Based on the effective heat transfer cells of structured packing, a short-range radiation model (SRM) and a subcell radiation model (SCM) are applied to obtain analytical results of ETC. It is shown that the SRM of present effective heat transfer cells are in good agreement with the numerical simulations of random packing and it is only slightly higher than empirical correlations when temperature exceeds 1200 °C. In order to develop a generic theoretical approach of modeling ETC, the subcell radiation model is presented and in good agreement with Kunii–Smith correlation, especially at very high temperature ranges (over 1500 °C). Based on SCM, one-dimensional (1D) radial heat transfer model is applied in the analysis of the HTTU experiments. The results of ETC and radial temperature distribution are in good agreement with the experimental data.


2011 ◽  
Vol 48 (4) ◽  
pp. 532-542 ◽  
Author(s):  
Marie-Hélène Fillion ◽  
Jean Côté ◽  
Jean-Marie Konrad

This paper presents an experimental study on thermal radiation and the thermal conductivity of rock-fill materials using a 1 m × 1 m × 1 m heat transfer cell. Testing temperatures are applied by temperature-controlled fluid circulation at the top and bottom of the sample. Heat flux and temperature profiles are measured to establish the effective thermal conductivity λe, which includes contributions from both conduction and radiation heat transfer mechanisms. The materials studied had an equivalent particle size (d10) ranging from 90 to 100 mm and porosity (n) ranging from 0.37 to 0.41. The experimental results showed that thermal radiation greatly affects the effective thermal conductivity of materials with λe values ranging from 0.71 to 1.02 W·m−1·K−1, compared with a typical value of 0.36 W·m−1·K−1 for conduction alone. As expected, the effective thermal conductivity increased with particle size. An effective thermal conductivity model has been proposed, and predictions have been successfully compared with the experimental results. Radiation heat transfer becomes significant for d10 higher than 10 mm and predominant at values higher than 90 mm. The results of the study also suggest that the cooling potential of convection embankments used to preserve permafrost conditions may not be as efficient as expected because of ignored radiation effects.


Author(s):  
Xinming Zhang ◽  
Qinghua Chen ◽  
Danling Zeng

Graphite foam is a new material for effective heat conduction, which possesses exceedingly good thermal physical properties, thus the investigation on it has absorbed wide attention of scientists and engineers. By using experimental method such a material was obtained in our lab, and the factors which influence the micro-structure of the material was preliminary discussed based on our experiments. However, the main focus of the present paper is placed on the determination of the effective thermal conductivity of the material. Firstly, in accordance with the microscopic structure of the material, a simplified geometric model was constructed. Based on it a heat conduction unit cell was proposed to calculate the effective thermal conductivity of the porous material. Then, a geometric transformation was carried out to transit the original simple model to the real fractal one. The effective thermal conductivity λ' and its averaged value λ'm for the bulk porous material were derived. Examples were provided to show the computational procedure and to confirm the availability of the method proposed. The influence factors on λm. in the fractal model were also discussed in detail.


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