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

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.

1990 ◽  
Vol 57 (3) ◽  
pp. 789-791 ◽  
Author(s):  
A. Jagota ◽  
C. Y. Hui

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.


2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Pingming Huang ◽  
Yu Zhao ◽  
Yanwei Niu ◽  
Xiang Ren ◽  
Mingfeng Chang ◽  
...  

The effective thermal conductivity (ETC) of concrete is the most important parameter in determining the temperature field and thermal stresses. A 2D random polygonal aggregate model and its modified model considering porosity were established in this paper in order to partially replace the experiment for parametric analysis on the ETC of concrete and to save the experiment cost. A mesoscopic finite element method for the ETC of concrete with arbitrary gradation was also proposed. In addition, the influence factors (thermal conductivity of coarse aggregate, cement mortar, and volume fraction of coarse aggregate) of the effective thermal conductivity of concrete were analyzed. The results show that the 2D gradation curve of coarse aggregates is proved to exist, and there is a corresponding relationship between the 2D and 3D gradation curves of coarse aggregates. The effective thermal conductivity of concrete has a positive exponential relationship with the volume fraction of coarse aggregates, a positive logarithm relationship with the thermal conductivity of coarse aggregates, and a positive linear correlation with the thermal conductivity of cement mortar. The most practical way to improve the effective thermal conductivity of concrete is to increase the ETC of the cement mortar, but the most effective way is to replace the aggregate with a material with a high thermal conductivity.


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