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

Abstract

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.