Study on the sound absorption coefficient model for porous asphalt pavements based on a CT scanning technique

In the study of the noise reduction performance of porous asphalt pavements, it is usually necessary to establish an acoustic model to develop the experiment and the theoretical analysis. However, although the traditional acoustic model is rational, there are some limitations in its accuracy and further research should be carried out. Through CT scanning, image processing and three-dimensional model building, the mesostructure characteristics of porous asphalt concrete (PAC) specimens were identified, the air-void parameters of PAC specimens were obtained, and a prediction model of the sound absorption coefficient and air-void parameters was established. In view of the difficulty involved in obtaining air-void parameters in engineering, a macroscopic prediction model of the sound absorption coefficient and air voids was established. The study showed that PAC specimens contained a large number of voids, most of which were smaller than 1 mm in equivalent diameter and were mostly distributed within 0.4-0.5 mm. Through correlation analysis, several parameters that highly correlated with the sound absorption coefficient were found out: measured air voids, reconstructed air voids, total air-void volume, average air-void volume, total air-void surface area and average air-void surface area. A prediction model for the sound absorption coefficient was established based on measured air voids, total air-void volume, average air-void volume, total air-void surface area, and average air-void surface area. In addition, a prediction model of the sound absorption coefficient and measured air voids was proposed for practical engineering purposes. The above two models can predict the sound absorption coefficient of PAC accurately, which may provide a reference in the study and application of PAC in noise reduction and impact energy absorption. (C) 2019 Elsevier Ltd. All rights reserved.