Research on Asphalt Pavement Air Voids Content Estimation Utilizing GPR Considering the Surface Microscopic Structure
LING Tianqing1,2, CUI Lilong2, ZHANG Yi3, TIAN Bo1, LI Dingzhu2
1 Key Laboratory of Transport Industry of Road Structure and Material, Research Institute of Highway, Ministry of Transport, Beijing 100088, China 2 School of Civil Engineering,Chongqing Jiaotong University, Chongqing 400074, China 3 Chongqing Construction Residential Engineering Co., Ltd, Chongqing 400015, China
Abstract: Air voids content is the most important factor for asphalt pavement which have close relationship with road performance and durability. In order to predict the air voids content of asphalt layer with high accuracy, a method was proposed considering the surface microscopic structure based on ground penetrating radar (GPR). Firstly, the numerical model of porous thin layer-uniform voids layer was established based on the finite-difference time-domain (FDTD) software, and the influence of surface microscopic structure on the prediction accuracy of air voids content was quantitatively simulated. After that, the algorithm was developed to decompose the electromagnetic wave reflected from the surface and calculate the dielectric constant of the uniform voids layer based on the full waveform inversion theory. Finally, the effectivity of the algorithm was verified through FDTD numerical models and laboratory measurements. The results show that: the air voids content of the uniform layer first increased and then decreased with the increase of the air voids content of the porous thin layer, and the surface microscopic structure of the asphalt layer influenced the accuracy of air voids content prediction significantly. The reflection wave decomposed and reconstructed by the full waveform inversion method was in good correspondence with the original waveform, and the dielectric constant of the uniform layer can be calculated accurately. Compared to the traditional metal reflection method, the average error of air voids content estimation obtained from the FDTD models and laboratory measurements using the proposed method was reduced by 24.0% and 6.6%, respectively, which verified the feasibility of this method.
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2021, Vol. 35 
