ABSTRACT
X-ray computed tomography (CT) as a non-destructive testing method has been used to evaluate the air voids and void-related distresses in asphalt mixtures. To evaluate the air void development in asphalt mixtures under loading, this study proposed a volume-equivalent maximal ball model based on CT to characterise the changes of void connectivity. The void distribution and shape features were described using the variation coefficient of modified annular-sector segmentation, positional eccentricity ratio, and sphericity. The results indicate that voids are relatively heterogeneous and discrete in stone mastic asphalt (SMA-13) mixture compared with dense-graded asphalt concrete (AC-13), particularly for those with volume smaller than 0.01 mm3. The void connectivity and distribution in SMA-13 seem to be more susceptible to load as its coarse aggregates tend to shift their positions during deformation. Rutting reduces the vertical inhomogeneity of AC-13 but increases that of SMA-13. Moreover, loading complicates the void geometry of AC-13 whereas the opposite is true for SMA-13, foreboding that SMA mixtures maintain the potential to resist rutting failure after 1 h of loading compared to AC types. In general, the topological characteristics of air voids within asphalt mixtures and their dynamic response during permanent deformation are principally dependent on mixture gradations.
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Jinzhou Liu
Jinzhou Liu, Ph.D. Candidate. He is presently studying for a Ph.D. degree at Southeast University. His research involves multiscale rutting failure mechanism and characterisation of air void mesostructure of asphalt mixture using computational mechanics and experimental methods.
Yuchen Wang
Yuchen Wang, Ph.D. Candidate. She is currently pursuing a Ph.D. degree at Southeast University. Her research interests include simulation and characterisation of air voids within asphalt mixture using discrete element simulation method and digital image processing technology.
Shuyi Wang
Shuyi Wang, Ph.D. Candidate. He is presently studying for a Ph.D. degree at Southeast University. His research involves the three-dimensional characterisation of air voids within asphalt mixtures during freezing and thawing cycles.
Qi Liu
Qi Liu, Ph.D. Candidate. He is presently studying for a Ph.D. degree at Southeast University. His research involves simulation and characterisation of asphalt gradient aging, multiscale modelling, and evaluation of asphalt mixtures.
Bin Yu
Bin Yu, a professor in the School of Transportation at Southeast University, received his PhD. degree in civil engineering from the University of South Florida. His research involves functional road material design and performance evaluation, life cycle modelling and environmental impact analysis, and optimisation of road maintenance decisions based on data mining and artificial intelligence.
Qian Wang
Qian Wang, Ph.D. Candidate. He is presently studying for a Ph.D. degree at the University of New South Wales. His research involves characterisation of microstructure within asphalt mixture using digital image processing technology.