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ABSTRACT
The poor cracking resistance of Semi-Flexible Pavement (SFP) mixture has limited its wider application. Particularly, the dual skeletal interlocking structure makes its damage process complicated. Its fracture process is expected to change with aggregate gradation and temperature, but the relevant knowledge is very limited. Thus, this study aims to investigate the effects of the two factors on the fracture characteristics of SFP using the acoustic emission (AE) technique and X-ray computed tomography (CT) approach. SFP specimens with three gradations (the target cement grout volume is 22%, 25% and 30%, respectively) were fabricated and subjected to the split tensile tests at three different temperatures (−10°C, 10°C and 25°C). Machine learning-based techniques were applied to analyze the AE signals to improve the understanding of the mesoscale damage process. Although the analysis of macro mechanical parameters showed the diminishing effect of temperature dependency on the fracture process with an increase in cement grout volume, the effect was found to be still significant based on the mesoscale analysis. Besides, it was found that the damage process transferred from the main crack going through cement to distributed meso-cracks in asphalt and cement with the temperature increase.
Disclosure statement
No potential conflict of interest was reported by the author(s).