Study on stochastic behavior of particle system in hot mix asphalt mixture from a meso-structural perspective

Abstract

The variability and uncertainty bring great trouble to the application and in-depth research of asphalt mixture. This study aimed to detect the microstructural differences between the asphalt specimens after fixing the experimental and environmental inputs. To this end, the digital image correlation (DIC) method was utilized to propose reliable skeletal and disruptive meso-parameters. Besides, the close packing theory and digital sieving technique were combined to classify the internal particles of the mixture structure. Afterward, the stochastic behaviors of the particle systems containing the dominant aggregate size range (DASR) and interstitial component (IC) aggregates were thoroughly discussed. Finally, the disruption effect of IC on the skeletal structure was also investigated. The analysis results show that the microstructure of the asphalt mixture was a typical random system with a great deal of contingency. The aggregate contact index (ACI) was the most variable among the overall skeletal parameters, with a variation coefficient (COV) of 13.24 %. Besides, almost all the microstructural indexes indicated that about 4% of the specimens in parallel tests showed significant variability behavior, e.g., Na,13.2 > Na,16.0. Besides, the microstructural uncertainty of the minority class, e.g., the 16-mm aggregates with a 4% ∼7% COV higher than the other classes, was particularly significant. Finally, the interference effect was proven to focus on the contact behavior of DASR particles, thus damaging the DASR-based system. This study not only emphasizes the impact of variability but provides implications for controlling the performance of asphalt pavement.