Digital 3D morphological features and distribution of asphalt coarse aggregate

Abstract:

In order to accurately analyze the morphological characteristics and distribution properties of aggregates in the mixture, and to have a more comprehensive, in-depth, and specific understanding of aggregates, CT scanning, digital image processing, and three-dimensional geometric reconstruction technologies were used to reconstruct the real shape of aggregate particles. Five morphological characteristic parameters of aggregates were proposed, and a digital evaluation and experimental analysis were conducted on the morphological characteristics of three aggregates. The accuracy of the digital reconstruction method was validated and the morphological distribution characteristics of aggregate particles were analyzed. Additionally, the Pearson correlation method was utilized to analyze the correlations among the morphological parameters. The study demonstrates that the use of CT scanning technology and digital reconstruction technology can accurately restore the morphological characteristics of aggregate particles and obtain morphological parameters. There are significant distribution characteristics of the morphology of different particle sizes of the same aggregate. The three-dimensional needle-like index and three-dimensional texture index show little variation across different particle sizes. As the particle size increases, the variability of the morphology parameter values for aggregates decreases. The overall three-dimensional texture index follows a power-law distribution, and the complexity gradually decreases with the increase of particle size. Additionally, as the particle size increases, the three-dimensional edge angle gradually stabilizes. There is a strong negative correlation between three-dimensional edge angle and solid moment degree, as well as between solid sphericity and three-dimensional edge angle. Conversely, there is a strong positive correlation between sphericity of the actual shape and the three-dimensional texture index. Digital 3D reconstruction can accurately and comprehensively describes and analyzes the morphology and distribution characteristics of aggregates.