Quantitative Characterization of 3D Road Aggregate Morphology

Abstract

This study quantitatively analyzed the shape, angularity, and roughness of road aggregate particles. A contactless three-dimensional (3D) scanning technique was used to capture the 3D coordinate data of point clouds on an aggregate surface. The data were then used to reconstruct 3D elevation digital models of aggregate particles. Six independent feature parameters were subsequently used as an evaluation index to quantitatively describe the multilevel features of the 3D morphology of road aggregates. The methods for calculating and analyzing the feature parameters on the basis of the cloud data of the aggregate scanning point were also presented. The 3D morphologies of four types of road aggregates were studied. On the basis of the results, an aggregate polishing testing system was developed, and the practicability of the 3D roughness coefficient index was demonstrated accordingly. Results show that (1) the sphericity index can describe the compactness of aggregate shape, (2) the shape factor index can describe the needle-flake properties of aggregates, (3) the ellipsoid index can evaluate the sharp edges and corners of aggregates, (4) the maximum surface curvature can be used to identify the local angular features of particles, (5) the two-dimensional roughness index can be used to analyze the anisotropic characteristics of the surface profiles of aggregates, and (6) the 3D roughness index is suitable for evaluating the roughness of aggregate surface texture at the mesoscopic level. Under the experimental conditions of this study, the shape and angular features of aggregate particles matched the requirements of road performance. This result benefitted the formation of an aggregate skeleton structure in asphalt concrete with S>0.76, SF of 0.80–1.20, and E of 0.79–0.88. The aggregate texture was uneven, and the physical adsorption between the asphalt and the aggregates on the contact surface was relatively high when JRC3D≥11.0.