Analysis of aggregate shape characteristics and its relationship to hot mix asphalt performance

This paper presents the development of a methodology for the classification of aggregates based on their shape, angularity and texture characteristics. This methodology utilizes the Aggregate Imaging System (AIMS) to measure aggregate characteristics, and the clustering statistical method to analyze the measurements. The outcome of this analysis method is the percentage of aggregate particles that belong to groups or clusters that have statistically different characteristics. The Categorical Counts method is employed in this study for comparing the characteristics of different aggregate samples. This method detects not only the statistical difference between aggregate samples, but it is also capable of identifying differences in each of the clusters. The quality of AIMS measurements is evaluated through the analysis of repeatability and reproducibility. Finally statistical analysis was conducted to determine whether aggregate properties are significant enough to influence the measured mechanical properties of a wide range hot mix asphalt (HMA) mixtures or not. Although the results showed that aggregate shape characteristics had strong correlations with measured mechanical properties, the data was not comprehensive enough to develop predictive equations of mechanical properties as functions of aggregate and other mixture properties. Discussion is provided on the laboratory experimental factors that influence the correlations between aggregate characteristics and measured mixture mechanical properties.