Adaptive classification of aggregate morphologies using clustering for investigation of correlation with contact characteristics of aggregates

To investigate the mechanism of the influence of aggregate morphologies on the internal structure of asphalt mixtures, an accurate classification of aggregates in morphology using an integration of affinity propagation (AP) and K-means clustering is proposed. To achieve this goal, the similarities of aggregates in angularity, surface texture, and form were evaluated and then used in clustering. Furthermore, morphological labels for aggregate clusters were constructed to indicate major features of the shape of aggregates in a cluster from the statistical perspective. 2,766 coarse aggregates in three specimens were three-dimensionally (3-D) reconstructed and classified in three ways. Compared with two other ways, K-means clustering using the cluster centers derived from the AP method performs best in the qualitative indices including silhouette coefficient, Davies-Bouldin (DB) index, and the Dunn index. Furthermore, the correlation between the contact characteristic and the morpho-logical grades of cluster labels in three specimens was analyzed, which shows that aggregates of cubic form, relatively rounded angularity with more fractured facets, and rich texture are more likely to have contact re-lations and larger contact regions. In addition, a pre-processing operation before clustering was adopted to reach a balance between the quality and efficiency of clustering. Therefore, the proposed method facilitates the optimization of the internal structure by the configuration of aggregate morphologies in future.

Automated summary

This study proposes a method to accurately classify the morphology of aggregates and investigates the influence of different morphologies on the internal structure of asphalt mixtures. By evaluating the similarities of aggregates and using clustering methods, the aggregates are classified and morphology labels are constructed. This method provides insights for optimizing the internal structure through the configuration of aggregate morphologies.