A digital reconstruction framework for three-dimensional asphalt pavement surface texture using the Contact Dynamics method

Pavement surface texture plays a critical role in functional performance, yet its design still relies largely on empirical trial-and-error due to the lack of predictive digital reconstruction methods. To address this limitation, this study develops a three-dimensional discrete element method (DEM)-based framework for the digital reconstruction of asphalt pavement surface texture using the Contact Dynamics method. Laser-scanned polyhedral aggregates are employed to generate digital asphalt mixture models with controlled gradation and packing. Direct DEM reconstruction captures the aggregate-controlled surface envelope but systematically overestimates surface roughness due to the absence of binder-induced smoothing effects. To alleviate this limitation, a bridging-based reconstruction strategy is introduced to approximate the surface continuity introduced by asphalt mastic. The proposed framework significantly improves the agreement between reconstructed and measured surface texture descriptors. Further particle-scale analysis reveals that pavement texture formation is governed by the coupled effects of aggregate size distribution and packing organization, establishing a physically interpretable link between internal skeleton structure and macroscopic surface morphology. The proposed framework provides an efficient approach for digital pavement surface reconstruction and quantitative surface characterization.