Investigation of Interaction Mechanisms between Hot Mix Asphalt and Paver Screed

The durability of asphalt pavements under traffic loads is significantly influenced by the compaction quality during construction. Poor compaction can lead to early pavement failure through cracking, rutting, or grain breakouts. The initial compaction stage performed by the asphalt paver is particularly critical, as subsequent roller compaction cannot correct errors at this stage. However, the complex interaction between the paver screed and hot mix asphalt, coupled with external factors like the delivery temperature of the asphalt mix, makes it difficult to achieve optimal compaction settings. This study addresses the knowledge gaps surrounding the precompaction process by analyzing the interaction between the paver screed and hot mix asphalt. A multi-faceted approach was adopted to achieve this, consisting of a comprehensive laboratory program, field trials, and a full-scale paver simulation using discrete element methods. The laboratory program examined different asphalt mixtures to evaluate the influence of temperature and asphalt mix type on various pre-defined asphalt paving properties. Field trials focused on understanding the effects of tamper and vibratory unit speeds, on the paving outcomes. Lastly, the discrete element simulation provided insights into the flow behavior and material movements during paving. The laboratory findings show that asphalt mix temperature impacts flow behavior, pre-compaction resistance, and friction. The field trials revealed that tamper speed significantly affects layer thickness and compaction, while the vibratory unit showed only a minor influence on the paving outcomes. The simulation results identify two primary material flow directions in the auger tunnel, driven by auger movements, with key grain rearrangement occurring near the tamper. Furthermore, the analysis emphasizes the importance of the tamper movement in achieving optimal compaction and critical wear areas on machine components. Based on these insights, recommendations for machine and process optimization were provided to enhance paving practices.