Hydrodynamic self-cleaning behaviors of double-layer drainage asphalt pavement

To understand self-cleaning behaviors of hydrodynamic pressure on clogging substances in double-layer drainage asphalt pavement (DDAP), the computational fluid dynamics-discrete element method (CFD-DEM) coupling model of DDAP with various particle-sized clogging substances was established. Then the hydrodynamic pressure was extracted and user-defined functions for hydrodynamic pressures were created to simulate self-cleaning effects of hydrodynamic pressure on clogging substances. Results indicate that hydrodynamic pressure gradient causes high-speed water flow in connected pavement pores. Some clogging particles are removed under positive hydrodynamic pressure, and partial clogging substances are flushed out to pavement surface. Also, the self-cleaning effectiveness of hydrodynamic pressure on clogging substances increases with vehicle speed is raised. The self-cleaned clogging mass under negative hydrodynamic pressure is significantly larger than that under positive hydrodynamic pressure. Additionally, the self-cleaned clogging mass increases as the wheel load is elevated, but it shows little differences in the self-cleaned clogging mass when the wheel load exceeds 4000 N. At the same water film thickness on DDAP, the self-cleaned clogging mass under negative hydrodynamic pressure is larger than that under positive hydrodynamic pressure. Thicker water films provide higher self-cleaning efficiency. Finally, smaller clogging particles are less interfered with pavement pore to cause the clogging. Larger-sized clogging substances have more deposition state types, and are accumulated in the shallow surface layer. Under negative hydrodynamic pressure, the clogging substances are easily pumped out to pavement surface, demonstrating higher self-cleaning effectiveness on clogging substances.