Gradation Optimization Based on Micro-Analysis of Rutting Behavior of Asphalt Mixture

Abstract

This study investigates the microscopic mechanism of the force on particles of different particle sizes in the asphalt mixture during rutting formation. The gradation was optimized by analyzing the particle force results. The enhanced discrete element method (EDEM) was used to simulate the rutting test, study the correlation state between different particle sizes in the rutting process, and analyze the rutting of asphalt pavement from the aggregate level. From a microscopic perspective, the specific forces acting on particles at different times were determined to investigate the particle size range of stressed particles in two types of asphalt mixtures. Furthermore, the role of particles with different sizes in the rutting process was analyzed. The force limit values of particles with different particle sizes are fitted, and the force of particles in two types of asphalt mixtures is compared and analyzed. After that, the gradation of the asphalt mixture is optimized, and the feasibility of the gradation optimization method is verified by laboratory experiments. The results show that the change rule of the rutting simulation test is gradually transformed from compacted rutting to unstable rutting. The force of the asphalt concrete-13 (AC-13) asphalt mixture is borne by the particles with a radius greater than 1.8 mm. The force of the stone matrix asphalt-13 (SMA-13) asphalt mixture is borne by the particles with a radius greater than 3.6 mm, and the small particle size particles play a filling role. When the particle radius is less than 5.1 mm, the force value of AC-13 asphalt mixture particles is greater than that of SMA-13. When the particle radius exceeds 5.1 mm, the force value of SMA-13 asphalt mixture particles is greater than that of AC-13. The force of particles with a radius of 5.7 mm and 7.3 mm in the SMA-13 asphalt mixture is 30% higher than that in AC-13, and the force limit of particles is proportional to the particle size. The dynamic stability, flexural tensile strength, water immersion residual stability, and freeze-thaw splitting strength ratios of the optimized asphalt mixture are improved compared with those before optimization. The AC-13 asphalt mixture is increased by 8.5%, 9.2%, 1.6%, and 1.9%, respectively, and the SMA-13 asphalt mixture is increased by 10.6%, 7.3%, 0.7%, and 2.1%, respectively. It shows that the grading optimization method is feasible.