Kang Wang

Graded aggregates used in high-speed railway subgrades often undergo micro breakage (i.e., corner and edge spalling) under cyclic loading, whereas the mechanism linking local particle spalling to contact-network evolution and permanent deformation remains unclear. To address the lack of a physically based micro breakage criterion and a continuous local shape-updating scheme in existing DEM approaches, this study proposes an energy-driven micro breakage method. The method uses the relationship between contact elastic energy and fracture energy for newly created free surfaces as the breakage criterion. It also employs a radial function representation to simulate local particle shape evolution. The proposed method is subsequently validated through multilevel tests and shows reasonable agreement with the experimental results for particle micro breakage and the associated mechanical responses. Furthermore, dynamic triaxial simulation results show that micro breakage exhibits a distinct cumulative characteristic and increases with loading frequency and amplitude. Meanwhile, micro breakage drives particle rearrangement and new contact formation, leading to skeleton densification and weakening of the strong force-chain network, which in turn accelerates plastic deformation accumulation. These coupled processes constitute an important mechanism governing the progressive degradation of graded aggregates under cyclic loading. This study clarifies the associated particle-scale mechanism and provides a reference for performance optimization.

This study investigated the macro and meso mechanisms of void formation in graded aggregates within high-speed railway subgrades under train loads using a hybrid discrete element–finite difference method (DEM-FDM). First, a contact parameter inversion model based on a linear model (LM) was developed using extensive DEM simulations through angle of repose, drop, and inclined plate tests. The contact parameters for graded aggregates were further calibrated through physical and triaxial tests. Next, a refined hybrid DEM-FDM model was established to capture void formation behavior, characterized by the contact force chain ratio, and was validated against field measurements. Finally, simulations were conducted under different levels of void formation to explore the associated mechanisms based on dynamic response and meso-mechanical analysis. The results showed that the LM-based inversion model could accurately determine the contact parameters. The hybrid model’s predictions of dynamic displacement and acceleration under various train speeds fell within the range of the field data. When the fine particle loss ratio l_p was ≤3%, the dynamic displacement and acceleration remained below the standard limits of 0.22 mm and 10 m/s². As l_p increased, the contact between the roadbed and base weakened, and complete separation occurred at l_p ≥ 11%, preventing effective load transfer. These findings offer new insights into void formation in graded aggregates and support the safe operation of high-speed railways.