Hongfu Tan
Hongfu Tan has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- Jiawen Xu
Institute of Intelligent Manufacturing and Smart Transportation, Suzhou City University, Suzhou 215104, China
1 shared publication - Kang Wang
Department of Civil Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
1 shared publication - Le You
Institute of Intelligent Manufacturing and Smart Transportation, Suzhou City University, Suzhou 215104, China
1 shared publication - Lei Zhang
Zheda Jingyi Electromechanical Technology Corporation Limited, Hangzhou 311121, China
1 shared publication - Qian Chen
School of Smart Manufacturing and Intelligent Transportation, Suzhou City University, Suzhou 215104, China
1 shared publication - Zhibo Cheng
Institute of Computing Technologies, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China
1 shared publication
Latest Publications
- Open Access
Investigating the Mechanisms and Dynamic Response of Graded Aggregate Mud Pumping Based on the Hybrid DEM-FDM Method
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 lp was ≤3%, the dynamic displacement and acceleration remained below the standard limits of 0.22 mm and 10 m/s2. As lp increased, the contact between the roadbed and base weakened, and complete separation occurred at lp ≥ 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.
Open AccessInvestigating the Mechanisms and Dynamic Response of Graded Aggregate Mud Pumping Based on the Hybrid DEM-FDM Method
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 lp was ≤3%, the dynamic displacement and acceleration remained below the standard limits of 0.22 mm and 10 m/s2. As lp increased, the contact between the roadbed and base weakened, and complete separation occurred at lp ≥ 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.