Toward large-scale fine resolution DEM landslide simulations: periodic granular box for efficient modeling of excavatable slope

Abstract

Understanding landslide hazards and developing mitigation measures is critical to protecting lives and property. The Discrete Element Method (DEM) has demonstrated its ability to simulate landslides and estimate impact forces on mitigation structures. Such simulations often model slope surfaces as bedrock on which a fixed amount of earth mass is released and slides. Mass entrainment due to local failure of an excavatable slope surface is rarely modeled with sufficient resolution. Fine-resolution modeling of an excavatable slope for simulation is necessary and non-trivial to improve DEM simulations of large-scale landslides. In this study, we present a method based on Periodic Granular (PG) boxes for efficient modeling of excavatable slopes. A PG box is a packing of particles in a quasi-static state inside a virtual unit box, where the periodic boundary conditions are satisfied at the box surfaces. The procedures used to construct a PG box are presented. The quality of PG boxes is analyzed both at the particle contact scale and at the laboratory specimen scale by measuring contact orientation statistics and by performing numerical triaxial tests. As a demonstration, a centimeter resolution slope model constructed using the PG box-based method is presented using topographic data for the Aso Bridge landslide. In addition, landslide simulations to verify the excavation effect were performed on sub-meter resolution slope models. Our simulations show that landscape shape and particle size have a direct effect on the movement and deposition of earth masses. This highlights the need for detailed 3D terrain modeling and further study of particle size effects. By constructing the first excavatable DEM slope model with billions of centimeter-sized particles, this study can be considered a solid step toward fine-resolution DEM simulations of large-scale landslides, which can contribute to both scientific understanding and engineering countermeasures to mitigate the catastrophic consequences of large-scale landslides.