2018/08/11 by S. Takizawa, Shinta Takizawa, Hirofumi Niiya +7 · 6 citations
Engineering · Environmental Science · Physics and Astronomy · #Acceleration #Attenuation #Classical mechanics #Discrete element method #Geology #Geotechnical engineering #Granular flow and fluidized beds #Granular layer #Granular material #Impact crater #Landslide #Landslides and related hazards #Materials science #Mechanics #Optics #Particle Dynamics in Fluid Flows #Physics #Projectile #Terrain #cond-mat.soft
paper · pdf · doi:10.1016/j.physd.2018.08.002
published in Physica D Nonlinear Phenomena 386-387, 8-13 (Elsevier BV) · 7 pages, 5 figures
openalex publication_date 2018/08/11 · arxiv created 2018/08/15 · arxiv updated 2018/08/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The collapse of an inclined cohesive granular layer triggered by a certain perturbation can be a model for not only landslides on Earth but also relaxations of asteroidal surface terrains. To understand such terrain dynamics, we conduct a series of experiments of a solid-projectile impact onto an inclined wet granular layer with various water contents and inclination angles. As a result, we find two types of outcomes: "crater formation" and "collapse". The "collapse" phase is observed when the inclination angle is close to the maximum stable angle and the impact-induced vibration at the bottom of wet granular layer is sufficiently strong. To explain the collapse condition, we propose a simple block model considering the maximum stable angle, inclination angle, and impact-induced vibrational acceleration. Additionally, the attenuating propagation of the impact-induced vibrational acceleration is estimated on the basis of three-dimensional numerical simulations with discrete element method using dry particles. By combining wet-granular experiments and dry-granular simulations, we find that the impact-induced acceleration attenuates anisotropically in space. With a help of this attenuation form, the physical conditions to induce the collapse can be estimated using the block model.