Two-phase MPM modeling of dry granular fronts and watery tails formed in debris flows

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION(2024)

引用 1|浏览3
暂无评分
摘要
Debris flow is a mixture involving complicated interactions between granules and liquids. In the process of sliding down at high speed, it may pose a great threat to the life and health of people and property safety. In nature, the debris flows often show a dry granular front and a more watery tail, which makes the debris flows the most destructive geological disaster. Therefore, it is of great significance to deeply understand the kinematic characteristics of the landslide body and to accurately predict the flow of granular-liquid mixture in practical applications. In this paper, a two-phase material point method (MPM) based on mixture theory is used to model the formation of watery tails and dry granular fronts observed in debris flows. In the proposed model, the debris flow is idealized as a granular-liquid mixture, the liquid phase is assumed to be a weakly compressible viscous fluid, and an elastic-plastic model with Mohr-Coulomb yield criterion is used to model the granular response, and the granular-liquid interaction is realized through momentum exchange. The accuracy and effectiveness of the proposed method were verified by comparing the numerical results with the experimental data through two tests of a dry granular collapse and a granular-liquid mixture destabilization. Then, we applied the validated method to simulate the phenomenon of watery tails and dry granular fronts formed in debris flows, and investigated the effects of the angle of the inclined plane, the initial saturation (defined as the initial depth ratio of water to granular material), the granular density, internal friction angle, particle diameter and the initial porosity on the time evolution of the front end of the granules and the liquid.
更多
查看译文
关键词
Debris flows,Granular landslide,Dry granular fronts,Watery tails,Numerical modeling,Material point method,Granular -liquid interaction
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要