Multi-phase flow simulation of landslide dam formation process based on extended coupled DEM-CFD method. (December 2021)

• Record Type: Journal Article
• Authors: Nian, Tingkai; Li, Dongyang; Liang, Qiuhua; Wu, Hao; Guo, Xingsen
• Is Part Of: Computers and geotechnics. Volume 140(2021)
• Publication Date: 2021-12
• Subjects: Landslide dam -- Discrete element method -- Volume of fluid -- Landslide-river interaction -- Impulse wave -- Particle-liquid-gas interaction; Engineering geology -- Data processing -- Periodicals; Soil mechanics -- Data processing -- Periodicals; Rock mechanics -- Data processing -- Periodicals; 624.1510285
• DOI: 10.1016/j.compgeo.2021.104438
• Languages: English
• ISSNs: 0266-352X

Abstract

Abstract: The landslide-river interaction and the impulse waves involved in the landslide dam formation process may not be insignificant and have not been extensively investigated and simulated. This paper presents a numerical investigation on the formation process of landslide dams and resulting free surface flow dynamics in the impacted river via coupled discrete element method (DEM) and computational fluid dynamics (CFD) with the volume of fluid (VOF). The accuracy and validity of the extended coupled method are verified using a series of test cases involving three-phase interaction and free surface evolution. It is then applied to simulate the landslide dam formation processes related to landslide and river flow scenarios of different kinematic characteristics. Furthermore, quantitative analysis is performed to describe the complex evolution of the dam morphology and dynamic evolution of impulse waves. It is found that the impact between the landslide, river flow and valley drives the dam formation process. The landslide velocity considerably influences the propagation of impulse waves, while the river flow velocities control the dam morphology in opposite ways in the upstream and downstream. This research provides a practical modeling framework to understand the formation mechanism of landslide dams and support applications in hazard prediction and mitigation.