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Modelación computacional de deslizamientos de tierra masivos inducidos por sismos usando el Método del Punto Material.
- Source :
-
Obras y Proyectos . 2024, Issue 35, p31-39. 9p. - Publication Year :
- 2024
-
Abstract
- Landslides represent one of the most frequent and destructive natural hazards in recent years. In highly seismic countries, the occurrence of large earthquakes is a significant triggering factor in the generation of these landslides. Therefore, it is of interest to various disciplines within civil engineering to study these phenomena through empirical analysis, analytical methods, and numerical modelling, aiming to provide a more accurate representation of these complex phenomena. For this purpose, a computational modelling approach is developed to describe the dynamics of a landslide or rockslide induced by seismic loading, using the Material Point Method (MPM). Presently, the utilization of MPM holds considerable significance because it is a numerical method engineered to simulate large deformations. This stands in contrast to conventional methods like the Finite Element Method (FEM), which struggles to precisely deal with this type of problems due to the generation of errors related to mesh distortion. In this study, it is performed a modelling process involving a real and documented scenario--a massive landslide occurrence in the vicinity of Daguangbao, China, triggered by the 2008 Wenchuan Earthquake. The obtained results successfully capture the landslide dynamics in terms of velocities, deformations, and travel distances in accordance with existing reports and other research endeavours. The maximum attained velocities of the landslide are approximately 100 km/h, affirming the catastrophic nature of this event. [ABSTRACT FROM AUTHOR]
Details
- Language :
- Spanish
- ISSN :
- 07182805
- Issue :
- 35
- Database :
- Academic Search Index
- Journal :
- Obras y Proyectos
- Publication Type :
- Academic Journal
- Accession number :
- 178288114
- Full Text :
- https://doi.org/10.21703/0718-2813.2024.35.2797