Digital Twin Modeling for Landslide Risk Scenarios in Mountainous Regions

Area of Science:

• Geological Engineering
• Computational Geomechanics

Background:

• Rainfall-induced landslides are a significant geological hazard.
• These events threaten lives, property, and ecosystems, necessitating improved prediction methods.

Purpose of the Study:

• To develop an advanced digital twin framework for mitigating rainfall-induced landslides in high-altitude mountainous regions.
• To couple multiple physical fields for enhanced landslide prediction and analysis.

Main Methods:

• Utilized a spherical discrete element method (DEM) for landslide simulation.
• Pioneered a three-dimensional close-packed spherical DEM with streamlined contact mechanics for computational efficiency and stability.
• Developed a coupled hydro-mechanical model integrating stress, rainfall, and seepage fields.

Main Results:

• Identified a trapezoidal stress distribution with inward-increasing stress in 2D simulations.
• Observed alterations in stress magnitudes post-failure, while the overall pattern persisted.
• Achieved enhanced computational efficiency and numerical stability through simplified friction modeling.

Conclusions:

• The proposed digital twin framework enables real-time mapping of landslide evolution.
• Dynamic parameter adjustments allow for accurate modeling of hydro-mechanical interactions during landslides.
• The study advances the prediction and mitigation strategies for rainfall-induced landslides.