# Digital Twin Modeling for Landslide Risk Scenarios in Mountainous Regions

## TL;DR

A new 3D digital twin model improves landslide risk prediction by efficiently simulating stress and displacement patterns in mountainous regions.

## Contribution

The novel 3D digital twin framework introduces a physics-driven approach with enhanced computational efficiency for landslide simulation.

## Key findings

- Stress distribution in slopes increases uniformly from 0 kPa at the surface to 210 kPa in the innermost region.
- The sensitive zone of landslides is located at one-tenth of the slope height above the toe, not at the crest or base.
- The digital twin model enables real-time landslide evolution mapping through a coupled hydro-mechanical framework.

## Abstract

A novel 3D digital twin framework for landslides is developed using a closest-packed spherical discrete element model. The point-contact mechanism of spherical elements simplifies friction modeling and enhances computational efficiency. Steady-state slope stress exhibits a trapezoidal distribution, increasing from the surface inwards. The stress increases uniformly from 0 kPa at the surface to 210 kPa in the innermost region.

What are the main findings?
A sensitive zone of the landslide mass was identified in the numerical simulations. Both stress and displacement results consistently showed the highest concentration at one-tenth of the slope height above the toe, rather than at the crest or base.Advanced Simulation Framework: The novel 3D digital twin approach improves computational efficiency and enables realistic landslide evolution mapping.

A sensitive zone of the landslide mass was identified in the numerical simulations. Both stress and displacement results consistently showed the highest concentration at one-tenth of the slope height above the toe, rather than at the crest or base.

Advanced Simulation Framework: The novel 3D digital twin approach improves computational efficiency and enables realistic landslide evolution mapping.

What are the implications of the main findings?
This finding offers a new perspective for future research, as the identified stress and displacement concentration zone provides a tangible focus for further investigation.Advanced Predictive Modeling: The 3D digital twin framework provides a more stable method for simulating landslides. This approach introduces a physics-driven framework, effectively addressing the lack of realistic physical parameters in conventional hazard scenario modeling.

This finding offers a new perspective for future research, as the identified stress and displacement concentration zone provides a tangible focus for further investigation.

Advanced Predictive Modeling: The 3D digital twin framework provides a more stable method for simulating landslides. This approach introduces a physics-driven framework, effectively addressing the lack of realistic physical parameters in conventional hazard scenario modeling.

Background: Rainfall-induced landslides are a widespread and destructive geological hazard that resist precise prediction. They pose serious threats to human lives and property, ecological stability, and socioeconomic development. Methods: To address the challenges in mitigating rainfall-induced landslides in high-altitude mountainous regions, this study proposes a digital twin framework that couples multiple physical fields and is based on the spherical discrete element method. Results: Two-dimensional simulations identify a trapezoidal stress distribution with inward-increasing stress. The stress increases uniformly from 0 kPa at the surface to 210 kPa in the interior. The crest stress remains constant at 1.8 kPa under gravity, whereas the toe stress rises from 6.5 to 14.8 kPa with the slope gradient. While the stress pattern persists post-failure, specific magnitudes alter significantly. This study pioneers a three-dimensional close-packed spherical discrete element method, achieving enhanced computational efficiency and stability through streamlined contact mechanics. Conclusions: The proposed framework utilizes point-contact mechanics to simplify friction modeling, enhancing computational efficiency and numerical stability. By integrating stress, rainfall, and seepage fields, we establish a coupled hydro-mechanical model that enables real-time digital twin mapping of landslide evolution through dynamic parameter adjustments.