Study on large deformation of soil-rock mixed slope based on GPU accelerated material point method

Area of Science:

• Geotechnical Engineering
• Computational Mechanics
• Geohazards

Background:

• Soil-rock mixtures present complex challenges in slope stability analysis.
• Understanding landslide dynamics is critical for infrastructure safety and risk assessment.
• Material Point Method (MPM) is a powerful tool for simulating large deformation phenomena.

Purpose of the Study:

• To investigate the influence of stone content on the stability of soil-rock mixture slopes.
• To analyze the dynamics of large displacement landslides in these mixtures.
• To evaluate the efficacy of a GPU-accelerated MPM framework for geotechnical simulations.

Main Methods:

• Digital image processing to create soil-rock mixture slope models with varying stone content.
• Material Point Strength Reduction Method (SRM) to assess slope stability.
• Gravity ramping to establish initial conditions and monitor slope response.
• High-performance GPU-based MPM for simulating landslide dynamics.

Main Results:

• A positive correlation exists between stone content and slope stability.
• Increasing stone content from 10% to 40% progressively improved the safety factor.
• The GPU-accelerated MPM framework efficiently handled complex geotechnical simulations.

Conclusions:

• Higher stone content enhances the stability of soil-rock mixture slopes.
• The study validates the effectiveness of GPU-accelerated MPM for landslide dynamics.
• Findings provide valuable data for designing stable slopes in mixed soil-rock environments.