Stress chain analysis of soil particles in slope via persistent homology

TL;DR

This paper uses persistent homology and particle discrete element simulations to analyze the force chain network in slopes, linking topological features to slope instability and enabling better prediction of slope failure.

Contribution

It introduces a novel approach combining persistent homology with particle simulations to analyze slope stability and predict failure.

Findings

Topological features correlate with slope instability stages.

Persistent homology provides effective topological signatures for slope failure.

The method enables early prediction of slope destruction.

Abstract

The relationship between the macroscopic response of the slope and the macrostructure of the force chain network under the action of the metal plate was studied by the particle discrete element method and the persistent homology. The particle accumulation model was used to simulate the instability process of slope under the continuous downward action of metal plate by the particle discrete element method. The macroscopic responses such as the total velocity vector of the two-dimensional slope deposit, the angle of the slip cracking surface when the slope is unstable, and the average velocity in the y-direction of the slope were studied. Then, the normal force chain undirected network model of the natural accumulation of slope stacking particles was constructed. Finally, the topological characteristics of the particle contact force chain network of the slope top were analyzed by the persistent homology method to obtain the barcode. Finally, the relationship between the instability evolution and the characteristics of persistent homology is established. This research provides a new method for the study of slope instability topology identification. Thus, the instability destruction of slope can be predicted effectively.