Abstract

During the process of landslide, its dynamic mechanism is important to understand and predict these kinds of natural hazard. In this paper, a new method, based on concepts of complex networks, has been proposed to investigate the evolution of contact networks in mesoscale during the sliding process of slope. A slope model was established using the discrete element method (DEM), and influences of inter-particle frictional coefficients with four different values on dynamic landslides were studied. Both macroscopic analysis on slope landslide and mesoanalysis on structure evolution of contact networks, including the average degree, clustering coefficient and N-cycle, were done during the process of landslide. The analysis results demonstrate that: 1) with increasing inter-particle frictional coefficients, the displacement of slope decreases and the stable angle of slope post-failure increases, which is smaller than the peak internal frictional angle; 2) the average degree decreases with the increase of inter-particle frictional coefficient. When the displacement at the toe of the slope is smaller, the average degree there changes more greatly with increasing inter-particle frictional coefficient; 3) during the initial stage of landslide, the clustering coefficient reduces sharply, which may leads to easily slide of slope. As the landslide going on, however, the clustering coefficient increases denoting increasing stability with increasing inter-particle frictional coefficients. When the inter-particle frictional coefficient is smaller than 0.3, its variation can affect the clustering coefficient and stable inclination of slope post-failure greatly; and 4) the number of 3-cycle increases, but 4-cycle and 5-cycle decrease with increasing inter-particle frictional coefficients.

Highlights

  • Slope failure is a common geological hazard, which is a changing progress with time and space, including initial stage, landslide stage and stable stage post failure [1]

  • The analysis results demonstrate that: 1) with increasing inter-particle frictional coefficients, the displacement of slope decreases and the stable angle of slope post-failure increases, which is smaller than the peak internal frictional angle; 2) the average degree decreases with the increase of inter-particle frictional coefficient

  • Recurring to some concepts from complex network, including the average degree of contact network, clustering coefficient and N-cycle, we can investigate the mesostructures varying with the process of landslide, which can help in understanding the dynamic mechanism of landslide

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Summary

Introduction

Slope failure is a common geological hazard, which is a changing progress with time and space, including initial stage, landslide stage and stable stage post failure [1]. Studies on mesostructures and evolution of contact networks are necessary to be done to provide a new method to analyze the macroscopic mechanism of landslide. DEM has been used to simulate the sliding process of landslide, macroscopic process of landslide should be analyzed physically in detail from the meso scale of soil grains and meso structure network, which will be explored primarily here in the viewpoint of complex network method. Methods based on complex network have been used to analyze compression process of dense samples, but few studies have been reported on contact network analysis of landslide process in a perspective of complex network. Discrete element method (DEM) is employed here to construct slope model for computational analysis, based on which the influences of inter-particle frictional coefficients on process of landslide is investigated. From the perspective of complex network, the average degree, clustering coefficient and N-cycle are explored in detail during the process of landslide

Establishment of Slope Model
Calibration of Parameters of Biaxial Tests
Displacement Analysis
Analysis on Geometrical Shape of Slope Post-Failure at a New Stable State
Displacement at Slope Toe
Evolution Analysis of Contact Network in the Process of Landslide
The Evolution of Average Degree
The Evolution of Clustering Coefficient
N-Cycle
Analysis on Relationships Bridging Meso and Macro Parameters
Conclusions
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