Probabilistic analysis of post-failure behavior of soil slopes using random smoothed particle hydrodynamics

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

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Detail(s)

Original languageEnglish
Article number105266
Journal / PublicationEngineering Geology
Volume261
Early online date14 Aug 2019
Publication statusPublished - 1 Nov 2019

Abstract

Slope failure or landslide is a common and severe geo-hazard which may cause significant casualties and economic losses. Casualties and economic losses caused by soil slope failure are often determined by volume of sliding soil mass and influence zone during post-failure process. It is therefore of great importance to study both slope failure probability and post-failure behavior. Estimation of failure probability has attracted much research attention, but assessment of post-failure behavior, especially the influence zone, is relatively rare. This probably dues to the difficulty in simulating the whole process of slope failure (e.g., initiation of the slope failure, transportation and final deposition of the sliding mass). For example, the factor of safety and critical slip surface obtained from the commonly-used limit equilibrium method only correspond to initiation of the slope failure; while finite element/difference methods may suffer from grid distortion problems when simulating large soil deformation that occurs during slope failure. To properly assess the post-failure behavior of soil slopes, this paper proposed a Monte Carlo simulation (MCS) based method, called random smoothed particle hydrodynamics (RSPH), in which random field theory is used together with a particle-based mesh-free numerical method, called smoothed particle hydrodynamics (SPH). The proposed approach is able to simulate the whole process of soil slope failure and provide reasonable estimations of failure probability, influence zone and volume of sliding mass during post-failure process.

Research Area(s)

  • Geo-hazard, Landslides, Large deformation, Monte Carlo simulation, Random field, Soil slopes