Stochastic Slope Stability Analysis: Exploring the Uncertainty of Input Motion

DOI

10.2991/978-94-6463-258-3_59How to use a DOI?

Keywords

Stochastic Slope Stability Analysis; Pseudo-static Approach; Random Variability of Pseudo-static Loading; Soil Stochastic Modelling

Abstract

Slope stability issues are widely studied by geoengineers due to the significant risk they pose to human safety and the economy. Slope failures can be especially perilous, particularly in earthquake-prone regions, where even statically stable slopes can be triggered by dynamic loads. The pseudo-static (PS) approach is commonly employed in the initial stages of assessing seismic slope stability due to its effectiveness and efficiency. However, the variability of the PS coefficient is not commonly incorporated in the realm of stochastic slope stability analyses. In this study, the research focuses on simulating the spatial variability of soils in seismic slope stability analysis. The approach employed involves the integration of non-circular limit equilibrium method (LEM) of slices, Monte Carlo (MC) simulation, and random fields, termed as non-circular 2D-RLEM. A single random variable (SRV) approach is utilized for the pseudo-static (PS) load. The outcomes of parametric investigations are presented as design aids, providing valuable insights into the sensitivity of stochastic slope stability problems to various factors, including different levels of average PS loading and its uncertainty. It was observed that the impact of assigning different values to the coefficient of variation of seismic loading on the resulting slope failure probabilities was more significant for larger earthquakes. Meanwhile, a higher uncertainty level of the seismic coefficient was observed to be more critical for slopes with lower failure probabilities (i.e. less than about 40%).

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Pooneh Shah Malekpoor
AU  - Susana Lopez-Querol
AU  - Sina Javankhoshdel
PY  - 2023
DA  - 2023/11/08
TI  - Stochastic Slope Stability Analysis: Exploring the Uncertainty of Input Motion
BT  - Proceedings of the Rocscience International Conference  (RIC 2023)
PB  - Atlantis Press
SP  - 633
EP  - 640
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-258-3_59
DO  - 10.2991/978-94-6463-258-3_59
ID  - Malekpoor2023
ER  -