Abstract

Slope stability in reservoirs depends on time-dependent triggering factors such as fluctuations of the groundwater level and precipitation. This paper assesses the stability of reservoir slopes over time, accounting for the uncertainty of the shear strength and hydraulic parameters. An intelligent surrogate model has been developed to reduce the computational effort. The capability of two machine learning algorithms, namely Support Vector Regression and Extreme Gradient Boosting, is considered to obtain the relationship between geomechanical parameters and the factor of safety. The probability of failure of a hypothetical reservoir slope is estimated employing Monte Carlo simulations for different scenarios of drawdown velocity. A sensitivity analysis is conducted to investigate the influence of the geomechanical parameters, regarded as random variables, on the probability of failure. The results revealed that the coefficient of variation in the effective friction angle and the correlation between effective cohesion and friction angle have the highest impact on the probability of failure. The intelligent surrogate model can predict the factor of safety of reservoir slopes under rapid drawdown with high accuracy and enhanced computational efficiency.

Highlights

  • Rapid drawdown is one of the major causes of failure of earth slopes subjected to changing river levels

  • The seepage analysis and the slope stability analysis are conducted for each sample combination (i.e., 2000 times) and for each time step of the transient seepage analysis

  • The pore water pressure (PWP) and the effective degree of saturation are the inputs of the slope stability analysis and the factor of safety (FOS) is calculated with the Morgenstern–Price method

Read more

Summary

Introduction

Rapid drawdown is one of the major causes of failure of earth slopes subjected to changing river levels. The internal pore water pressure (PWP) distribution of a fine-grained slope reflects the initial water level for some time. Three approaches have been proposed to investigate this scenario: undrained analyses, flow methods and coupled flow deformation analyses. The first group is suitable for impervious materials and neglects the water flow since the dissipation of PWP is much slower than the decrease in the water level. A fully coupled flow deformation analysis was first proposed by Pinyol et al [42]. The authors highlighted the discrepancies between the aforementioned approaches: the undrained analysis leads to conservative and unrealistic results while pure flow analyses underestimate the PWP. The authors validated the coupled hydro-mechanical method by comparing the calculated PWP with piezometer measurements from the Canelles landslide in Spain [43]

Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call