Probabilistic slope stability assessment of variably saturated overburden dump slopes

Abstract

Coal mining operations produce substantial soil and rock materials, often called Overburden (OB). These wastes are often dumped nearby, and this dumping results in the formation of large mounds of debris several meters in height, known as OB-dump slopes. The present study addresses the stability problem of variably saturated OB-dump slopes under a probabilistic framework by employing the kinematically admissible solution of the classical plasticity theorem. For the study, OB-dump slopes, located in several locations of the Dhanbad region in India, are selected. Varying magnitudes of steady-state surface flux boundary conditions have been simulated in the numerical analysis to understand the time-dependent behaviour of the OB-dump slope. Furthermore, for a comprehensive and detailed investigation, the influence of seismic stresses has also been accounted for by performing a series of rigorous pseudo-static analyses considering the strength non-linearity of the OB-dump materials. In addition, a probabilistic approach has been implemented to quantify the uncertainties associated with the critical random input parameters through the application of the design of experiments and factorial design methodology. The relative significance or sensitivity of each parameter was obtained using analysis of variance (ANOVA), and multiple regression analysis was employed to develop a predictive model for assessing the safety factor of the dump slope. Finally, the developed prediction model has been coupled with a rigorous Monte-Carlo simulation technique to obtain the probability of failure of the OB-dump slope. Based on the study, it was found that the saturation and its variation of OB-dump materials play a crucial role in its stability, with a percentage variation of up to 6.6% in the FoS. Additionally, seismic earthquake coefficients and slope angle are the two most critical parameters affecting the slope stability, followed by the infiltration rate ratio.