Probabilistic identification of removable wedges in rock slopes: Influence of stochastic model parameters

Stochastic fracture network models are commonly employed to deal with uncertainties in the characterization of discontinuities in rock masses. We explore the engineering significance of parameters of the network model in the context of problem of formation of removable wedges in rock excavations. Discontinuities are simulated using the Poisson disk model, and removable wedges in the excavation are identified using block theory. The formation of removable wedges of different sizes is assumed to follow a Poisson process. Poisson regression and Monte Carlo simulations are used to identify statistically relevant parameters of the model and to study the effects that variations in their values have in formation of removable blocks. Results indicate that the volumetric intensity significantly affects the computed estimates of removable blocks. Estimates are sensitive to changes in discontinuity size in cases in which discontinuities are “small” compared to the height of the slope, and the interaction between the mean size and the coefficient of variation of discontinuity sizes is also found to be significant. The rates of formation of removable wedges are higher when joint sets with small orientation variability are considered.