Abdoreza Fazeli

Analysis of stability of rock slopes is a branch of rock engineering that is highly amenable to probabilistic treatment. Probabilistic analysis of rock slope stability has been used as an effective tool to evaluate uncertainty so prevalent in variables and has received considerable attention in the literature. In this research the application of the Jointly Distributed Random Variables (JDRVs) method for probabilistic analysis and reliability assessment of rock slop stability with plane sliding is investigated. The selected probabilistic parameters are friction angle of sliding surface and apparent cohesion which are modeled using a truncated normal probability distribution function and the depth of water in tension cracks and earthquake acceleration ratio which are considered to have truncated exponential probability distri- bution function. The parameters related to geometry and unit weight are regarded as deterministic parameters. The results are compared with the Monte Carlo (MC) simulation. Comparison of the results indicates that the results of the JDRV method include a degree of error, primarily due to the interdepen- dency of some of the variables in the formulation. It is also shown that due to this interdependency of the variables, the application of JDRV method in reliability assessment of rock slope stability will result in errors and hence, the MC method will be the preferable method. The results of sensitivity analysis using Monte Carlo simulation show that the friction angle of sliding surface is the most effective parameter in rock slope stability with plane sliding.