Risk analysis of rock slope stability and stochastic properties of discontinuity parameters in western North Carolina.

摘要

Probabilistic analysis is a powerful method to quantify variability and uncertainty common to engineering geology studies. In rock slope engineering, uncertainty and variability involve a large scatter of orientation data and fracture geometry, with subsequent, varied test results. For comparison, conventional deterministic analysis based on the factor of safety concept uses a fixed representative value for each parameter without considering scatter effects.; Objectives of this research were to characterize stochastic properties of discontinuity parameters, conduct probabilistic analysis of rock slope stability and to compare deterministic and probabilistic results. Field sites in the Blue Ridge Province of North Carolina were investigated.; The research is composed of two parts; analysis of stochastic properties of discontinuity parameters, and risk analysis of rock slope stability based on random properties of parameters.; Using field measurements and test results, the random properties of geometric and strength parameters for discontinuities were characterized, based on statistical and probabilistic analysis procedures. Probabilistic stability analysis was accomplished using statistical parameters and probability density functions of each discontinuity parameter, by applying the Monte Carlo simulation method. Two different probabilities were evaluated; probability that a block is kinematically unstable and that a block is kinetically unstable. Using these calculations, probabilities of block failure and of slope system failure were determined.; Results of probabilistic analysis for the current study indicate that rock slopes along Interstate 40 are still unstable, whereas those along Interstate 26 are fairly stable. Comparisons between deterministic and probabilistic evaluations indicated that in many cases, results of the deterministic analysis differ significantly from those of the probabilistic analysis.