ABSTRACT:
Probabilistic rock slope stability analyses are essential to risk assessments, as risk is defined by the probability of occurrence of an instability multiplied by the consequences of the failure. Usually, probabilistic rock slope stability problems are modeled using the Coulomb failure criterion since it is linear, providing simple modeling algorithms. It is acknowledged widely that rock slope stability problems may exhibit non-linear failure behavior, leading to consideration of non-linear limit equilibrium failure function generation in probabilistic analyses. In this paper two probabilistic models for the problem of plane failure are formulated by considering the Coulomb and Barton-Bandis failure criteria. The models are implemented for the stability evaluation of a 734 m high jointed rock slope called ‘Oppstadhornet’ in the west of Norway. It is observed that for the same rock slope conditions, the reliability index and the associated probability of failure (i.e. the safety indices for the probabilistic methods) give different values depending on the failure criterion adopted for the analysis. The Coulomb failure criterion gives probability values that are one order of magnitude higher than the Barton-Bandis failure criteria. Correspondingly, the reliability index values for the Barton- Bandis criteria are higher than the Coulomb criteria. The differences in the safety indices between the two criteria become more pronounced when the friction angle of discontinuities decreases.
1 INTRODUCTION
Risk assessment due to rock slides require probabilistic assessment of stability, as risk is basically defined by the multiplication of probability of occurrence of rock slide and consequences of the failure. Moreover, since rock slope stability problems contain many uncertainties due to inadequate information about site characteristics, inherent variability and measurement errors in the geological and geotechnical parameters, probabilistic modeling of rock slope stability problems allow systematic treatment of these uncertainties.