The Probabilistic Model for Shearing Resistance of Jointed Rock is a step in the development of complete methods for reliability analysis of rock slopes. The model derives the probability distribution of the strength of a discontinuous rock mass taking uncertainty on the joint pattern into consideration. The distributions of joint spacing and length from field surveys, the shear resistance parameters of intact rock and rock discontinuities, and the in-situ stress field are input data to the model. The paper describes the two main parts of the method, the stochastic model of joint geometries and the mechanical model. The results of actual computations are then presented and discussed to show the practical applicabilities of the method and to examine the sensitivity to various input parameters. The main qualitative, conclusion is that the probability distribution of apparent persistence is insensitive to variations of the stress field and of the joint orientation relative to the stress field. Apparent persistence depends strongly however on the distribution parameters of joint spacing and length together with cohesion of intact rock.


Probabilistic approaches to rock slope stability analysis have become increasingly common because they provide a rational incorporation of the uncertainty of parameters affecting slope stability. Risk analyses and Bayesian updating techniques used in site exploration require the use of probabilities of failure rather than the traditional factor of safety. Complete probabilistic modeling is theoretically possible but may be somewhat premature because the assumed mechanisms and associated parametric relations may introduce inaccuracies that have a greater effect than the uncertainty of individual parameters. In this paper a limited topic, the effect of discontinuity geometry on slope stability, will be treated. This partial model can later be incorporated into a complete probabilistic slope stability analysis.

This content is only available via PDF.
You can access this article if you purchase or spend a download.