Stacey, TR 2007, 'Slope Stability in High Stress and Hard Rock Conditions', in Y Potvin (ed.), Slope Stability 2007: Proceedings of the 2007 International Symposium on Rock Slope Stability in Open Pit Mining and Civil Engineering, Australian Centre for Geomechanics, Perth, pp. 187-200, https://doi.org/10.36487/ACG_repo/708_Stacey
(https://papers.acg.uwa.edu.au/p/708_Stacey/)
Abstract: Open pit mines are being planned to greater depths that will certainly involve high stress and hard rock 
conditions. These conditions are not satisfactorily accounted for by conventional stability analysis 
approaches that are based on the common mechanisms of failure involving planar, wedge and circular shear 
surface, and toppling. Failure mechanisms in high, hard rock slopes are much more complex than this. 
Progressive failure in hard rock slopes involves initiation and progression of failure along existing weakness 
planes, and initiation and progression of failure in intact rock. 
Mechanisms of slope failure behaviour, and the implications for slope stability analysis and slope design, 
are considered in this paper. It is concluded that what is required for robust stability evaluation and design 
is much better understanding of the rock mass, and methods of analysis that can model the rock mass and 
take into account variability in all of the geotechnical parameters. Better site investigations and modern 
methods of slope monitoring should supply considerable information regarding the understanding of the 
three dimensional rock mass. Owing to geotechnical variability, data must be expressed in the form of 
statistical distributions, and methods of stability analysis must therefore be probabilistic rather than 
deterministic. The output from such analyses will not be a single evaluation, but a distribution of evaluations 
that will form the basis for a decision on the acceptability of risk of failure. Although the methods required 
for such analyses are already available in theory, they cannot yet be practically implemented because of lack 
of computing power. In particular, the requirement that analyses are probabilistic and three dimensional 
places enormous demands on computing capacity.