Optimizing Support Design for Wedge Instability - the Viability Index
Mark S. Diederichs1, Samantha Espley2, Chris Langille3
The assessment of structural instability potential for mine openings typically involves scanline mapping of existing rockmasss exposures, a stereographical analysis of joint orientation data to identify sets or clusters, and a ubiquitous joint wedge analysis to identify maximum or full-span wedges. The most critical of these wedges are then analyzed for their internal stability (sliding wedges) or for their requirements for stabilizing support.
This technique is widely accepted, and yet it consistently yields highly conservative results for support requirements. It is of considerable importance in today's mining climate to reduce production costs, of which support costs make up a significant component. This can be done by designing support systems with sufficient capacity for the most viable instability case instead of the worst possible case. The "worst case" for wedge instability is the full-span wedge or the largest wedge which can possible form across a given span. With the exception of several scenarios where this may be a common occurrence (these are identified in this paper), the probability of three joints mutually intersecting to create such a wedge occurring is extremely low due to the discontinuous nature of joints and the variability of spacing and location. In addition, such a wedge may possess limited amounts of internal stability due to cohesion and clamping.
This paper introduces a technique in which joint set dominance, spacing, and trace length are used to factor the full-span (ubiquitous) predictions for wedge size, accounting for the relative probability of occurrence of such a wedge. In addition, the internal stability of the wedge is accounted for, further reducing the required support, based on joint roughness, shape and alteration as well as wedge shape and clamping stress. This semi-empirical viability index technique has been verified using discrete wedge mapping and has been shown to be an efficient and valuable tool in optimizing and rationalizing support design in underground mines.