GEOTECHNICAL SLOPE STABILITY ANALYSIS, B & G SECTOR, BINGHAM CANYON OPEN PIT, UTAH, WITH A CONSEQUENT INVESTIGATION OF METHODS FOR DELINEATING ROCK MASS FRACTURE DOMAINS

Stability analysis of the B & G sector for a projected ultimate pit slope design of the northwestern side of the Bingham pit was conducted using probabilistic Monte Carlo limiting equilibrium methods. Stepped path plane failure and simple wedge failure were examined at various scales for the entire slope which was projected to exceed 2000\u27 in height. Circular and irregular failure through intact material was examined for a portion of the upper part of the slope. All of the analysis was accomplished on a mainframe computer. As a consequence of the stability analysis, a more thorough investigation of methods delineating rock mass fracture domains was undertaken. This developed because requirements for the Monte Carlo limiting equilibrium method dictated that design sets be selected to carry out the stability analysis. To justify the use of these design sets to describe the fracture domains in the slope area under study several methods for verifying their applicability were investigated. Of the methods studied only two, namely Critical Pair Clustering and Cell Coding offered any real advance over existing methods. FORTRAN computer programs were developed to cluster window mapping locations together on the basis of the similarity of joint orientation values measured within the windows during field mapping. Details regarding the stability analysis phase of the study are not available for public distribution. Probabilistic methods were used to analyze potential stepped planar, circular and wedge failures. The subsequent domain delineation investigation indicated the one of the methods, Critical Pair Clustering, seems to be able to produce results similar to those produced by the analysis of variance of cluster statistics method but requiring far less data while still retaining its vector character. Another method, Cell Coding, cannot be easily evaluated at present without further field testing. It did, on occasion, produce results similar to those of the clustering method. Shortcomings appear to be the amount of processing required by both methods