The current economic climate and demand for iron ore has resulted in mine operators being prepared to accept aggressive slope designs and associated failures provided that they can be quantified (ie volume of failure and clean up costs, etc) and incorporated into the mining costs, at a feasibility study level._x000D_
This has numerous implications for pit slope design/geomechanics. Typically when geotechnical engineers conduct slope stability modelling a single value, usually the average or mean value for model input parameters (ie structural orientations, material properties and hydrological conditions) are chosen. The implications resulting from using a single value for model input parameters will vary depending on how the modeller has chosen the value, ie should the modeller choose a mean value from a log-normal distribution of material strengths an optimistic representation of the stability may eventuate, consequently if the designer decides to conservatively downgrade the values by a nominal factor, a pessimistic representation of slope angles may occur, which would result in excessive stripping and mine development costs._x000D_
A more realistic and representative way to model the inherent variability of geological/geotechnical conditions would be to do so probabilistically. Whereby the modeller can assess the variability of the geological structure as observed/recorded during the core logging process and a similar approach for the material strength properties. The final model output would be a distribution of factors of safety in relation to overall slope angles, ie probabilities of failure for individual slope angles could be determined. This output (graph) could be modified by the mining engineer to incorporate mining costs as well as clean up costs for the respective slope angles and associated failure volumes, ie probabilities of failure._x000D_
The author intends to provide a detailed overview of the processes involved in deriving a geotechnical design, ie; starting from the data collection phase (core logging/face mapping), through to the data interpretation and formulation of slope parameters; determining the variability and uncertainties associated with each of the process; ensuring that it is adequately captured in the model input parameters; and how the mining engineer could utilise this information to derive final feasibility study mining costs.