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In this paper a knowledge-based clustered partitioning technique is developed for determining reliability index and failure probability of rock wedge. Here, the a reliability index is analyzed and the optimization is carried out using a knowledge-based clustered partitioning (KCP) technique. The reliability index computed with this KCP technique is compared with those using other approaches such as the Excel Solver-based method. The new technique for determining the reliability index involves a global search method and is found effective and efficient. Reliability analysis with this KCP technique is then used to examine the influence of parameter uncertainties and correlations among the parameters on the failure probability of rock wedges. Significant findings are derived from the sensitivity and parametric analysis.

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