Abstract
The study of slope stability is of paramount importance for society, as it enables the evaluation of slope security and the establishment of alert parameters to mitigate financial losses and, in severe cases, prevent human casualties. Improving alert criteria necessitates a comprehensive assessment not only of the slope's safety factor but also its probability of failure. Therefore, the use of probabilistic techniques becomes imperative, with the Monte Carlo Method (MCM) emerging as a prevalent choice in geotechnical investigations. Employing MCM for slope stability involves modeling the target profile while varying crucial material parameterssuch as friction angle, cohesion, and specific weightin each iteration. As a result, the outcome yields a distribution of safety factors, aiding in the assessment of both average safety levels and failure probabilities. Failure probability is determined by counting simulations with safety factors below unity. Conventional approaches identified in the literature often employ uniform profiles in successive rounds, overlooking the spatial distribution of parameters. Hence, this study introduces a case analysis where failure probability is quantified through MCM, integrating random fields in each iteration. For assessing variability, the PLAXIS software was utilized, employing classical limit equilibrium methods alongside the LAS technique (Local Average Subdivision). This facilitates a comparative analysis of probabilities derived from distinct equilibrium methodologies. The case study will focus on a slope within Brazilian territory, where a comprehensive geotechnical survey encompassing field and laboratory assessments has been conducted.
Published Version
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