Landslide risk reduction by coupling monitoring and numerical modeling
Keywords:engineering-geology model, monitoring, numerical modeling
The importance of the reference engineering-geology model of a slope is a concept well established in the scientific and technical community facing on large infrastructures. The engineering-geology model is in fact a fundamental informative layer to understand and predict the structure-slope interactions and to design stabilization countermeasures. Such an issue has a relevant role in the case of unstable slopes: at this regard the Vajont case history represents a worldwide reference. Engineering-geology models can be validated and/or updated by monitoring data. Furthermore, the harmonization of engineering-geology models and monitoring data can be achieved by the implementation of stress-strain numerical models, that represent a validating tool for the engineering-geology models, by collecting the monitoring data and by refining, via calibration analyses, the rheological behaviors, i.e. the stress-strain constitutive laws. In this frame, our experience is referred to an unstable slope involved in a tunnel excavation. A very detailed engineeringgeology model was built by means of several in situ and laboratory investigations. The availability of monitoring data with high temporal and spatial resolution referred to slope instability episodes triggered by different external factors (e.g. rainfalls, tunneling, etc) made it possible to better understand the dynamics of the slope-infrastructure system and to refine the numerical model of the slope by using the finite difference code FLAC 7.0. Such a numerical model was implemented by applying a continuum equivalent approach to the involved jointed rock mass, which was considered as a visco-plastic material in order to account for the time dependent behavior. At present promising results have been obtained, especially in terms of assessment of stress-strain variations due to external forces (both environmental and man-induced) and, thus, of forecasting the activation/reactivation of slope instabilities
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