Abstract
Risk is part of every sector of engineering design. It is a consequence of the uncertainties connected with the cognitive boundaries and with the natural variability of the relevant variables. In soil and rock engineering, in particular, uncertainties are linked to geometrical and mechanical aspects and the model used for the problem schematization. While the uncertainties due to the cognitive gaps could be filled by improving the quality of numerical codes and measuring instruments, nothing can be done to remove the randomness of natural variables, except defining their variability with stochastic approaches. Probabilistic analyses represent a useful tool to run parametric analyses and to identify the more significant aspects of a given phenomenon: They can be used for a rational quantification and mitigation of risk. The connection between the cognitive level and the probability of failure is at the base of the determination of hazard, which is often quantified through the assignment of safety factors. But these factors suffer from conceptual limits, which can be only overcome by adopting mathematical techniques with sound bases, not so used up to now (Einstein et al. in rock mechanics in civil and environmental engineering, CRC Press, London, 3–13, 2010; Brown in J Rock Mech Geotech Eng 4(3):193–204, 2012). The present paper describes the problems and the more reliable techniques used to quantify the uncertainties that characterize the large number of parameters that are involved in rock slope hazard assessment through a real case specifically related to rockfall. Limits of the existing approaches and future developments of the research are also provided.
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The Authors thank the Foundation “Montagna Sicura” (Aosta), the “Gran Paradiso” National Park, Eng. M. Curtaz, Dr. M. Vagliasindi, Dr. P. Quagliolo, and Dr. M. Balestro for the support provided during this study.
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Ferrero, A.M., Migliazza, M.R., Pirulli, M. et al. Some Open Issues on Rockfall Hazard Analysis in Fractured Rock Mass: Problems and Prospects. Rock Mech Rock Eng 49, 3615–3629 (2016). https://doi.org/10.1007/s00603-016-1004-2
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DOI: https://doi.org/10.1007/s00603-016-1004-2