Landslide continuum dynamic models have improved considerably in the past three decades, especially within the past few years, but a consensus on the best method of determining the input resistance parameter values for predictive runs has not yet emerged. A calibration-based approach is one possible method, although different calibrated values are often obtained using different models to back-analyze the same event. These differences may be amplified by the different input geometrical assumptions made in each case.With the authors’ own models, consistent ranges of calibrated parameter values have been found for specific classes of events, and these ranges can be used for parametric forward-analyses. A long-term goal of this work is to build a calibration database large enough to permit probabilistic input parameter selection.

Special lecture. Advances in landslide continuum dynamic modelling / Mcdougall, S; Pirulli, Marina; Hungr, O; Scavia, Claudio. - STAMPA. - 1:(2008), pp. 145-157. (Intervento presentato al convegno 10th International Symposium on Landslides and Engineered Slopes tenutosi a Xi'An (China) nel 30 June - 4 July).

Special lecture. Advances in landslide continuum dynamic modelling

PIRULLI, MARINA;SCAVIA, Claudio
2008

Abstract

Landslide continuum dynamic models have improved considerably in the past three decades, especially within the past few years, but a consensus on the best method of determining the input resistance parameter values for predictive runs has not yet emerged. A calibration-based approach is one possible method, although different calibrated values are often obtained using different models to back-analyze the same event. These differences may be amplified by the different input geometrical assumptions made in each case.With the authors’ own models, consistent ranges of calibrated parameter values have been found for specific classes of events, and these ranges can be used for parametric forward-analyses. A long-term goal of this work is to build a calibration database large enough to permit probabilistic input parameter selection.
2008
9780415411967
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/1902689
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