The paper describes part of a study carried out to develop the geotechnical model of a coastal area on the Adriatic Sea, between the municipalities of Cesenatico and Bellaria-Igea Marina in the Emilia-Romagna region (Italy). A large experimental database, provided by the Geological, Seismic and Soil Survey of the Emilia-Romagna Authority, was used to develop a stratigraphic model of the upper 30 m subsoil of this coastal area, together with estimates of the mechanical parameters of the different soil units. A Bayesian approach was used to identify the most probable number of soil layers and their thicknesses, based on the Soil Behaviour Type Index obtained from CPTU results. This tool has already been used for small scale areas and its implementation in large datasets could eventually provide a preliminary estimate of the expected soil conditions at a site, taking into account statistically the inherent spatial variability in a rational and transparent way.
Tonni, L., García Martínez, M., Rocchi, I., Zheng, S., Cao, Z., Martelli, L., et al. (2018). A probabilistic approach to CPTU interpretation for regional-scale geotechnical modelling. Leiden : CRC Press/Balkema.
A probabilistic approach to CPTU interpretation for regional-scale geotechnical modelling
Tonni, L.
;García Martínez, M. F.;
2018
Abstract
The paper describes part of a study carried out to develop the geotechnical model of a coastal area on the Adriatic Sea, between the municipalities of Cesenatico and Bellaria-Igea Marina in the Emilia-Romagna region (Italy). A large experimental database, provided by the Geological, Seismic and Soil Survey of the Emilia-Romagna Authority, was used to develop a stratigraphic model of the upper 30 m subsoil of this coastal area, together with estimates of the mechanical parameters of the different soil units. A Bayesian approach was used to identify the most probable number of soil layers and their thicknesses, based on the Soil Behaviour Type Index obtained from CPTU results. This tool has already been used for small scale areas and its implementation in large datasets could eventually provide a preliminary estimate of the expected soil conditions at a site, taking into account statistically the inherent spatial variability in a rational and transparent way.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
