This study aims to quantify the impact of soil deformability on the modal response of monumental buildings, taking into account material uncertainty through a probabilistic approach. To this end, two well-known monuments, the Leaning Tower and the Baptistery of Pisa (Italy), which share the same deformable soil conditions, were selected as case studies. To assess the sensitivity of the computed eigenfrequencies to variations in soil and masonry elastic parameters, surrogate models were constructed using the generalized Polynomial Chaos Expansion technique. The model of the Leaning Tower was subsequently updated through Bayesian inference, leveraging the availability of eigenfrequencies identified in a recent experimental campaign and considering both deformable soil and fixed-base conditions. The study highlights the key influence of soil elastic properties on the first eigenfrequencies, which are the most commonly used in dynamic model updating. In addition, the model updating process results provide strong evidence of the critical role that Soil Structure Interaction (SSI) plays in achieving reliable structural models. These results underscore the importance of considering soil deformability in designing structural health monitoring systems and updating dynamic models based on experimental eigenfrequencies.

Probabilistic assessment of the modal response of monumental structures considering soil deformability and material uncertainty: The Leaning Tower and Baptistery of Pisa (Italy)

G. Bartolini
;
A. De Falco;F. Landi;C. Resta;L. Vignali
2025-01-01

Abstract

This study aims to quantify the impact of soil deformability on the modal response of monumental buildings, taking into account material uncertainty through a probabilistic approach. To this end, two well-known monuments, the Leaning Tower and the Baptistery of Pisa (Italy), which share the same deformable soil conditions, were selected as case studies. To assess the sensitivity of the computed eigenfrequencies to variations in soil and masonry elastic parameters, surrogate models were constructed using the generalized Polynomial Chaos Expansion technique. The model of the Leaning Tower was subsequently updated through Bayesian inference, leveraging the availability of eigenfrequencies identified in a recent experimental campaign and considering both deformable soil and fixed-base conditions. The study highlights the key influence of soil elastic properties on the first eigenfrequencies, which are the most commonly used in dynamic model updating. In addition, the model updating process results provide strong evidence of the critical role that Soil Structure Interaction (SSI) plays in achieving reliable structural models. These results underscore the importance of considering soil deformability in designing structural health monitoring systems and updating dynamic models based on experimental eigenfrequencies.
2025
Bartolini, G.; De Falco, A.; Landi, F.; Resta, C.; Vignali, L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1320827
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