Central Italy Earthquakes occurred in 2016 pointed out once more the vulnerability of Cultural Heritage (CH), especially for what concerns bell-towers since they tend to get dramatically damaged due to their considerable slenderness and deterioration, endangering their surroundings and making their preservation fundamental. This work presents the results of the study carried out on four different isolated masonry bell towers, located in Ferrara province (Italy); the parameters of the materials were deduced by calibrating Finite Element Models (FEMs) using the data collected during an investigation campaign conducted with a wired accelerometric sensor system, since it was not possible to apply destructive methodologies. Dynamic data were extracted through the application of two Operational Modal Analysis (OMA) identification techniques: the Enhanced Frequency Domain Decomposition (EFDD) and the Stochastic Subspace Identification (SSI) methodology. Particular attention was devoted to the use of MAC matrix in the validation of the mode shapes results.

Model Updating of Historical Belfries Based on Oma Identification Techniques

Standoli, G.;Giordano, E.;Clementi, F.
2021

Abstract

Central Italy Earthquakes occurred in 2016 pointed out once more the vulnerability of Cultural Heritage (CH), especially for what concerns bell-towers since they tend to get dramatically damaged due to their considerable slenderness and deterioration, endangering their surroundings and making their preservation fundamental. This work presents the results of the study carried out on four different isolated masonry bell towers, located in Ferrara province (Italy); the parameters of the materials were deduced by calibrating Finite Element Models (FEMs) using the data collected during an investigation campaign conducted with a wired accelerometric sensor system, since it was not possible to apply destructive methodologies. Dynamic data were extracted through the application of two Operational Modal Analysis (OMA) identification techniques: the Enhanced Frequency Domain Decomposition (EFDD) and the Stochastic Subspace Identification (SSI) methodology. Particular attention was devoted to the use of MAC matrix in the validation of the mode shapes results.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11566/274078
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