Abstract
This paper presents a novel method for rapidly addressing the earthquake-induced damage identification task in historic masonry towers. The proposed method, termed DORI, combines operational modal analysis (OMA), FE modeling, rapid surrogate modeling (SM) and non-linear Incremental dynamic analysis (IDA). While OMA-based Structural Health Monitoring methods using statistical pattern recognition are known to allow the detection of small structural damages due to earthquakes, even far-field ones of moderate intensity, the combination of SM and IDA-based methods for damage localization and quantification is here proposed. The monumental bell tower of the Basilica of San Pietro located in Perugia, Italy, is considered for the validation of the method. While being continuously monitored since 2014, the bell tower experienced the main shocks of the 2016 Central Italy seismic sequence and the on-site vibration-based monitoring system detected changes in global dynamic behavior after the earthquakes. In the paper, experimental vibration data (continuous and seismic records), FE models and surrogate models of the structure are used for post-earthquake damage localization and quantification exploiting an ideal subdivision of the structure into meaningful macroelements. Results of linear and non-linear numerical modeling (SM and IDA, respectively) are successfully combined to this aim and the continuous exchange of information between the physical reality (monitoring data) and the virtual models (FE models and surrogate models) effectively enforces the Digital Twin paradigm. The earthquake-induced damage identified by both data-driven and model-based strategies is finally confirmed by in-situ visual inspections.
Highlights
Several methods have been validated in the literature for earthquake-induced damage identification, aimed at the preventive conservation of historic masonry buildings
This paper proposes a new method for damage detection, localization and quantification in long-term monitored historic masonry towers subjected to earthquakes
The results demonstrate that the proposed method enables a rapid post-earthquake damage identification, allowing to immediately detect the presence of damage and to subsequently localize and quantify it with an acceptable level of confidence in different macrostructural elements
Summary
Several methods have been validated in the literature for earthquake-induced damage identification, aimed at the preventive conservation of historic masonry buildings. The research carried out in (Kita et al 2020) proposed the use of an IDA-based approach for damage localization and quantification in the case of a laboratory low-rise masonry structure Effective on such a scaled-down model, the application of the method in full-scale masonry structures that have experienced real earthquake-induced damage has not yet been explored. This paper proposes a new method for damage detection, localization and quantification in long-term monitored historic masonry towers subjected to earthquakes It firstly relies on the data-driven OMA-based approach for a rapid and automated damage detection. The combination of two independent innovative methods is proposed for damage localization and quantification: (i) SM-based damage identification and (ii) IDA-based damage identification With the former relying on linear numerical modeling and long-term vibration monitoring data, and the latter on a non-linear modeling and seismic on-site response to earthquakes, their integration and cross-validation represent the pivot feature of this work.
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