Comparison of different finite element model updates based on experimental onsite testing: the case study of San Giovanni in Macerata

Understanding the behavior of historic structures that have undergone structural changes, restorations, and damage over time is still a significant challenge for structural engineers, particularly in those countries subject to high seismic risk, such as Italy. The study of built heritage for its prevention and conservation is an active research topic, due to the numerous uncertainties present in historic structures. Finite element modelling has become the most common and accessible method to study the behavior of complex masonry structures, however, the gap between numerical and experimental analysis may lead to erroneous results. Model updating techniques can reduce the discrepancy between the behavior of the numerical models and the testing results. The goal of this work is to illustrate a methodology to integrate the information derived from local, global, and geotechnical investigations into the finite element model of the masonry historical church of San Giovanni in Macerata, considering the Douglas-Reid model updating method. The PRiSMa laboratory of Roma Tre University carried out local investigations such as sonic tomography, video endoscopy and double flat jack tests, along with five ambient vibration tests that were processed through the operational modal analysis to extrapolate the dynamic properties of the building (modal frequency, modal shape vector and modal damping). The combined use of global, local and geotechnical information implemented in the methodology effectively reduced the uncertainties of the model and led the refinement and validation of the most relevant structural parameters.

Automated summary

Studying the behavior of historic structures is a challenge for structural engineers, with finite element modeling being a common method. Model updating techniques help reduce discrepancies, and integrating local, global, and geotechnical information in the methodology effectively reduces uncertainties and validates structural parameters.