Bayesian model updating of historic masonry towers through dynamic experimental data

A Bayesian approach successfully updates finite element models of historic masonry towers, addressing critical uncertainties in material properties and geometry. Using dynamic experimental data from San Gimignano's towers, the study refines numerical models by incorporating measured natural periods and accounting for measurement errors and modeling uncertainties, such as restraint effects from neighboring buildings. This method enhances seismic risk assessment, a key factor in preserving cultural heritage. The findings highlight the potential of Bayesian model updating to improve structural analysis in historic masonry towers, with future applications extending to seismic studies.

Bartoli, G., Betti, M., Facchini, L., Marra, A. M., & Monchetti, S. (2017). Bayesian model updating of historic masonry towers through dynamic experimental data. Procedia Engineering, 199, 1258–1263. https://doi.org/10.1016/j.proeng.2017.09.267