Probabilistic Digital Twin Development of the Historic “Ponte delle Torri” Masonry Bridge Using Long-Term Monitoring Data

This study presents a probabilistic - based digital twin for the “Ponte delle Torri” masonry bridge, using one year of continuous monitoring data including acceleration time histories, displacement records, load-cell measurements, and temperature time histories. The “Ponte delle Torri” is an historic masonry bridge of considerable cultural and structural significance featuring a multi-arched configuration with ten spans. A simplified Finite Element (FE) model is developed to reproduce the structure global behavior. The piers are replaced by equivalent linear springs, whose stiffness values are treated as uncertain parameters to be inferred. This modeling approach allows an efficient representation of the interaction between the structure and its supports in a computationally efficient form, while maintaining the essential mechanical behavior. This probabilistic framework allows to explicitly consider multiple data sources simultaneously. Dynamic features such as natural frequencies and mode shapes extracted from acceleration measurements are combined with static displacement data and their correlation with temperature effects. The monitoring data are used to update the uncertain mechanical parameters of the model and to simulate potential structural damage scenarios. This integrated formulation explicitly accounts for measurement and modelling uncertainties, providing a physically consistent and data-informed representation of the bridge’s structural behaviour over time.