Modal-based FE model updating via genetic algorithms: Exploiting artificial intelligence to build realistic numerical models of historical structures

Cultural Heritage preservation requires the combination of in situ investigations and accurate Finite Elements models in order to correctly interpret the empirical evidence and successfully apply advanced structural analyses for health assessment purposes, allowing to infer about the future evolution of the structural response and timely detect deviations from the expected behaviour. In this paper the actual dynamic behaviour of the Civic Tower of Ostra, Italy, is thoroughly investigated by means of a detailed numerical model built and calibrated using the experimental modal features estimated through field dynamic testing. To this end, a fully automated Finite Element Model Updating procedure based on genetic algorithms and machine learning is conceived and employed, allowing the successful estimation of the unknown material properties of the tower, considering both isotropic and orthotropic behavioural models for masonry. The results enabled to establish baseline information on the current structural condition of the heritage and to set performance standards that will serve to optimise the control of the structural integrity over time.

Automated summary

Preserving cultural heritage requires a combination of in situ investigations and accurate Finite Elements models to interpret empirical evidence, assess structural health, and detect deviations in behavior. This study thoroughly investigates the dynamic behavior of the Civic Tower of Ostra, Italy, using detailed numerical models and experimental modal features, allowing for the estimation of unknown material properties and establishment of performance standards for optimizing structural integrity over time.