Model Updating of Cultural Heritage Buildings Through Swarm Intelligence Algorithms

Abstract

Masonry buildings constitute a great Italian historical and cultural heritage, but they were also severely damaged by earthquakes over the centuries. Therefore, to assess their structural and seismic performance, it is crucial to gain a refined and trustworthy numerical model adopting model updating techniques, sometimes based on artificial intelligence algorithms. This article deals with the development and the updating of a finite element model of an historical church that account for the presence of both the seismic damage and securing systems. The model updating is performed adopting the particle swarm optimization algorithm and is based on the comparison between numerical and experimental modal parameters, the latter achieved by an extensive dynamic test campaign. The obtained calibrated numerical model has been adopted to support the restoration work design, as well as the design of a structural health monitoring system that has been permanently installed on the church.