A mechanics-based model for simplified seismic vulnerability assessment of masonry bell towers. (1st November 2022) - Chisari, Corrado; Cacace, Daniela; De Matteis, Gianfranco
Graphical abstract: Highlights: Extensive survey on bell towers in Naples was carried out. Parametric structural modelling of masonry bell towers was created. A vulnerability index is defined as a function of a collapse measure. Global sensitivity analysis highlighted influential parameters on seismic vulnerability. A simplified model with six parameters can achieve good accuracy. Abstract: The safeguard of historical heritage cannot disregard a rational assessment of the seismic vulnerability of the assets, especially in areas as Italy where high exposure and hazard may lead to significant risk. In this context, while established empirical methods based on observed damage after earthquakes are available for some constructional typologies as churches and palaces, large-scale approaches for masonry bell towers aimed at defining a vulnerability ranking for prioritisation of intervention are still missing or not sufficiently validated. In this paper, a novel simplified vulnerability model is formulated through sensitivity-informed parameter reduction of a more detailed mechanics-based assessment methodology. The framework is based on (a) a parametric representation of the bell tower, (b) a mechanical model providing a measure of collapse, (c) a vulnerability definition based on the measure of collapse. The variation ranges of the input parameters are calibrated against the results of the surveys carried out in the historical centre of Naples. A global sensitivity analysis is then used to identify the most important parameters governing the vulnerability of the structure and remove the least influential parameters. Vulnerability models based on different amount of input data are finally proposed, and their accuracy is assessed comparatively with the original mechanical model. The results show that good accuracy can be obtained by using six geometrical and typological parameters, while further increase in the quality of the prediction may be achieved with the introduction of additional information regarding materials and constructional features, which can only be acquired by means of more detailed surveys on-site.