Typological Inventory of Residential Reinforced Concrete Buildings for the City of Potenza

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Abstract

The seismic vulnerability assessment of the built heritage located on a specific area represents an important starting point for both the evaluation of the consequences in the aftermath of significant seismic events and a proper management of the post-seismic reconstruction phase. In other words, the vulnerability assessment represents one of the main input elements for resilience analysis at urban scale. However, facing with a large-scale study, a building-specific assessment approach appears extremely difficult and time-consuming. In this optic, the definition of territorial-specific structural typologies and corresponding vulnerability classes represent a powerful tool for a rapid estimation of the “global vulnerability” of an examined area. As a matter of fact, the classification of the built heritage in a limited number of structural typologies (featuring similar characteristics) could sensibly reduce the complexity of the vulnerability assessment, hence resilience analysis, at urban scale. In this paper, an investigation on the built heritage of the city centre of Potenza (south of Italy) is proposed. In particular, the main typological and structural features of the residential Reinforced Concrete (RC) constructions, detected in the investigated territory, have been identified through an integrated approach involving: Census data, documentary analyses, site and virtual inspections (i.e. GIS-based analysis). The typological-structural characterization represents the first step of a comprehensive study, carried out within the PON-AIM 2014–2020 project, aimed at the evaluation of the seismic resilience of the examined area.

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Flora, A., Iacovino, C., Cardone, D., & Vona, M. (2020). Typological Inventory of Residential Reinforced Concrete Buildings for the City of Potenza. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12250 LNCS, pp. 899–913). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-58802-1_64

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