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Defining a Masonry Building Inventory for the City of Potenza

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

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Abstract

The seismic vulnerability assessment of masonry built heritage is an importance issue in Italy, due to the high seismic hazard of the territory and the huge amount of masonry buildings located in the exposed areas. The evaluation of the seismic performance of buildings can be useful to assess possible damages occurred after an earthquake, the direct costs which would result from it, the “pre” and “post” loss distribution in an urban area and the most vulnerable buildings. At urban scale, a building-specific assessment approach appears extremely difficult and time-consuming because of the large number of constructions. Therefore, being able to classify the built heritage in a limited number of territorial-specific structural typologies with similar characteristics would significantly simplify the vulnerability assessment.

This paper shows a typological and structural classification of existing masonry buildings of the historic center of Potenza (south of Italy) aimed at designing a virtual city consisting of different buildings categories. The main typological and structural features of the masonry constructions (MUR) have been identified through documentary analyses, Census data, site investigation and GIS-based analysis by considering the frequency of significant structural parameters. This represents the starting point of a comprehensive research study, carried out within the PON-AIM 2014–2020 project, aimed at the evaluation of the seismic resilience of the investigated area.

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Acknowledgements

This research was funded by the PON-AIM 2014–2020 project supported by the Italian Ministry of University and Public Instruction.

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Correspondence to Chiara Iacovino .

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Iacovino, C., Flora, A., Cardone, D., Vona, M. (2020). Defining a Masonry Building Inventory for the City of Potenza. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12250. Springer, Cham. https://doi.org/10.1007/978-3-030-58802-1_65

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  • DOI: https://doi.org/10.1007/978-3-030-58802-1_65

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-58802-1

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