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Detailed Structural Characterization of Existing RC Buildings for Seismic Exposure Modelling of the Lisbon Area

Author(s):
ORCID
ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 5, v. 12
Page(s): 642
DOI: 10.3390/buildings12050642
Abstract:

As many European countries, the Portuguese territory is a region of moderate seismicity, and a large part of its building stock includes reinforced concrete (RC) buildings built before the introduction of modern seismic codes (<1983s). Currently, the Lisbon building stock is composed of 45% of RC buildings, of which 71% were built in such a construction period. Being designed to only sustain gravitational loads and without adequate lateral load resistance, these buildings are likely to be severely damaged during an earthquake. This highlights the need to propose reliable seismic risk assessment and earthquake loss models for such structures. In this context, the development of an exposure model which quantifies the building stock susceptible to be seismically damaged, in terms of structural characteristics, spatial location, and occupancy, is of major importance. The main purpose of this paper is to contribute the definition of a building exposure model for the city of Lisbon, focusing on a detailed structural characterization of these typologies. It starts with an extensive collection and analysis of design blueprints of existing buildings in two Lisbon’s neighborhoods: Alvalade and Benfica, which were found to be representative of the RC building stock in the city. Then, the information collected is scrutinized and statistically post-processed through probability distributions that provide a clear insight on the RC typologies and their structural characteristics. These results can be used in the future for the development of a numerical models and to derive fragility and vulnerability models, fundamental to conducting seismic risk analyses.

Copyright: © 2022 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10679431
  • Published on:
    18/06/2022
  • Last updated on:
    10/11/2022
 
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