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Journal Article

Citation

Ortega J, Vasconcelos G, Rodrigues H, Correia M, Ferreira TM, Vicente R. Int. J. Disaster Risk Reduct. 2019; 39: e101242.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.ijdrr.2019.101242

PMID

unavailable

Abstract

The paper presents and discusses the application of two large scale seismic vulnerability assessment methods on the island of Faial in Azores (Portugal). The two methods are specifically conceived to assess the seismic vulnerability of vernacular architecture. The first method follows a classical seismic vulnerability index approach and is referred as SVIVA (Seismic Vulnerability Index for Vernacular Architecture). The second method is referred as SAVVAS (Seismic Assessment of the Vulnerability of Vernacular Architecture Structures) and it is a numerical tool intended to estimate the seismic capacity of vernacular buildings in terms of seismic load factors associated with different structural damage limit states. The main reason behind the selection of Faial Island as a case study was the availability of post-earthquake reports of the building stock after the 1998 Azores earthquake, which allowed comparing the damage scenarios obtained using both methods with the post-earthquake damage data and thus helped for the calibration and validation of the two methods. The application of both methods led to a good fit between estimated versus observed damage grades, which validated their applicability as large-scale first level approaches. Moreover, as the main outcome, the paper presents the novelties of the SAVVAS method, which had not been applied before, and discusses its main advantages, namely: no need for calibration with previous post-earthquake damage data, an enhancement of the prediction capabilities, a more individualized evaluation of the buildings and the possibility to assess the seismic performance of the building in different loading directions.


Language: en

Keywords

1998 Azores earthquake; Seismic vulnerability assessment; Stone masonry; Vernacular architecture; Vulnerability index

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