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Empirical fragility curves: The effect of uncertainty in ground motion intensity

Ioannou, I; Chandler, RE; Rossetto, T; (2020) Empirical fragility curves: The effect of uncertainty in ground motion intensity. Soil Dynamics and Earthquake Engineering , 129 , Article 105908. 10.1016/j.soildyn.2019.105908. Green open access

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Abstract

Empirical fragility curves derived from large post-disaster databases with data aggregated at municipality-level, commonly make the assumption that the ground motion intensity level is known and is determined at the centroid of each municipality from a ground motion prediction equation. A flexible Bayesian framework is applied here to the 1980 Irpinia database to explore whether more complex statistical models that account for sources of uncertainty in the intensity can significantly change the shape of the fragility curves. Through this framework the effect of explicitly modelling the uncertainty in the intensity, the spatial correlation of its intra-event component and the uncertainty due to the scatter of the buildings in the municipality are investigated. The analyses showed that the results did not change substantively with increased model complexity or the choice of prior. Nonetheless, informed decisions should be based on the defensible modelling of the significant variability in the data between municipalities.

Type: Article
Title: Empirical fragility curves: The effect of uncertainty in ground motion intensity
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.soildyn.2019.105908
Publisher version: https://doi.org/10.1016/j.soildyn.2019.105908
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10085692
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