Recent earthquakes have exposed the vulnerability of existing buildings; this is demonstrated by damage incurred after moderate-to-high magnitude earthquakes. This stresses the need to exploit available data from different sources to develop reliable seismic risk components. As far as it regards empirical fragility assessment, accurate estimation of ground-shaking at the location of buildings of interest is as crucial as the accurate evaluation of observed damage for these buildings. This implies that explicit consideration of the uncertainties in the prediction of ground shaking leads to more robust empirical fragility curves. In such context, the simulation-based methods can be employed to provide fragility estimates that integrate over the space of plausible ground-shaking fields. These ground-shaking fields are generated according to the joint probability distribution of ground-shaking at the location of the buildings of interest considering the spatial correlation structure in the ground motion prediction residuals and updated based on the registered ground shaking data and observed damage. As an alternative to the embedded coefficients in the ground motion prediction equations accounting for subsoil categories, stratigraphic coefficients can be applied directly to the ground motion fields at the engineering bedrock level. Empirical fragility curves obtained using the observed damage in the aftermath of Amatrice Earthquake for residential masonry buildings show that explicit consideration of the uncertainty in the prediction of ground-shaking significantly affects the results.

Empirical fragility assessment using conditional GMPE-based ground shaking fields: application to damage data for 2016 Amatrice Earthquake / Miano, A.; Jalayer, F.; Forte, G.; Santo, A.. - In: BULLETIN OF EARTHQUAKE ENGINEERING. - ISSN 1570-761X. - (2020). [10.1007/s10518-020-00945-6]

Empirical fragility assessment using conditional GMPE-based ground shaking fields: application to damage data for 2016 Amatrice Earthquake

Miano A.;Jalayer F.
;
Forte G.;Santo A.
2020

Abstract

Recent earthquakes have exposed the vulnerability of existing buildings; this is demonstrated by damage incurred after moderate-to-high magnitude earthquakes. This stresses the need to exploit available data from different sources to develop reliable seismic risk components. As far as it regards empirical fragility assessment, accurate estimation of ground-shaking at the location of buildings of interest is as crucial as the accurate evaluation of observed damage for these buildings. This implies that explicit consideration of the uncertainties in the prediction of ground shaking leads to more robust empirical fragility curves. In such context, the simulation-based methods can be employed to provide fragility estimates that integrate over the space of plausible ground-shaking fields. These ground-shaking fields are generated according to the joint probability distribution of ground-shaking at the location of the buildings of interest considering the spatial correlation structure in the ground motion prediction residuals and updated based on the registered ground shaking data and observed damage. As an alternative to the embedded coefficients in the ground motion prediction equations accounting for subsoil categories, stratigraphic coefficients can be applied directly to the ground motion fields at the engineering bedrock level. Empirical fragility curves obtained using the observed damage in the aftermath of Amatrice Earthquake for residential masonry buildings show that explicit consideration of the uncertainty in the prediction of ground-shaking significantly affects the results.
2020
Empirical fragility assessment using conditional GMPE-based ground shaking fields: application to damage data for 2016 Amatrice Earthquake / Miano, A.; Jalayer, F.; Forte, G.; Santo, A.. - In: BULLETIN OF EARTHQUAKE ENGINEERING. - ISSN 1570-761X. - (2020). [10.1007/s10518-020-00945-6]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/818049
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 22
  • ???jsp.display-item.citation.isi??? 15
social impact