%0 Generic
%A Minas, S
%A Sousa, L
%A Galasso, C
%A Rossetto, T
%C Thessaloniki, Greece
%D 2018
%F discovery:10069016
%I EAEE
%K Seismic risk; Fragility curves; Seismic hazard; FRACAS; Portfolio loss
%P 11276
%T Sensitivity of Probabilistic Regional Seismic Loss to Hazard and Vulnerability Modelling Options
%U https://discovery.ucl.ac.uk/id/eprint/10069016/
%X This paper investigates the sensitivity of probabilistic regional seismic loss assessment of reinforced concrete  (RC) buildings to different ground motion intensity and vulnerability modelling options. To this aim, several  variations of the loss assessment framework are tested to determine their effect in the resultant damage  prediction, and the consequent loss estimation. Specifically, this study systematically assesses the sensitivity of  losses to (1) ground motion intensity characterization (through selection of different types of intensity measures -  IMs); and (2) assumptions in structural analysis (simplified nonlinear static-based procedures versus advanced  nonlinear time-history analysis).  A synthetic portfolio of RC structures located in Avellino, Southern Italy, is chosen as a case-study. A sitespecific hazard analysis is carried out, allowing the calculation of ground shaking footprints for different types of  IMs, including conventional and advanced IM representations. Three regular 4-storey, 4-bay RC bare frame  buildings, corresponding to three distinct vulnerability classes, compose the exposure database. Seismic fragility  and vulnerability functions are derived for the considered building typologies, and finally, economic earthquake  losses are estimated for all tested ground motion IMs and fragility derivation methods.  Results from this study highlight that the choice of the analysis method type has a significant impact in the  overall loss estimation, as the proposed (more advanced) procedure is capable of capturing the building response  and corresponding damage states more accurately. The choice of the IM type is also of high importance within  the loss estimation process, due to the ability of advanced IMs to capture more information than standard IM,  e.g. in terms of spectral shape.
%Z This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.