A class-oriented mechanical approach for seismic damage assessment of RC buildings subjected to the 2009 L’Aquila earthquake

Abstract

The simplified mechanical method POST (PushOver on Shear Type models) for seismic vulnerability assessment of RC buildings is used in this study to derive damage scenarios for a database of 7597 RC buildings subjected to the 2009 L’Aquila earthquake. POST allows the evaluation of fragility curves through the determination of the non-linear static response of RC buildings in closed form, assuming the hypothesis of shear type behaviour, and considering the influence of infill panels both in the derivation of structural response and in assessment of building damage, which is defined according to the European Macroseismic Scale EMS-98. The aim of the present study is to provide a much more significant and reliable validation of the methodology, thanks to a much wider database compared to previous studies, and based on a different application of the methodology, i.e. at building class-level instead of single building-level. To this aim, the main geometrical-typological characteristics of the analysed buildings (number of storeys, age of construction, building area) have been statistically characterized based on data collected from post-earthquake AeDES survey forms, considering both the variability of each single parameter and the correlation that exists between one parameter and the other. This also allows to analyse the effectiveness of the adopted analytical procedure in predicting the general trends of observed damage with these parameters, showing a good agreement between observed and predicted trends. The overall predicted damage scenarios are compared with the corresponding observed ones, collected from AeDES survey forms, highlighting, again, a good agreement. Finally, the assumed mechanical interpretation of damage classification of EMS-98 is validated through the comparison between the distributions of damage to vertical structures and infill panels and the corresponding observed post-earthquake damage data.