Damage scenario for L’Aquila area: a large-scale comparison with 7597 RC buildings post-earthquake data

Methods for seismic vulnerability assessment are a fundamentally important tool for the identification and delimitation of seismic-prone areas and to plan seismic risk reduction and management strategies. They allow the derivation of event scenarios describing the expected consequences of the event, leading to estimates of people involved, dead or injured; damage to facilities and structures; and the number of unusable buildings and homeless people. In present work, a simplified mechanical method – PushOver on Shear Type models (POST) – for seismic vulnerability assessment of infilled RC building is briefly recalled (Del Gaudio et al., 2015; Del Gaudio et al., 2016a; Del Gaudio et al., 2017). The methodology allows the definition of building structural characteristic through a simulated design procedure in compliance with design code prescriptions, professional practice and seismic classification of the area of interest at the time of construction. The evaluation of non-linear static response is performed through a simplified model, considering the contribution of both RC columns and infill panels to lateral resistance, based on Shear Type assumption. Seismic capacity assessment is made in the SPO2IDA framework (Vamvatsikos and Cornell, 2006) for different performance levels, defined according to the damage classification proposed by European Macroseismic Scale (Grünthal, 1998). Finally, the use of a Monte Carlo simulation approach allows the derivation of fragility curves for different damage states (DSs). Therefore, predicted damage scenario is derived from POST methodology for a database consisting of 7597 Moment Resisting Frame (MRF) residential RC buildings located in the Abruzzi region, which after the 2009 catastrophic earthquake have been charged to post-earthquake usability assessment procedure (Del Gaudio et al., 2016b). Predicted damage scenario is then compared with damage scenario based on post-earthquake data.