Abstract
Seismic risk assessment has become a crucial issue for optimal management of economic resources allocated to mitigation. For this purpose, in the last decades, several research activities were aimed to update hazard, exposure, and vulnerability models that contribute to seismic risk assessment. From this perspective, the present work focuses on developing new empirical damage fragility curves for census-based typological unreinforced masonry buildings. In particular, damage data observed after the 2009 L’Aquila earthquake, Italy, related to almost 57,000 residential buildings, were used to calibrate the fragility functions. These data were complemented with the census data with the aim of obtaining an accurate estimation of the number of undamaged buildings. Damage fragility curves were identified for typological building classes, defined considering parameters present in both post-earthquake observations and census data with the aim of extending the results to the whole national territory. Six typological classes were defined considering the categories of the construction timespan and of the state of repair parameters. Then, a further distinction of the typological classes considering the number of stories parameter was included where relevant. The fragility curves were defined as a function of peak ground acceleration for five damage states, defined according to the European macroseismic scale. The results confirmed that older buildings are more vulnerable than newer ones and highlighted the crucial role of the state of repair on the damage fragility curves. Finally, the new set of damage fragility functions was uploaded in the Italian Risk Maps information technology platform, used by the Civil Protection Department for risk evaluation, as an exemplification of the potential application of the fragility curves.
Highlights
In the last few decades, different significant earthquakes of medium magnitude occurred in Italy, underlining the great vulnerability of existing buildings stock [1,2,3]
Combining the categories of the two selected parameters the six typological classes shown in Table 2 are obtained, for which an ID is defined as a function of the category assigned to each parameter, TxRy, where letter T is associated to construction timespan (i.e., T1 for < 1919; T2 for 1919–1961; T3 for >1961); and letter R is associated to the state of repair (R1 for Excellent and Good—D0 and D1 < 1/3, and R2 for Mean and Poor— D1 > 1/3, D2–D4)
There is a sheer interest in developing earthquake damage fragility curves for classes of buildings whose definition is based on parameters available in the census inventory
Summary
In the last few decades, different significant earthquakes of medium magnitude occurred in Italy, underlining the great vulnerability of existing buildings stock [1,2,3]. Among the different vulnerability models available in the literature, empirical fragility curves, based on observed damage, are largely widespread in Italy thanks to the recent publication of the data collected after the most relevant Italian earthquakes occurred in the last fifty years by the Civil Protection department throughout the DaDO (Observed Damage Database) platform [16,17]. The empirical models are defined for typological building classes [2,18,21,34] or considering a vulnerability index as a function of different structural parameters [25,26,27,35,36]. The typological building classes were defined considering the information available in both damage and census databases with the aim to use the fragility curves to derive damage scenarios in different areas of the national territory. Fragility curves were used to simulate damage risk maps within the IRMA platform for all the municipalities of the Abruzzo region
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