Empirical fragility curves for Italian residential RC buildings

Abstract

In this paper, empirical fragility curves for reinforced concrete buildings are derived, based on post-earthquake damage data collected in the aftermath of earthquakes occurred in Italy in the period 1976–2012. These data, made available through an online platform called Da.D.O., provide information on building position, building characteristics and damage detected on different structural components. A critical review of this huge amount of data is carried out to guarantee the consistency among all the considered databases. Then, an in-depth analysis of the degree of completeness of the survey campaign is made, aiming at the identification of the Municipalities subjected to a partial survey campaign, which are discarded from fragility analysis. At the end of this stage, only the Irpinia 1980 and L’Aquila 2009 databases are considered for further elaborations, as fully complying with these criteria. The resulting database is then integrated with non-inspected buildings sited in less affected areas (assumed undamaged), to account for the negative evidence of damage. The PGA evaluated from the shakemaps of the Italian National Institute of Geophysics and Volcanology (INGV) and a metric based on six damage levels according to EMS-98 are used for fragility analysis. The damage levels are obtained from observed damage collected during post-earthquake inspections through existing conversion rules, considering damage to vertical structures and infills/partitions. The maximum damage level observed on vertical structures and infills/partitions is then associated to the whole building. Fragility curves for two vulnerability classes, C2 and D, further subdivided into three classes of building height, are obtained from those derived for specific structural typologies (identified based on building height and type of design), using their frequency of occurrence at national level as weights.

Comparative analysis of the fragility curves for Italian residential masonry and RC buildings

“…Among the masonry fragility models, one has a mechanical derivation (Donà et al 2020), one is based on an empirical-heuristic approach (Lagomarsino et al 2021) and the other two have an empirical derivation (Rosti et al 2020a;Zuccaro et al 2020). Regarding the models for RC buildings, one is developed on a mechanical basis (Borzi et al 2020b) and the other on an empirical basis (Rosti et al 2020b). The criteria behind these models and the relevant state of art for their derivation is presented in the above-mentioned papers.…”

“…Similarly, Figs. 7 and 8 present the fragility models proposed for residential RC buildings, three height classes and two vulnerability classes, C2 and D. Regarding RC buildings, a second version of the model by Rosti et al (2020b) was also introduced and compared. This version better represents the specific scenario of L'Aquila (as well as that of Amatrice), as will be discussed below.…”

Fragility Estimation for Global Building Classes Using Analysis of the Cambridge Earthquake Damage Database (CEQID)

“…Peak ground acceleration (PGA) obtained from the USGS shakemap archives (Wald et al, 2008), was chosen to characterize the ground motion. The relationship between PGA and probability of damage is represented with a cumulative lognormal relationship, as nowadays very widely adopted (Kappos et al, 2006;Polidoro and Spence, 2015). A lognormal fragility function assumes that the logarithm of the PGA at which a building gets damaged is normally distributed, with mean value here de ned as lnµ and standard deviation σ.…”

Seismic Loss Estimation in Pre-1970 Residential RC Buildings: The Role of Infills and Services in Low–Mid-Rise Case Studies

“…In fact, the main approaches for loss estimation developed in Italy since the end of the 80s (Guagenti et al, 1988;Yang et al, 1989;Colonna et al, 1994;Bramerini et al, 1995;Di Pasquale and Orsini, 1998;Di Pasquale et al, 2005) make use of the empirical Damage Probability Matrix (DPMs), discarding the contribution of infills on damage estimation of RC buildings, to account for expected annual loss through the use of suitable damage factor (DF) coefficients. Only recently, Dolce et al (2019) develop seismic risk maps for Italy, taking advantage of the use of fragility curves for RC buildings (Rosti et al, 2020) and also explicitly accounting for infill contribution in damage evaluation.…”