Seismic fragility of Italian RC precast industrial structures

• Fragility curves for Italian RC precast industrial buildings were developed.
• An analytical method using dynamic analyses in 2D and 3D environment was employed.
• Beam–column connection failure was explicitly accounted for as collapse limit state.
• Collapse fragility curves are dominated by connection failure mechanism.
• Vertical input in dynamic analyses is critical for connection collapse evaluation.

Despite the moderate ground motions observed during the seismic events in Northern Italy, May 2012, reinforced concrete (RC) precast industrial buildings suffered excessive damage, which led to substantial direct and indirect losses. The aim of this paper is to present a seismic fragility model for Italian RC precast buildings, to be used in earthquake loss estimation and seismic risk assessment. An analytical methodology has been used that consists of (1) random sampling of one hundred structures for each building typology, (2) pushover analysis to establish a number of damage limit states, (3) execution of nonlinear dynamic analysis and comparison of the maximum demand with the limit state capacity to allocate the structure in a damage state, and (4) regression analysis on the cumulative percentage of buildings in each damage state for a set of intensity measure levels to derive the statistical parameters of the fragility functions. The building population employed in the analysis was generated considering both material and geometric variability that was obtained from the field surveys of 650 industrial facilities, as well as other information available in the literature. Several aspects of the fragility derivation process were further analysed, such as the correlation between different intensity measure types and damage, the consideration of different collapse mechanisms (e.g. beam–column connection failure) and the differences in the resulting fragility curves when adopting a 2D or a 3D modelling environment. A good agreement with preliminary empirical fragility functions based on field data was also observed.