Abstract

In conventional design approaches, structural safety is assessed without considering extreme load conditions that may cause global system collapse as a consequence of local failures in a component or localized portion of the structure. Even when extreme conditions are taken into account, structural safety is not probabilistically assessed and controlled, thus neglecting uncertainties in loads and system capacity. A few studies have been carried out so far, emphasizing the need for probabilistic risk assessment and management of structures to disproportionate (or progressive) collapse. To this aim, fragility analysis may be used to predict the probability of progressive collapse given that local damage has occurred. This approach is a well-established tool in earthquake engineering and explicitly accounts for uncertainties in both demand and capacity, providing the probability of failure as a function of a given intensity measure.In this paper, fragility functions for low-rise reinforced concrete (RC) framed building structures are presented to be implemented in progressive collapse risk assessment. Two building classes representative of European buildings designed for gravity loads and earthquake resistance in accordance with Eurocodes 2 and 8, respectively, were investigated. Fiber-based finite element (FE) models were developed and integrated with numerical techniques able to simulate the removal of first-story columns within an open source platform. Nonlinear response, resisting mechanisms and damage patterns under sudden column loss scenarios were reproduced at both local and global structural levels. Based on statistics and probability distribution functions for geometry, material properties and loads of the case-study building classes, Monte Carlo simulation was performed to generate random realizations of structural models. Fragility functions at multiple damage states show a significant influence of both seismic design/detailing and secondary beams on robustness of the case-study RC building classes.

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