USING DIFFERENT UNCERTAINTY MODELS FOR SEISMIC ASSESSMENT OF RC BRIDGES

Abstract eng:
The seismic assessment of structures depends on a large number of aleatory and epistemic uncertainties, which are majorly associated to the estimation of the structural demand and capacity, both usually featuring considerable dispersion levels, particularly when reinforced concrete structures are being assessed. When focusing on bridges, additional complexity may be introduced by the irregular behaviour in the transverse direction. Several procedures may be used for the assessment of the seismic safety of bridges, deterministic or probabilistic, and all rely on an accurate prediction of the demand, obtained via linear or nonlinear static or dynamic analysis. This work employs both static and dynamic analysis methods for demand estimation within a relatively straightforward framework to compute the failure probability of existing bridges. Different variables typically considered in a seismic assessment procedure (geometry, material properties, earthquake records, intensity level) are statistically characterized, catering for a global simulation process, where each iteration step is associated to an independent structural nonlinear static or dynamic analysis. Failure probability is then obtained through different uncertainty models, corresponding to the convolution of capacity and demand distributions or the probabilistic analysis of a safety indicator, defined as the difference between capacity and demand at each random simulation realisation. A case study of seven bridge configurations, with different (ir)regularity levels, is considered together with a relatively large set of real earthquake records. The simulation process is carried out using Latin Hypercube sampling, expected to considerably reduce the number of realizations with no reliability loss. Conclusions have allowed the identification of vulnerable configurations and shown the differences in considering different uncertainty models.

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