This study focuses on identifying, both qualitatively and quantitatively, the seismic behavior of reinforced concrete bridges with seat-type abutments under earthquake loading, especially with respect to abutment skew angle. To that end, the study proposes novel methodologies for modeling skew-angled seat-type abutments and for seismic response assessment of structures whose response is characterized as "multi-phased." The proposed methodologies are applied to a comprehensive database of bridges with combinations of a variety of bridge geometric properties, including: (1) number of spans; (2) number of columns per bent; (3) column-bent height; (4) span arrangement; and (5) abutment skew angle. An extensive nonlinear response history analysis was conducted using three sets of ground motions representing records for rock sites and soil sites, as well as others that contained pronounced velocity pulses, denoted as "pulse-like.";We demonstrate that demand parameters for skew-abutment bridges, such as deck rotation, abutment unseating, and column drift ratio, are higher than those for straight bridges. By investigating the sensitivity of various response parameters to variations in bridge geometry and ground motion characteristics, we show that bridges with larger abutment skew angles bear a higher probability of collapse due to excessive rotation, and that shear keys can play a major role in reducing deck rotations and thus the probability of collapse. We further show that resultant peak ground velocity (PGVres) is the most efficient ground motion intensity measure (IM) compared to many other IMs.;In view of the skewed bridges' explicit changes in demand parameter behavior due to shear key failure, we propose a probabilistic-based approach for multi-phase structural response assessment. This method, denoted as "Multi-Phase Probabilistic Assessment of Structural Response to Seismic Excitations," or M-PARS, provides a probabilistic framework for computing the complementary probability distribution function of an engineering demand parameter given the ground motion intensity measure, G(EDP|IM)
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