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Probabilistic seismic demand model for curved reinforced concrete bridges

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Abstract

This article examines the seismic behaviour of curved box-girder concrete highway overpass bridges commonly built in California. In particular, a probabilistic seismic demand model for curved 5-span reinforced concrete box-girder bridges with single circular column bents is developed. The principal parameter of the demand model is the bridge curve radius in the horizontal plane, varying from infinity (representing a straight bridge) to a sharp curve radius equal to the length of the bridge. Three bridge prototypes are analyzed: (1) a tall-column bridge with relatively low lateral stiffness; (2) a bridge commonly designed in California and (3) a short-column bridge with high lateral stiffness. A probabilistic seismic demand analysis, including a modal analysis and an evaluation of the nonlinear static and dynamic response, are performed for each bridge prototype and each radius value. The magnitude-distance bin approach is used to cover a range of plausible ground motion scenarios. The probabilistic demand models are cast in terms of one engineering demand parameter, the bridge drift ratio, and two intensity measures: the peak ground displacement or velocity, and the spectral displacement at the fundamental period of the bridge, S d (T 1). The demand models show an increase in transverse-direction drift ratio demand for sharply curved bridges.

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Authors and Affiliations

  1. Department of Mechanical and Structural Engineering, University of Trento, via Mesiano 77, 38123, Trento, Italy

    Nicola Tondini

  2. Department of Civil, Environmental and Geomatics Engineering, Institute of Structural Engineering, ETH Zurich, Wolfgang-Pauli-Str. 15, 8093, Zurich, Switzerland

    Bozidar Stojadinovic

Authors
  1. Nicola Tondini
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  2. Bozidar Stojadinovic
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Correspondence to Nicola Tondini.

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Tondini, N., Stojadinovic, B. Probabilistic seismic demand model for curved reinforced concrete bridges. Bull Earthquake Eng 10, 1455–1479 (2012). https://doi.org/10.1007/s10518-012-9362-y

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  • DOI: https://doi.org/10.1007/s10518-012-9362-y

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