4.6 Article

Model updating-based dynamic collapse analysis of a RC cable-stayed bridge under earthquakes

Journal

STRUCTURES
Volume 43, Issue -, Pages 1100-1113

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.istruc.2022.07.023

Keywords

Progressive seismic collapse; RC cable -stayed bridge; Measurement system; Nonlinear model updating; OpenSees; Shake table test

Funding

  1. Key Laboratory of Earthquake En- gineering Simulation and Seismic Resilience of China Earthquake Administration
  2. National Natural Science Foundation of China (NSFC) [51978513]

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This study proposes a general framework for progressive seismic collapse analysis of reinforced concrete bridges, and validates the efficiency and reliability of this framework through shake table tests and updating of finite element models.
This study proposes a general framework for progressive seismic collapse analysis of reinforced concrete (RC) bridges and it begins with an introduction of the progressive seismic collapse framework, which is mainly composed of five procedures. Subsequently, a 1:12 scale RC cable-stayed bridge together with the measurement system are presented, and the bridge model is subjected to a series of shake table tests. A conventional nonlinear finite element (FE) model, representing the undamaged condition of the cable-stayed bridge, is established, and the FE model is then nonlinearly updated based on the measured data from the measurement system when the bridge model is under small and moderate shake table excitations. The reliability of the updating process is validated through comparisons against another independent group of the measured data during the same moderate excitation. A more destructive ground motion is finally applied to the damaged FE model, where the progressive seismic collapse responses are obtained. The simulated seismic collapse responses based on the nonlinearly updated FE model give a good agreement with the measured data from the shake table tests employing the same destructive excitation, indicating that the model updating strategy proposed in this paper is efficient and reliable.

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