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Bayesian model updating of a large-span steel tied arch bridge: an experimental study

 Bayesian model updating of a large-span steel tied arch bridge: an experimental study
Auteur(s): , , , ORCID
Présenté pendant IABSE Congress: Structural Engineering for Future Societal Needs, Ghent, Belgium, 22-24 September 2021, publié dans , pp. 475-480
DOI: 10.2749/ghent.2021.0475
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In this paper, a large-span steel tied arch bridge's Bayesian FEMU is carried out based on the ambient vibration data. Firstly, the ERA method is used for modal identification. Then, the benchmark ...
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Détails bibliographiques

Auteur(s): (Department of Bridge Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China)
(Department of Bridge Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China)
(Department of Bridge Engineering, College of Civil Engineering, Tongji University, Shanghai 200092, China)
ORCID (State Key Laboratory for Disaster Reduction in Civil Engineering, Tongji University, Shanghai, 200092, China‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌‌)
Médium: papier de conférence
Langue(s): anglais
Conférence: IABSE Congress: Structural Engineering for Future Societal Needs, Ghent, Belgium, 22-24 September 2021
Publié dans:
Page(s): 475-480 Nombre total de pages (du PDF): 6
Page(s): 475-480
Nombre total de pages (du PDF): 6
DOI: 10.2749/ghent.2021.0475
Abstrait:

In this paper, a large-span steel tied arch bridge's Bayesian FEMU is carried out based on the ambient vibration data. Firstly, the ERA method is used for modal identification. Then, the benchmark FE model of this bridge is established. Based on the sensitivity analysis, six updating parameters significantly affecting the natural frequency are selected. Subsequently, the objective function of the FEMU is established, and the DRAM algorithm is utilized to simulate the parameter samples conforming to the posterior distribution. Finally, the uncertainty analysis of the updated items is carried out. After FEMU, the results show that the model's frequency uncertainty is reduced, and the theoretical frequencies are highly consistent with the identified frequencies.

Copyright: © 2021 International Association for Bridge and Structural Engineering (IABSE)
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