Time-Domain Finite Element Model Updating for Operational Monitoring and Damage Identification of Bridges

The well-known limitations of modal system identification methods have led to a broad exploration of alternative solutions for operational monitoring and damage diagnosis of structures. This study presents a time-domain Bayesian finite element model updating approach to jointly identify the vehicula...

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Vydáno v:Structural control and health monitoring Ročník 2023; číslo 1; s. 1 - 21
Hlavní autoři: Malekghaini, Niloofar, Ghahari, Farid, Ebrahimian, Hamed, Bowers, Matthew, Azari, Hoda, Taciroglu, Ertugrul
Médium: Journal Article
Jazyk:angličtina
Vydáno: Pavia Hindawi 31.07.2023
John Wiley & Sons, Inc
Témata:
Bayesian analysis
Bridge loads
Concrete deterioration
Damage detection
Domains
Finite element method
Force distribution
Identification methods
Model updating
Parameter estimation
Parameter identification
Prestressing
Reinforced concrete
Reinforcing steels
System identification
Vibration monitoring
ISSN:1545-2255, 1545-2263
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Shrnutí:The well-known limitations of modal system identification methods have led to a broad exploration of alternative solutions for operational monitoring and damage diagnosis of structures. This study presents a time-domain Bayesian finite element model updating approach to jointly identify the vehicular loads and finite element modeling parameters of bridges using the vibration data and the location of vehicles traversing the bridge as input. A Bayesian model updating is devised and verified through a series of case studies based on numerically simulated data from a prestressed reinforced concrete box-girder bridge model. Damage states are defined for concrete degradation and delamination, steel corrosion, and loss of prestressing force. Ten different damage scenarios, encompassing the range from minor localized to major distributed damage, are examined. The responses of the damaged bridge are simulated under random traffic scenarios. The acceleration responses, along with the location of the vehicles on the bridge, are used for jointly estimating the model parameters and vehicular loads. The estimated model parameters are then used to infer the location and extent of damage within the bridge. The results show the successful performance of the proposed approach in a numerically simulated environment.
Bibliografie:ObjectType-Article-1
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ISSN:1545-2255
1545-2263
DOI:10.1155/2023/4170149