Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/15658
Title: Structural health monitoring oriented finite element model of Tsing Ma Bridge tower
Authors: Fei, QG
Xu, YL 
Ng, CL
Wong, KY
Chan, WY
Man, KL
Keywords: Finite element model
Model updating
Structural health monitoring
Suspension bridge tower
Validation
Issue Date: 2007
Publisher: World Scientific
Source: International journal of structural stability and dynamics, 2007, v. 7, no. 4, p. 647-668 How to cite?
Journal: International journal of structural stability and dynamics 
Abstract: The modeling, updating and validation of a structural health monitoring oriented finite element model (FEM) of the Tsing Ma suspension bridge towers are presented in this paper. The portal-type bridge tower is composed of two hollow reinforced concrete legs and four deep pre-stressed cross-beams with a steel truss cast in the concrete of each cross-beam to form a narrow corridor for access between two legs. Except that steel trusses are modeled by beam elements, all structural components are modeled by solid elements to facilitate local damage detection, in particular at member joints. The established tower model is then updated using sensitivity-based model updating method taking the natural frequencies identified from field measurement data as reference. Furthermore, a two-level validation criterion is proposed and implemented to examine the replication performance of the updated finite element model of the bridge tower in terms of (1) natural frequencies in higher modes of vibration and (2) dynamic characteristics of the tower-cable system. The validation results show that a good replication of dynamic characteristics is achieved by the updated tower model when compared to the field measurement results. Finally, stress distribution and concentration of the bridge tower are investigated through nonlinear static analysis of the tower-cable system.
URI: http://hdl.handle.net/10397/15658
ISSN: 0219-4554
EISSN: 1793-6764
DOI: 10.1142/S0219455407002502
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