Abstract

Accurate finite element models play significant roles in the design, health monitoring and life-cycle maintenance of long-span bridges. However, due to uncertainties involved in finite element modelling, updating of the finite element model to best represent the real bridge is inevitable. This is particularly true after a long-span bridge experiences a moderate or severe earthquake and suffers some damage. This study thus proposes a time history analysis-based nonlinear finite element model updating method for long-span cable-stayed bridges. Special efforts are made to (1) establish the response time history-based objective functions and associated acceptance criteria, (2) conduct comprehensive sensitivity analyses to select appropriate nonlinear updating parameters and (3) develop a highly efficient cluster computing-aided optimization algorithm. A scaled structure of the Sutong cable-stayed bridge in China is adopted as a case study. Three nonlinear test cases performed in the shake table tests of the scaled bridge are used to validate the feasibility and accuracy of the proposed method. A good agreement is observed between the simulated response time histories and the measured response time histories for the scaled bridge under both moderate and strong ground motions. The proposed method could provide an accurate nonlinear finite element model for better performance assessment, damage detection and life-cycle maintenance of long-span cable-stayed bridges.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.