TY - JOUR
T1 - Time history analysis-based nonlinear finite element model updating for a long-span cable-stayed bridge
AU - Lin, Kaiqi
AU - Xu, You Lin
AU - Lu, Xinzheng
AU - Guan, Zhongguo
AU - Li, Jianzhong
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The financial supports from the Research Grants Council of Hong Kong through a competitive GRF grant (Grant No. 15269516); The Hong Kong Polytechnic University through a special grant (Grant No. 1-ZVN3) and the National Natural Science Foundation of China (No. 51908133) are also appreciated.
Publisher Copyright:
© The Author(s) 2020.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - long-span cable-stayed bridge
KW - Nonlinear finite element model updating
KW - particle swarm optimization
KW - shake table test
KW - time history analysis
UR - http://www.scopus.com/inward/record.url?scp=85092604001&partnerID=8YFLogxK
U2 - 10.1177/1475921720963868
DO - 10.1177/1475921720963868
M3 - Journal article
AN - SCOPUS:85092604001
SN - 1475-9217
JO - Structural Health Monitoring
JF - Structural Health Monitoring
ER -