FE Model Updating on an In-Service Self-Anchored Suspension Bridge with Extra-Width Using Hybrid Method

• Published in: Applied sciences Vol. 7; no. 2; p. 191
• Main Authors: Xia, Zhiyuan, Li, Aiqun, Li, Jianhui, Duan, Maojun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 2017
• Subjects: Accuracy; Artificial intelligence; Blanks; Bridges; Civil engineering; Datasets; Efficiency; FE model updating; Finite element method; Gaussian mutation; Genetic algorithms; Hypercubes; Integration; Iron; Iterative methods; Kriging meta-model; Latin hypercube sampling; Mathematical analysis; Methods; Model updating; Optimization; Optimization techniques; particle swarm optimization; self-anchored suspension bridge; Suspension bridges; Swarm intelligence; Test procedures; Vibration; Vibration tests
• DOI: 10.3390/app7020191
• ISSN: 2076-3417

Nowadays, many more bridges with extra-width have been needed for vehicle throughput. In order to obtain a precise finite element (FE) model of those complex bridge structures, the practical hybrid updating method by integration of Gaussian mutation particle swarm optimization (GMPSO), Kriging meta-model and Latin hypercube sampling (LHS) was proposed. By demonstrating the efficiency and accuracy of the hybrid method through the model updating of a damaged simply supported beam, the proposed method was applied to the model updating of a self-anchored suspension bridge with extra-width which showed great necessity considering the results of ambient vibration test. The results of bridge model updating showed that both of the mode frequencies and shapes had relatively high agreement between the updated model and experimental structure. The successful model updating of this bridge fills in the blanks of model updating of a complex self-anchored suspension bridge. Moreover, the updating process enables other model updating issues for complex bridge structures