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Finite Element Model Updating of Bridge Structures Based on Improved Response Surface Methods

Autor(en): ORCID

ORCID


Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Structural Control and Health Monitoring, , v. 2023
Seite(n): 1-16
DOI: 10.1155/2023/2488951
Abstrakt:

An accurate and reasonable finite element model is essential for bridge structural health monitoring and safety assessment. To improve the accuracy and efficiency of the finite element model updating, this paper proposes a finite element model updating method for bridge structures based on an improved response surface method. By introducing the radial basis function as the augmentation term of the polynomial function, a response surface model based on the augmentation polynomial is established, and the fitting accuracy of the global response surface model is improved. The convergence speed and accuracy of the response surface model optimization solution are improved by improving the regression step and annealing strategy in the simulated annealing algorithm. The method is validated using the numerical case of a simply supported beam and the finite element model of the main bridge of the Tonghe Songhua River Highway Bridge (Tonghe Bridge), and the safety condition of the main bridge of the Tonghe Bridge is evaluated using the updated finite element model. The results show that the maximum relative error of the updated parameters of the simply supported beam decreased from 13.011% before improvement to 0.719% after improvement, and the maximum relative error of the natural frequencies decreased from 0.728% before improvement to 0.225% after improvement; the maximum relative error of the natural frequencies of the finite element model of the Tonghe Bridge main bridge decreased from 21.68% before improvement to 4.23% after improvement. In April, May, and June of 2021, the main bridge of the Tonghe Bridge operated well and had a good security reserve.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.1155/2023/2488951.
  • Über diese
    Datenseite
  • Reference-ID
    10725421
  • Veröffentlicht am:
    30.05.2023
  • Geändert am:
    30.05.2023
 
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