Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
2 files | 3.70 MB
Add to list
  1. Search results
  2. Condition assessment of a concrete fi...

Condition assessment of a concrete filled steel tube arch bridge using in-situ vibration measurements and an Improved Artificial Fish Swarm Algorithm

Shiqiang Qin, Jiacheng Feng, Jian Tang, Xuejin Huo, Yunlai Zhou, Fei Yang and Magd Abdel Wahab (UGent)
(2024) COMPUTERS & STRUCTURES. 291.
Author
Organization
Abstract
This study aims to assess the condition of a Concrete-Filled Steel Tube (CFST) arch bridge using in-situ vibration measurements, Finite Element Model Updating (FEMU) and an Improved Artificial Fish Swarm Algorithm (IAFSA). Dynamic coefficients, derailment coefficients and wheel unloading rates are extracted from the responses of running safety assessment. An updated finite element model using a kriging model and IAFSA is employed to evaluate the strength and rigidity of the structures. The results indicate that the natural frequencies and damping ratios of the CFST arch bridge meet the requirements of design code. The maximum bridge dynamic coefficient is found to be 1.085, indicating that the bridge dynamic performance is good. The wheel unloading rates of vehicle and locomotive exceed the specification limit, indicating that the track condition has to be improved before the bridge is operated. By updating an initial FE model, the errors between the predicted and the measured parameters are reduced to less than 5%.
Keywords
Computer Science Applications, Mechanical Engineering, General Materials Science, Modeling and Simulation, Civil and Structural Engineering, Continuous rigid frame, Concrete filled steel tube, Arch bridge, Finite, Element Model Updating, Artificial Fish Swarm Algorithm

Downloads

  • Download
    (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 2.05 MB
  • Download
    Yichang Bridge maw R1 maw clean.docx
    • full text (Accepted manuscript)
    • |
    • open access
    • |
    • Word
    • |
    • 1.65 MB

Citation

Please use this url to cite or link to this publication:

MLA
Qin, Shiqiang, et al. “Condition Assessment of a Concrete Filled Steel Tube Arch Bridge Using In-Situ Vibration Measurements and an Improved Artificial Fish Swarm Algorithm.” COMPUTERS & STRUCTURES, vol. 291, 2024, doi:10.1016/j.compstruc.2023.107213.
APA
Qin, S., Feng, J., Tang, J., Huo, X., Zhou, Y., Yang, F., & Abdel Wahab, M. (2024). Condition assessment of a concrete filled steel tube arch bridge using in-situ vibration measurements and an Improved Artificial Fish Swarm Algorithm. COMPUTERS & STRUCTURES, 291. https://doi.org/10.1016/j.compstruc.2023.107213
Chicago author-date
Qin, Shiqiang, Jiacheng Feng, Jian Tang, Xuejin Huo, Yunlai Zhou, Fei Yang, and Magd Abdel Wahab. 2024. “Condition Assessment of a Concrete Filled Steel Tube Arch Bridge Using In-Situ Vibration Measurements and an Improved Artificial Fish Swarm Algorithm.” COMPUTERS & STRUCTURES 291. https://doi.org/10.1016/j.compstruc.2023.107213.
Chicago author-date (all authors)
Qin, Shiqiang, Jiacheng Feng, Jian Tang, Xuejin Huo, Yunlai Zhou, Fei Yang, and Magd Abdel Wahab. 2024. “Condition Assessment of a Concrete Filled Steel Tube Arch Bridge Using In-Situ Vibration Measurements and an Improved Artificial Fish Swarm Algorithm.” COMPUTERS & STRUCTURES 291. doi:10.1016/j.compstruc.2023.107213.
Vancouver
1.
Qin S, Feng J, Tang J, Huo X, Zhou Y, Yang F, et al. Condition assessment of a concrete filled steel tube arch bridge using in-situ vibration measurements and an Improved Artificial Fish Swarm Algorithm. COMPUTERS & STRUCTURES. 2024;291.
IEEE
[1]
S. Qin et al., “Condition assessment of a concrete filled steel tube arch bridge using in-situ vibration measurements and an Improved Artificial Fish Swarm Algorithm,” COMPUTERS & STRUCTURES, vol. 291, 2024.
@article{01HEVYDM9KYP1FP1GFKAJTEEPT,
  abstract     = {{This study aims to assess the condition of a Concrete-Filled Steel Tube (CFST) arch bridge using in-situ vibration measurements, Finite Element Model Updating (FEMU) and an Improved Artificial Fish Swarm Algorithm (IAFSA). Dynamic coefficients, derailment coefficients and wheel unloading rates are extracted from the responses of running safety assessment. An updated finite element model using a kriging model and IAFSA is employed to evaluate the strength and rigidity of the structures. The results indicate that the natural frequencies and damping ratios of the CFST arch bridge meet the requirements of design code. The maximum bridge dynamic coefficient is found to be 1.085, indicating that the bridge dynamic performance is good. The wheel unloading rates of vehicle and locomotive exceed the specification limit, indicating that the track condition has to be improved before the bridge is operated. By updating an initial FE model, the errors between the predicted and the measured parameters are reduced to less than 5%.}},
  articleno    = {{107213}},
  author       = {{Qin, Shiqiang and Feng, Jiacheng and Tang, Jian and Huo, Xuejin and Zhou, Yunlai and Yang, Fei and Abdel Wahab, Magd}},
  issn         = {{0045-7949}},
  journal      = {{COMPUTERS & STRUCTURES}},
  keywords     = {{Computer Science Applications,Mechanical Engineering,General Materials Science,Modeling and Simulation,Civil and Structural Engineering,Continuous rigid frame,Concrete filled steel tube,Arch bridge,Finite,Element Model Updating,Artificial Fish Swarm Algorithm}},
  language     = {{eng}},
  pages        = {{11}},
  title        = {{Condition assessment of a concrete filled steel tube arch bridge using in-situ vibration measurements and an Improved Artificial Fish Swarm Algorithm}},
  url          = {{http://doi.org/10.1016/j.compstruc.2023.107213}},
  volume       = {{291}},
  year         = {{2024}},
}
Altmetric
View in Altmetric
Web of Science
Times cited: