JOURNAL ARTICLE

Structural Countermeasures Against Aerodynamic Torsional Divergence of a Suspension Bridge with a Main Span of 3000m.

  • Published In: International Journal of Structural Stability & Dynamics, 2026, v. 26, n. 6. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Zhang, Zhitian; Yang, Jiejun; Zeng, Jiadong 3 of 3

Abstract

Generalized structural and aerodynamic torsional stiffness of a suspension bridge with a main span length of 3 000 m are discussed first qualitatively in terms of analytical models. Two torsional divergence (TD) modes, symmetric and asymmetric, are compared in terms of the evolution of generalized torsional stiffness properties. It demonstrates that symmetric TD occurs prior to the asymmetric TD in a vast range of main span lengths. Numerical simulations of TD are then performed by the static finite element (FE) method. The results turn out a much lower critical wind speed of TD presented by the analytical model, due to stiffness degradation caused by main cable deformations. Finally, the effects of two types of countermeasures are examined. The replacement of the original deck section by a central slotted one can boost the critical wind speed of TD by 30%. Widening the main cable spacing enhances almost linearly the system's critical wind speed. A combined countermeasure of a slotted bridge deck and widened main cable spacing stabilizes substantially the system's aerodynamic static stability, resulting in a 45% increase in the critical wind speed of TD. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:International Journal of Structural Stability & Dynamics. 2026/03, Vol. 26, Issue 6, p1
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2026
  • ISSN:0219-4554
  • DOI:10.1142/S021945542650029X
  • Accession Number:191430841
  • Copyright Statement:Copyright of International Journal of Structural Stability & Dynamics is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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