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Erection procedure optimization of a long-span suspension bridge considering flutter risk in mixed wind climates
Journal of Tsinghua University (Science and Technology) 2025, 65(7): 1284-1290
Published: 01 July 2025
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Objective

During the erection stage of suspension bridges, the critical flutter wind speed varies continuously owing to changes in structural dynamic properties, including mass and stiffness. Concurrently, the wind climate fluctuates seasonally or even monthly throughout the bridge erection process. To evaluate the flutter risk of suspension bridges exposed to varying wind conditions, a framework is proposed to optimize the deck erection timeline under complex wind climates, with a summary of the flutter risk flow.

Methods

The aerodynamic flutter stability for each construction stage was tested by full-model wind tunnel tests. The time-varying wind climate is represented as an extreme wind speed annual exceedance probability distribution function for each month. Data for synoptic wind speed analysis were extracted from the National Oceanic and Atmospheric Administration (NOAA) Global Integrated Surface Dataset, while tropical cyclone wind speeds were modeled using Vickery's full-track Monte Carlo simulations. The mixed extreme wind speed, resulting from the combination of tropical cyclones and monsoons, was calculated using probability theory for independent events. An optimization algorithm was used to determine the optimal deck erection starting timeline to minimize on-site flutter probability during the entire deck erection construction process.

Results

Two specific analytical methods and visualizations were proposed. The flutter risk flow illustrates the flutter performance of a single program, while the erection flutter risk box plot provides a horizontal comparison of different erection processes. The study also discussed how to choose the best deck erection plan for different erection procedure configurations. The Shenzhong Link, built on the southern coastline of China, served as a case study. A full-bridge aeroelastic model wind tunnel test was conducted to determine the critical flutter speed at different erection stages. As the construction of the main beam progressed, the critical wind speed of the bridge generally increased. In addition, a negative angle of attack was detrimental when the main beam assembly rate was low, while a positive angle of attack was unfavorable at higher assembly rates. Extreme wind speeds from typhoons and synoptic winds were analyzed using Monte Carlo typhoon simulations and meteorological data statistics, respectively. The results indicated strong seasonality in coastal mixed climates owing to typhoon influence. The optimization algorithm identified an optimal timeline for the Lingdingyang Bridge, minimizing flutter risk. However, selecting the worst timeline could exponentially increase flutter risk.

Conclusions

This paper proposes a construction process optimization strategy for suspension bridge girder that minimizes the flutter risk during the overall construction process. The mixed climatic wind environment including typhoons and benign winds and the continuous time-varying bridge structure state are considered, and the time-varying construction period flutter probability is calculated. Research has shown that timeline optimization is a more economical and viable approach than structural and aerodynamic interventions, especially in mixed wind climates. Horizontal comparison of desk erection plans should consider not only the lowest flutter speed but also the flutter risk probability across all timelines. The erection risk box plot is an effective tool in this case. If the erection starting time is flexible, minimizing the flutter probability should be the main indicator. When the timeline is uncertain, greater attention should be given on the mean-value and quartile box indicators.

Open Access Issue
Intelligent prediction model for reduced-order dynamic modes of velocity field around a 1∶5 rectangular section
Acta Aerodynamica Sinica 2025, 43(5): 124-133
Published: 05 June 2025
Abstract PDF (2.4 MB) Collect
Downloads:21

Although the research on flow around bluff body sections can obtain the characteristics of the velocity field through particle image velocimetry (PIV) and computational fluid dynamics (CFD) methods, it is limited by the Reynolds number effect, onsite test conditions, and the accuracy of numerical simulation. However, the full-scale bridge surface pressure measurement technology is more engineering practical. Building upon the inherent coupling between the surface pressure field and velocity field of bridge sections, this paper proposes a reduced-order correlation and prediction model for the velocity field of a 1:5 rectangular section using surface pressure distribution. The developed model‌ integrates dynamic mode decomposition (DMD) and a BP neural network to: (1) extract pressure and velocity field modes across Reynolds numbers (1000–20000); (2) establish their mapping relationship through an implicit neural network; and (3) achieve velocity field prediction from pressure data. ‌Validation results‌ at Re=6000 show prediction errors of merely 0.06 m/s (lateral) and 0.02 m/s (vertical) at the reference point [1.5, 0], demonstrating the model's effectiveness. This research provides valuable insights for wake flow field reconstruction and aerodynamic measure evaluation in bridge sections.

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