Paper 451 Mini-symposium 19 Session 5

Characterising Wind-Induced Bridge Hanger Vibrations Through Long-Term Monitoring Data

Presented by El Azrak, Fatiha

Submission overview

Abstract

The dynamic response of bridge hangers is strongly influenced by wind loads. Therefore, long-term monitoring data offer a powerful basis for characterising their full-scale aeroelastic behaviour. This study presents a comprehensive analysis of long-term accelerometer and strain gauge data collected from one of the longest hangers of the new Bomarsund Bridge, in which pronounced resonance phenomena were registered. Acceleration and strain signals are processed to obtain spectral characteristics, evaluate vibration amplitudes, and reconstruct hanger displacements using both acceleration- and strain-based methods. The reconstructed displacements allow the identification of vibration trajectories and the investigation of coupled motion between the along-wind and cross-wind directions. The monitoring data reveal a distinct response window during which along-wind vibrations reach amplitudes approximately one order of magnitude larger than those in the cross-wind direction. Spectral analysis indicates dominant frequencies near 7 Hz in the along-wind direction and 14 Hz in the cross-wind direction, corresponding to the first bending modes of the hanger. The reconstructed trajectories exhibit repeatable figure-eight patterns, indicating coupled motion with a near 2:1 frequency relationship between the dominant modal components. Wind measurements from a nearby meteorological station are correlated with the structural response to identify the environmental conditions associated with the observed vibrations. The largest responses occur for moderate-to-high wind speeds (approximately U_mean ≈ 9–10 m/s), low turbulence intensity, and small angles of attack (|AOA| ≤ 10°), conditions that favour coherent aerodynamic excitation. The results demonstrate how long-term monitoring data can provide insight into the aeroelastic behaviour of bridge hangers and help identify wind conditions associated with large-amplitude vibrations.