Buffeting response of a suspension bridge (time domain)
Updated 28 Apr 2020
The coupled dynamic response of a suspension bridge to wind turbulence is computed in the time domain
The lateral, vertical and torsional response of a suspension is computed in the time domain using computed turbulent velocity time histories. The simplified Bridge model of the Lysefjord Bridge  is considered for the modelling of the structure. Turbulence is modelled using the Kaimal model . The quasi-steady theory, as well as the strip assumption, are used. Modal coupling between the lateral, vertical and torsional motions are accounted for in the time-domain model.
The present submission contains:
- The function dynaRespTD.m that computes the bridge response in the time domain (Non-linear load + modal coupling)
- The function dynaResp_noCouplingTD.m that computes the bridge response in the time domain (linearised load + no modal coupling)
- An example file that compares the time-domain approach with the frequency domain approach
- Various functions used for the example file, including simulation of correlated wind histories , computation of the bridge modal parameters , computation of the bridge response in the frequency domain .
Any suggestion, comment or question is welcomed.
 Cheynet, E., Jakobsen, J. B., & Snæbjörnsson, J. (2016). Buffeting response of a suspension bridge in complex terrain. Engineering Structures, 128, 474-487.
 Kaimal, J. C., Wyngaard, J. C. J., Izumi, Y., & Coté, O. R. (1972). Spectral characteristics of surface‐layer turbulence. Quarterly Journal of the Royal Meteorological Society, 98(417), 563-589.
E. Cheynet (2023). Buffeting response of a suspension bridge (time domain) (https://github.com/ECheynet/dynaRespTD/releases/tag/v2.1), GitHub. Retrieved .
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Versions that use the GitHub default branch cannot be downloaded
See release notes for this release on GitHub: https://github.com/ECheynet/dynaRespTD/releases/tag/v2.1
Added Github repository
The example file is simplified
The example is updated using a more time-consuming setup (more simulations, higher sampling frequency...)
New function added and example updated