Eeklo Footbridge: Benchmark Dataset on Pedestrian-Induced Vibrations

نویسندگان

چکیده

Vibration serviceability under crowd-induced loading has become a key design criterion for footbridges. Although increased research efforts are put into the characterization of loading, including related interaction phenomena, and first-generation guides available, major challenge lies in further development validation prediction models vibrations. Full-scale benchmark datasets that simultaneously register structural crowd motion make an invaluable contribution to meeting this need by providing detailed information on representative operational response data. Currently available either (1) involve (too) small number pedestrians or (2) do not simultaneous registration pedestrian bridge motion, else they footbridge (3) where only single mode very limited modes sensitive walking excitation, (4) which no suitable digital twin is (5) open access. This paper therefore presents new publicly full-scale dataset collected specifically loading. The real footbridge, with pedestrian-induced vibrations, available. motions registered using wireless triaxial accelerometers video cameras. In addition two data blocks involving purely ambient four densities, 0.25 0.50 persons/m2, representing total more than 1 h each density. Analysis shows different can be considered involved load case. identified distribution step frequencies indicates significant (near-)resonant footbridge. Furthermore, displays clear signs human–structure interaction, suggesting increase effective modal damping ratios due presence crowd.

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ژورنال

عنوان ژورنال: Journal of Bridge Engineering

سال: 2021

ISSN: ['1084-0702', '1943-5592']

DOI: https://doi.org/10.1061/(asce)be.1943-5592.0001707