Data-driven model of random lateral pedestrian excitation
Research and Applications in Structural Engineering, Mechanics and Computation - Proceedings of the 5th International Conference on Structural Engineering, Mechanics and Computation, SEMC 2013
Taylor & Francis (CRC Press)
Reason for embargo
Under indefinite embargo – no publisher permission. The final version is available from Taylor & Francis (CRC Press).
Randomness and narrow band nature are the two essential features of lateral walking loading not addressed adequately in the existing design guidelines for footbridges. One of the reasons for this is the lack of a comprehensive database of lateralwalking forces in the formof continuously recorded time series that can be used for development of statistically reliable characterisation of these forces for application in the civil engineering context. This paper has addressed the issue by establishing a large database of measured lateral walking time series recorded by a state-of-the-art instrumented treadmill at the University of Sheffield. Another reason is the lack of an adequate modelling strategy which can simulate reliably the actual forcing records. Motivated by the existing models of wind and earthquake loading, speech recognition techniques and a method of replicating electrocardiogram (ECG) signals, a data-driven mathematical model has been developed to generate synthetic force signals with realistic temporal and spectral features. This multi-disciplinary modelling strategy offers a radical departure from traditional Fourier-based representations of lateral walking loads towards more reliable and more realistic vibration serviceability assessment of footbridges. © 2013 Taylor & Francis Group, London, UK.
The authors would like to acknowledge the financial support provided by the UK Engineering and Physical Sciences Research Council (EPSRC) for grant reference EP/E018734/1 (“Human Walking and Running Forces: Novel Experimental Characterisation and Application in Civil Engineering Dynamics”) and to thank all test subjects for participating in the data collection.
Pavic, A. and Brownjohn, J., 2013, 'Data-driven model of random lateral pedestrian excitation' in Zingoni, A. (Ed.) Research and Applications in Structural Engineering, Mechanics and Computation, pp. 119 - 124