A Probabilistic Engineering Load Model for Pedestrian Streams
| Author(s): |
Christiane Butz
|
|---|---|
| Medium: | conference paper |
| Language(s): | English |
| Conference: | Footbridge 2008 - Footbridges for Urban Renewal, Third International Conference on Footbridges, 2-4 July 2008, Porto, Portugal |
| Published in: | Footbridge 2008 - Footbridges for Urban Renewal |
| Page(s): | 271-272 |
| Year: | 2008 |
| Abstract: | Numerical simulations of pedestrian streams are very time consuming and a special software has to be available that is able to do time step simulations with advanced load models. This is not acceptable for an estimation of the structural response in the design stage. Hence, a spectral load model by applying Monte-Carlo-simulations for four different traffic scenarios is derived, in which the stochastic properties of the pedestrian traffic are considered but which can be easily applied by the structural engineers in the design stage. It allows for a variation of modal properties, e.g. damping, natural frequencies, or the loading, e.g. pedestrian density, mean step frequency to perform sensitivity analysis in the design stage, because natural frequencies are normally not exactly determined and damping and traffic scenarios are only estimated values. The spectral model for pedestrian streams is based on extensive measured data and takes into account probabilistic requirements. It allows to calculate the 95 % fractile of the acceleration response of sinusoidal vibration modes and hence can be used for serviceability limit checks according to Eurocode requirements. The spectral model is easy to apply and is suitable as engineering load model. |
| Keywords: |
Monte-Carlo simulation pedestrian loading pedestrian streams probabilistic load model random loads
|
| License: | This creative work is copyrighted. The copyright holder(s) do(es) not grant any usage rights other than viewing and downloading the work for personal use. Further copying or publication requires the permission of the copyright holder(s). |
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data sheet - Reference-ID
10074421 - Published on:
25/10/2016 - Last updated on:
07/12/2021
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