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Validating Low-Level Footfall-Induced Vibration Predictions in Steel and Concrete Structures

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Topics in Model Validation and Uncertainty Quantification, Volume 5

Abstract

Occupant footfalls are often the most critical source of floor vibration on the elevated floors of buildings. Floor motions can disturb occupants, leading to frequent complaints and loss of functionality. In laboratory and healthcare facilities, this issue can be more critical, as high-resolution imaging equipment with stringent vibration criteria is often employed. Achieving these criteria requires sufficiently stiff and massive floor structures to effectively resist the forces exerted from user traffic. The difficulty for engineers is predicting these low levels of vibration. Two commonly used analysis methods to predict footfall vibration levels in steel buildings are the American Institute of Steel Construction (AISC) Design Guide 11, and The Steel Construction Institute (SCI) P354. The latter is more robust, as it can predict multi-modal time history responses at any point on the floor. Dynamic footfall loading is determined by considering walkers moving along reasonable pathways identified in the architectural floor plans. For concrete structures, The Concrete Centre (CCIP-016) proposes a methodology similar to the SCI. In this study, three steel and one concrete building are instrumented to measure footfall-induced vibrations. The measured values are compared to the predictions of the aforementioned methods, and the superiority of the SCI-P354 and CCIP-016 methods is shown.

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Correspondence to Michael J. Wesolowsky .

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© 2013 The Society for Experimental Mechanics, Inc.

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Wesolowsky, M.J., Graham, J.M., Love, J.S., Galsworthy, J.K., Swallow, J.C. (2013). Validating Low-Level Footfall-Induced Vibration Predictions in Steel and Concrete Structures. In: Simmermacher, T., Cogan, S., Moaveni, B., Papadimitriou, C. (eds) Topics in Model Validation and Uncertainty Quantification, Volume 5. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6564-5_19

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  • DOI: https://doi.org/10.1007/978-1-4614-6564-5_19

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-6563-8

  • Online ISBN: 978-1-4614-6564-5

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