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Robust Optimum Design of Tuned Mass Dampers to Mitigate Pedestrian-Induced Vibrations Using Multi-Objective Genetic Algorithms

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Tuned mass dampers (TMDs) are well-known control devices used widely to mitigate the pedestrian-induced vibrations on footbridges. The main purpose of this study is the robust optimum design of TMDs using multi-objective genetic algorithms in order to control the pedestrian-induced vibrations on footbridges considering the uncertainties associated with their modal properties. The performance of the TMD is improved via the robust optimum design of its modal parameters using multi-objective genetic algorithms. As an example, a benchmark footbridge, modelled by frame and shell elements, is used to assess numerically the performance and accuracy of the proposed method. The pedestrian action is simulated by an equivalent harmonic load. The proposed method is compared with the conventional Den Hartog's proposal. The results show that this new method is more effective than the conventional proposal and the resulting damping device is more economic due to the smaller value of its design parameters.
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Document Type: Research Article

Publication date: 01 November 2017

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    Structural Engineering International (SEI), the quarterly Journal of IABSE, published since 1991, is the leading international journal of structural engineering dealing with all types of structures and materials. SEI offers its readers a unique blend of short profiles on recent structures, and longer, in-depth technical articles on research, development, design, construction and maintenance. Articles are written by practicing engineers and academia from around the world and reflect the high standards of IABSE. IABSE Peer Review stamps are given to papers that have passed through a highly selective review process and demonstrate a significant contribution to the state of structural engineering knowledge.To recognise contributions of the highest quality, an Outstanding Paper Award is presented each year.

    SEI is printed in Switzerland; ISSN 1016-8664; E-ISSN 1683-0350
    Abstracted and indexed at: Web of ScienceSM; Science Citation Index Expanded (SciSearch); Journal Citation Reports/Science Edition; Current ContentsR/Engineering, Computing and Technology; CAB Abstracts database; INSPEC, CBA and others.

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