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The Methods and Approaches of Explainable Artificial Intelligence Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Optimum Design of Tuned Mass Dampers for Adjacent Structures via Flower Pollination Algorithm

Authors : Sinan Melih Nigdeli, Gebrail Bekdaş, Xin-She Yang

Published in: Computational Science – ICCS 2021

Publisher: Springer International Publishing

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Abstract

It is a very known issue that tuned mass dampers (TMDs) on an effective system for structures subjected to earthquake excitations. TMDs can be also used as a protective system for adjacent structures that may pound to each other. With a suitable optimization methodology, it is possible to find an optimally tuned TMD that is effective in reducing the responses of structure with an additional protective feature that reduces the amount of required seismic gap between adjacent structures by using an objective function. This function considers the displacement of structures with respect to each other. As the optimization methodology, the flower pollination algorithm (FPA) is used in finding the optimum parameters of TMDs of both structures. The method was evaluated on two 10-story adjacent structures and the optimum results were compared with harmony search (HS) based methodology.

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previous chapter Expedited Trust-Region-Based Design Closure of Antennas by Variable-Resolution EM Simulations
next chapter On Fast Multi-objective Optimization of Antenna Structures Using Pareto Front Triangulation and Inverse Surrogates
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Metadata
Title
Optimum Design of Tuned Mass Dampers for Adjacent Structures via Flower Pollination Algorithm
Authors
Sinan Melih Nigdeli
Gebrail Bekdaş
Xin-She Yang
Copyright Year
2021
Book
Computational Science – ICCS 2021

Print ISBN: 978-3-030-77969-6

Electronic ISBN: 978-3-030-77970-2

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-77970-2_9

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