Optimum Design and Tuning Applications in Structural Engineering via Swarm Intelligence

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dc.authorscopusid40461021100
dc.authorscopusid40461966400
dc.authorscopusid57196727294
dc.contributor.authorBekdaş, Gebrail
dc.contributor.authorNigdeli, Sinan Melih
dc.contributor.authorKayabekir, Aylin Ece
dc.date.accessioned2024-09-11T19:58:00Z
dc.date.available2024-09-11T19:58:00Z
dc.date.issued2023
dc.departmentİstanbul Gelişim Üniversitesien_US
dc.description.abstractAs all engineering disciplines, structural engineering problems are needed to be optimized and due to the nonlinear behavior of these problems, it is not possible to solve them mathematically, but metaheuristic methods are very successful in iterative optimization by assuming values for the design variables within a desired range of the user. In structural engineering problems, metaheuristic methods including swarm-intelligence-based algorithms are used in two groups of problems. Design optimization is the first group and the design like dimension, amount of material and orientations are optimally found for minimizing objectives related to cost, weight, CO2 emission and others. In these problems, constraints are found via design codes like steel and reinforced concrete structure design regulations. This group belongs to a design of a structure. The second group includes optimum tuning and it generally covers structural control applications. This group involves the optimum tuning of the additional control system of the structure that can be added to the newly constructed structure for better performance or existing ones to correct the failure or increase the existing performance. The role of engineers is to make the best possible structural design and optimization is important. More especially, tuning optimization is a must to provide acceptable performance. In this chapter, a review of existing studies about the design optimization of structural systems is presented for swarm intelligence-based algorithms. Then, optimum tuning applications are mentioned including the most important studies about tuned mass dampers. Finally, optimization problems are presented for design and tuning optimization. The RC retaining wall optimization was presented for two cases with and without toe projection and the optimization of a toe is 5% effective on reduction of cost. In span length optimization of frame structures, frame models with different stories have similar optimum span lengths. Active tuned mass dampers are up to 22.08% more effective than passive tuned mass dampers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.en_US
dc.identifier.doi10.1007/978-3-031-09835-2_6
dc.identifier.endpage134en_US
dc.identifier.issn1860-949Xen_US
dc.identifier.scopus2-s2.0-85139420939en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage109en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-031-09835-2_6
dc.identifier.urihttps://hdl.handle.net/11363/8396
dc.identifier.volume1054en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofStudies in Computational Intelligenceen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240903_Gen_US
dc.subjectMetaheuristic; Optimization; Optimum design; Structural engineering; Swarm intelligenceen_US
dc.titleOptimum Design and Tuning Applications in Structural Engineering via Swarm Intelligenceen_US
dc.typeBook Chapteren_US

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