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Optimum Design and Tuning Applications in Structural Engineering via Swarm Intelligence

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Advances in Swarm Intelligence

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1054))

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Abstract

As 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.

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Authors and Affiliations

  1. Department of Civil Engineering, Istanbul University-Cerrahpaşa, 34320, Avcilar, Istanbul, Turkey

    Gebrail Bekdaş & Sinan Melih Nigdeli

  2. Department of Civil Engineering, Istanbul Gelişim University, 34310, Avcılar, Istanbul, Turkey

    Aylin Ece Kayabekir

Authors
  1. Gebrail Bekdaş
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  2. Sinan Melih Nigdeli
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  3. Aylin Ece Kayabekir
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Correspondence to Gebrail Bekdaş .

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Editors and Affiliations

  1. Department of CS and Engineering, National Institute Of Technology Silchar, Cachar, Assam, India

    Anupam Biswas

  2. Department of Industrial Engineering, Pamukkale Üniversitesi Hastaneleri, Pamukkale, Turkey

    Can B. Kalayci

  3. Centre for AI Research and Optimisation, Torrens University Australia, Brisbane, QLD, Australia

    Seyedali Mirjalili

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Bekdaş, G., Nigdeli, S.M., Kayabekir, A.E. (2023). Optimum Design and Tuning Applications in Structural Engineering via Swarm Intelligence. In: Biswas, A., Kalayci, C.B., Mirjalili, S. (eds) Advances in Swarm Intelligence. Studies in Computational Intelligence, vol 1054. Springer, Cham. https://doi.org/10.1007/978-3-031-09835-2_6

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