Comparison of meta-heuristic approaches for the optimization of non-linear base-isolation systems considering the influence of superstructure flexibility

Öncü-Davas, Seda; Temür, Rasim; Alhan, Cenk

doi:10.1016/j.engstruct.2022.114347

Cited by 10 publications

(1 citation statement)

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“…Hence, it is of paramount importance to ascertain the ideal parameters for seismic isolation systems, ensuring the attainment of the intended seismic performance for base-isolated structures. In several studies in the related literature, distinct optimization approaches have been used to select the optimum damping ratio and motion period of an isolator (Charmpis et al, 2015; Greco and Marano, 2016; Kandemir and Mortazavi, 2022; Ocak et al, 2022; Öncü-Davas et al, 2022; Roy et al, 2014). The studies mentioned above indicate that the effective seismic management of a structure relies on choosing the suitable parameters for the isolation system.…”

Section: Introductionmentioning

confidence: 99%

Optimizing base isolation system parameters using a fuzzy reinforced butterfly optimization: A case study of the 2023 Kahramanmaras earthquake sequence

Kandemir,

Mortazavi

2023

Journal of Vibration and Control

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This study aims to obtain the viable parameters of base isolation systems that are utilized in buildings with seismic isolation and specially located in Turkey. To provide a more accurate representation of real-world scenarios, the study accounts for severe ground motion records simultaneously during the dynamic response analysis of the structure. Three records are taken from the 2023 Turkey earthquake (records for Elbistan, Nurdagi, and Pazarcik). The optimization model's objective function is to minimize the ratio of the roof acceleration to the peak ground acceleration. To ensure realistic outcomes, certain isolation parameters are constrained, such as maintaining the damping ratio and period within a predetermined range as well as the maximum lateral drift of the structure. An upgraded variant of the Butterfly Optimization Algorithm, known as the Fuzzy Butterfly Optimization Algorithm (FBOA), is employed to address the presented optimization model. The FBOA technique incorporates a fuzzy decision-making mechanism that adjusts its search strategy according to the prevailing conditions of the present problem. In addition, the FBOA method utilizes a new auxiliary vector called virtual butterfly, which provides information on the entire population based on each agent's quality. Consequently, FBOA transforms into a self-regulating search algorithm, eliminating the requirement for any external parameters. Results have verified the effectiveness of FBOA in detecting optimal parameters of the proposed isolation system.

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