Teaching-Learning Based Optimization of Nonlinear Isolation Systems under Far-Fault Earthquakes
TEKNIK DERGI, cilt.33, sa.1, ss.11487-11506, 2022 (SCI-Expanded)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 33 Sayı: 1
- Basım Tarihi: 2022
- Doi Numarası: 10.18400/tekderg.633636
- Dergi Adı: TEKNIK DERGI
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, TR DİZİN (ULAKBİM)
- Sayfa Sayıları: ss.11487-11506
- Anahtar Kelimeler: Seismic isolation, nonlinear isolation system, optimization, far-fault earthquake, ISOLATED BUILDINGS, NEAR-FIELD, DESIGN, PERFORMANCE, COLONY
- İstanbul Üniversitesi Adresli: Hayır
Özet
Seismic isolation systems exposed to far-fault earthquakes can reduce floor accelerations and story drift ratios to acceptable levels. However, they exhibit different structural performances in each earthquake due to different excitation frequency contents. By optimizing the isolation system parameters, their performance may be maintained at the best level under different farfault earthquakes. In this study, the optimization of the parameters of the nonlinear isolation system of a 5-story benchmark building is performed by Teaching-Learning Based Optimization (TLBO) algorithm to minimize peak floor accelerations under historical farfault earthquakes with and without exceeding a specified base displacement limit. According to the results of the analyses, it can be said that TLBO algorithm is a robust algorithm with low standard deviations for determining optimum nonlinear isolation system parameters.