Volume 14, Issue 2 (2-2024)                   2024, 14(2): 253-274 | Back to browse issues page

XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Ghaderi A, Nouri M, Hosseinzadeh L, Ferdousi A. OPTIMAL HYBRID CONTROL OF TALL TUBULAR BUILDINGS USING UPGRADED GAZELLE OPTIMIZATION ALGORITHM WITH CHAOS THEORY. International Journal of Optimization in Civil Engineering 2024; 14 (2) :253-274
URL: http://ijoce.iust.ac.ir/article-1-586-en.html
Abstract:   (1786 Views)
Seismic vibration control refers to a range of technical methods designed to reduce the effects of earthquakes on building structures and many other engineering systems. Most of the recently developed methods in this area have been investigated in vibration suppression of buildings structures each of which have advantages and disadvantages in dealing with complex structural systems and destructive earthquakes. This study aims to implement two of the well-known passive control systems as Base Isolation (BI) and Mass Damper (MD) control as a hybrid control scheme in order to reduce the seismic vibration of tall tubular buildings in dealing with different types of earthquakes. For this purpose, a 50-story tall building is considered with tubular structural system while the hybrid BI-MD control system ins implemented in the building for vibration control purposes. Since the parameter tuning process is one of the key aspects of the passive control systems, a metaheuristic-based parameter optimization process is conducted for this purpose in which a new upgraded version of the standard Gazelle Optimization Algorithm (GOA) is proposed as UGOA while the Chaos Theory (CT) is used instead of random movements in the main search loop of the UGOA in order to enhance the overall performance of the standard algorithm. The results show that the upgraded algorithm is capable of conducting better search in dealing with the optimal hybrid control of structural systems.
 
Full-Text [PDF 1680 kb]   (157 Downloads)    
Type of Study: Research | Subject: Applications
Received: 2024/01/20 | Accepted: 2024/03/17 | Published: 2024/05/27

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Iran University of Science & Technology

Designed & Developed by : Yektaweb