Result: Design Optimization of Tuned Liquid Dampers with Hybrid Algorithms

Title:
Design Optimization of Tuned Liquid Dampers with Hybrid Algorithms
Authors:
Ocak A., Nigdeli S.M., Bekdaş G.
Contributors:
İstanbul University Cerrahpaşa Institutional Repository
Source:
Lecture Notes in Networks and Systems ISBN: 9783031501500
Publisher Information:
Springer Nature Switzerland, 2023.
Publication Year:
2023
Subject Terms:
Optimization, Passive control, Tuned liquid damper, Jaya algorithm, Design optimization, Tuned liquid dampers, Teaching-learning-based optimization, Learning algorithms, Damping, Device parameters, Meta-heuristics algorithms, Metaheuristic algorithm, Hybrid algorithm, Hybrid algorithms, Damping device, Low-costs, Teaching-learning-based optimizations
Document Type:
Book Part of book or chapter of book<br />Conference object
Language:
English
DOI:
10.1007/978-3-031-50151-7_19
Rights:
Springer Nature TDM
Accession Number:
edsair.doi.dedup.....0d6f5106731d90bb5ece6b55240ea6db
Database:
OpenAIRE

Further Information

Tuned liquid damping devices are a low-cost, passive control system that does not require an external energy source and is effective in damping the dynamic vibrations of structures. Tuning the damper tank geometry and device parameters is important in optimizing the efficiency to be obtained from the control. In this study, tuned liquid damper (TLD) device parameters were optimized with algorithms created by hybridizing metaheuristic algorithms to minimize the structure movement. For this purpose, Jaya (JA) and Teaching-Learning Based Optimization (TLBO) algorithms were hybridized. By optimizing the properties of the TLD, the maximum displacement and total acceleration values of the structure under the critical earthquake record were reduced. In light of the results obtained, it was determined that hybrids may increase the performance of the algorithm in some cases. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.