Volume 13, Issue 4 (10-2023)
IJOCE 2023, 13(4): 533-561 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Tamjidi Saraskanroud H, Babaei M. CONNECTION TOPOLOGY OPTIMIZATION OF STEEL MOMENT FRAMES USING GENETIC ALGORITHM. IJOCE 2023; 13 (4) :533-561
URL: http://ijoce.iust.ac.ir/article-1-570-en.html
URL: http://ijoce.iust.ac.ir/article-1-570-en.html
1- Department of Civil Engineering, University of Tabriz, Tabriz, Iran
2- Department of Civil Engineering, University of Bonab, Bonab, Iran
2- Department of Civil Engineering, University of Bonab, Bonab, Iran
Abstract: (7584 Views)
Structural topology optimization provides an insight into efficient designing as it seeks optimal distribution of material to minimize the total cost and weight of the structures. This paper presents an optimum design of steel moment frames and connections of structures subjected to serviceability and strength constraints in accordance with AISC-Load and Resistance Factor Design (LRFD). In connection topology optimizations, different beam and column sections and connections and also to optimize two steel moment frames a genetic algorithm was used and their performance was compared. Initially, two common steel moment frames were studied, only for the purpose of minimizing the weight of the structure and the members of structure are considered as design variables. Since the cost of a steel moment frame is not solely related to the weight of the structure, in order to obtain a realistic plan, in the second part of this study, for the other two frames the cost of the connections is also added to the variables. The results indicate that the steel frame optimization by applying real genetic algorithm could be optimal for structural designing. The findings highlighted the prominent performance and lower costs of the steel moment frames when different connections are used.
Keywords: Steel frame optimization, metaheuristic algorithms, connection topology optimization, genetic algorithm
Type of Study: Research |
Subject:
Optimal design
Received: 2023/08/29 | Accepted: 2023/10/18 | Published: 2023/10/18
Received: 2023/08/29 | Accepted: 2023/10/18 | Published: 2023/10/18
Send email to the article author
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
