Volume 14, Issue 1 (1-2024)                   2024, 14(1): 61-81 | Back to browse issues page

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Goodarzimehr V, Salajegheh F. OPTIMAL DESIGN OF TALL STEEL MOMENT FRAMES USING SPECIAL RELATIVITY SEARCH ALGORITHM. International Journal of Optimization in Civil Engineering 2024; 14 (1) :61-81
URL: http://ijoce.iust.ac.ir/article-1-575-en.html
Abstract:   (10747 Views)
The analysis and design of high-rise structures is one of the challenges faced by researchers and engineers due to their nonlinear behavior and large displacements. The moment frame system is one of the resistant lateral load-bearing systems that are used to solve this problem and control the displacements in these structures. However, this type of structural system increases the construction costs of the project. Therefore, it is necessary to develop a new method that can optimize the weight of these structures. In this work, the weight of these significant structures is optimized by using one of the latest metaheuristic algorithms called special relativity search. The special relativity search algorithm is mainly developed for the optimization of continuous unconstrained problems. Therefore, a penalty function is used to prevent violence of the constraints of the problem, which are tension, displacement, and drift. Also, using an innovative technique to transform the discrete problem into a continuous one, the optimal design is carried out. To prove the applicability of the new method, three different problems are optimized, including an eight-story one-span, a fifteen-story three-span bending frame, and a twenty-four-story three-span moment frame. The weight of the structure is the objective function, which should be minimized to the lowest possible value without violating the constraints of the problem. The calculation of stress and displacements of the structure is done based on the regulations of AISC-LRFD requirements. To validate, the results of the proposed algorithm are compared with other advanced metaheuristic methods.
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Type of Study: Research | Subject: Optimal design
Received: 2024/01/12 | Accepted: 2024/01/1 | Published: 2024/01/1

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