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        Structural Design Optimization of All-Steel Buckling-Restrained Braces Using Intelligent Optimizers

        Seyed Mohamad Hoseini,Hossein Parastesh,Iman Hajirasouliha,Ahmad Ferdowsi 한국강구조학회 2021 International Journal of Steel Structures Vol.21 No.6

        This study aims to introduce a novel optimal structural design framework for buckling-restrained braces (BRBs) in multi-story buildings. Five artifi cial intelligence (AI) algorithms, including particle swarm optimization (PSO), shuffl ed frog-leaping algorithm (SFLA), interior search algorithm (ISA), hybrid of bat and particle swarm optimization (BAT-PSO), and political optimizer, which is recently proposed, are adopted for the optimum design of BRB systems. In the proposed optimization process, the BRB cross-sectional area is taken as the objective function considering the stiff ness-strength criteria. As a result, by optimizing the BRB cross-sectional area, the weight of BRBs will reduce. Two mostly-used cross-sectional profi les for all-steel BRBs (circular and rectangular) are considered. In general, the optimized solutions using AI algorithms were more cost eff ective and exhibited considerably better structural performance in terms of global buckling requirements in comparison to other conventional BRB designs. The results showed that BAT-PSO worked the best in terms of objective function value and computational time. The design solutions obtained using BAT-PSO were lighter (35% for circular profi les and 20% for rectangular profi les), and had superior performance in terms of both stiff ness and strength in comparison with the conventional BRB designs. It was also shown that using circular profi le can reduce the weight of BRB elements by around 15% compared to rectangular profi le. The results of this study should prove useful in more effi cient design of BRB systems in common practice.

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