Multi‐objective optimization design of concrete outriggers based on Genetic–HookeJeeves algorithm: Reducing lateral deflection, differential axial shortening, and construction cost of the structure

Mahya Safarkhani, Morteza Madhkhan
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Abstract

SummaryIn the context of tall concrete structures, it is crucial to not only control the lateral displacement of the building but also address the issue of differential axial shortenings in its vertical elements. Concrete outriggers, commonly resembling relatively stiff beams spanning one to two floors, connect the central core to exterior columns. The strategic placement and appropriate stiffness of these outriggers at different heights of the structure can significantly influence the overall behavior of the entire structure. This study focuses on optimizing the location, depth, and thickness of concrete outriggers, along with the dimensions of beams and columns, as well as the thickness of the core shear wall with the objective of minimizing construction costs and mitigating the occurrence of lateral displacement and differential axial shortenings within the structure. To achieve this, a combined approach of the Genetic–HookeJeeves algorithm has been employed. In this research, we have integrated HookeJeeves, a local search algorithm, with the genetic algorithm to create a hybrid approach that demonstrates high convergence performance. The structural modeling and analysis were conducted using ETABS finite element software, while a Euro‐International Concrete Committee model (CEB model) was utilized to assess the magnitude of differential axial shortenings, enabling us to approximate the long‐term behavior of concrete. The findings of this study highlight the significant impact of the location and stiffness of outriggers on mitigating both lateral displacement and differential axial shortenings within the structure. Optimal placement of an outrigger resulted in a 16% reduction in lateral displacement, and this value could reach up to 25% when the outrigger possessed the ideal stiffness. Additionally, such an arrangement led to a remarkable 36% decrease in the maximum differential axial shortening observed in the structure. These outcomes demonstrate that meeting the design requirements of the intended structure not only improves its performance but also reduces construction costs by 31%.
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基于遗传-Hooke-Jeeves 算法的混凝土支腿多目标优化设计:减少结构的横向挠度、轴向缩短差和施工成本
摘要 在高层混凝土结构中,至关重要的是不仅要控制建筑物的横向位移,还要解决其垂直构件的不同轴向缩短问题。混凝土支腿通常类似于横跨一至两层楼的刚度相对较大的梁,将中央核心筒与外部支柱连接起来。这些支腿在结构不同高度的战略位置和适当的刚度会对整个结构的整体行为产生重大影响。本研究的重点是优化混凝土支腿的位置、深度和厚度,以及梁和柱的尺寸和核心筒剪力墙的厚度,目的是最大限度地降低建筑成本,并减轻结构内发生的横向位移和轴向短缩差异。为此,我们采用了遗传-Hooke-Jeeves 算法相结合的方法。在这项研究中,我们将局部搜索算法 HookeJeeves 与遗传算法相结合,创建了一种混合方法,该方法具有很高的收敛性能。我们使用 ETABS 有限元软件进行了结构建模和分析,并利用欧洲-国际混凝土委员会模型(CEB 模型)评估了轴向短缩差异的大小,从而使我们能够近似分析混凝土的长期行为。这项研究的结果突出表明,支腿的位置和刚度对减轻结构内的横向位移和轴向短缩差异具有重要影响。支腿的最佳位置可使侧向位移减少 16%,当支腿具有理想刚度时,这一数值可达到 25%。此外,这种布置还使结构中观察到的最大轴向缩短差显著减少了 36%。这些结果表明,满足预期结构的设计要求不仅能提高其性能,还能降低 31% 的施工成本。
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