An innovative multi-objective optimization approach for compact concrete-filled steel tubular (CFST) column design utilizing lightweight high-strength concrete

Q1 Engineering International Journal of Lightweight Materials and Manufacture Pub Date : 2024-02-01 DOI:10.1016/j.ijlmm.2024.01.004

Iman Faridmehr , Moncef L. Nehdi , Ali Farokhi Nejad , Mohammad Ali Sahraei , Hesam Kamyab , Kiyanets Aleksandr Valerievich

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Abstract

Incorporating sustainability into Concrete-Filled Steel Tubular (CFST) columns' optimization can enhance efficiency and sustainability in construction. Discrepancies in international standards for ultimate load capacity computation in compact CFST columns under eccentric loading, particularly with lightweight high-strength concrete, pose challenges. This research compile a dataset of compact CFST columns, evaluating design codes (AISC 360-16, Eurocode 4) against experimental results. Besides, a comprehensive finite-element model predicts compact CFST column performance, investigating axial force-moment (P-M) interaction behavior with respect to the material strength ratio ( $f_{y}$ / $f_{c}^{'}$ ). In the second phase of the study, an ANN model, incorporating input parameters, estimates axial load capacity, facilitating multi-objective optimization for optimal CFST column geometry. The results confirmed that Eurocode 4 outperforms AISC 360-16 in experimental axial capacity predictions ( $N_{u c}$ / $N_{u c, t h e o r e t i c a l}$ ) where, the mean and standard deviation for Eurocode 4 were estimated at 1.07 and 0.22, respectively, compared to 1.21 and 0.29 for AISC 360-16. Besides, statistical metrics confirm the precision of the ANN model, particularly with high-strength concrete, promising efficiency in future computational intelligence-based structural design platforms.

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利用轻质高强度混凝土进行紧凑型混凝土填充钢管 (CFST) 柱设计的创新多目标优化方法

将可持续性融入混凝土填充钢管（CFST）柱的优化中，可以提高建筑的效率和可持续性。偏心荷载下紧凑型 CFST 柱的极限承载力计算国际标准存在差异，尤其是轻质高强度混凝土，这给研究带来了挑战。本研究汇编了紧凑型 CFST 柱的数据集，根据实验结果评估了设计规范（AISC 360-16、Eurocode 4）。此外，一个全面的有限元模型预测了紧凑型 CFST 柱的性能，研究了与材料强度比（fy/fc′）相关的轴力-力矩（P-M）相互作用行为。在研究的第二阶段，一个包含输入参数的 ANN 模型估算了轴向承载能力，从而促进了 CFST 柱最佳几何形状的多目标优化。结果证实，Eurocode 4 在实验轴向承载力预测（Nuc/Nuc,理论值）方面优于 AISC 360-16，Eurocode 4 的平均值和标准偏差分别为 1.07 和 0.22，而 AISC 360-16 的平均值和标准偏差分别为 1.21 和 0.29。此外，统计指标证实了 ANN 模型的精确性，尤其是在高强度混凝土方面，有望在未来基于计算智能的结构设计平台中发挥高效作用。

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