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Abstract This article investigates the behavior of hybrid FRP Concrete-Steel columns with an elliptical cross section. The investigation was carried out by gathering information through literature and conducting a parametric study, which resulted in 116 data points. Moreover, multiple machine learning predictive models were developed to accurately estimate the confined ultimate strain and the ultimate load of confined concrete at the rupture of FRP tube. Decision Tree (DT), Random Forest (RF), Adaptive Boosting (ADAB), Categorical Boosting (CATB), and eXtreme Gradient Boosting (XGB) machine learning techniques were utilized for the proposed models. Finally, these models were visually and quantitatively verified and evaluated. It was concluded that the CATB and XGB are standout models, offering high accuracy and strong generalization capabilities. The CATB model is slightly superior due to its consistently lower error rates during testing, indicating it is the best model for this dataset when considering both accuracy and robustness against overfitting.

This article investigates the behavior of hybrid FRP Concrete-Steel columns with an elliptical cross section. The investigation was carried out by gathering information through literature and conducting a parametric study, which resulted in 116 data points. Moreover, multiple machine learning predictive models were developed to accurately estimate the confined ultimate strain and the ultimate load of confined concrete at the rupture of FRP tube. Decision Tree (DT), Random Forest (RF), Adaptive Boosting (ADAB), Categorical Boosting (CATB), and eXtreme Gradient Boosting (XGB) machine learning techniques were utilized for the proposed models. Finally, these models were visually and quantitatively verified and evaluated. It was concluded that the CATB and XGB are standout models, offering high accuracy and strong generalization capabilities. The CATB model is slightly superior due to its consistently lower error rates during testing, indicating it is the best model for this dataset when considering both accuracy and robustness against overfitting. [ABSTRACT FROM AUTHOR]

Thin-walled columns have been widely employed as energy absorbers for vehicle structures due to their dramatic merits of high energy absorption to weight ratios. Meanwhile, columns filled with low-density metal foams have demonstrated notable improvement on energy absorption capabilities compared with their empty counterparts. Accordingly, the present study aims to investigate and optimize the crashworthiness characteristics of novel foam–filled elliptical column (F-EC) under multiple oblique impact loading. More specifically, the finite element (FE) models of hollow and foam-filled elliptical columns (H-EC, F-EC) are first built and validated against theoretical and experimental outcomes. On this basis, a detailed crashworthiness comparison between the elliptical columns (ECs) and the circular columns (CCs), including hollow and foam-filled columns (H-CC, H-EC, F-CC, F-EC), reveals the superiority of F-EC relative to others on overall crashworthiness characteristics under multiple oblique impact loading. Next, a Taguchi-based design of experiment (DoE) is implemented to investigate the impact of column parameters of F-EC, including the sectional ellipticity e , the column thickness t and the foam density ρ f , on the column peak crushing force under axial impact loading ( PCF 0 ) and overall specific energy absorption under multiple oblique impact loading ( SEA θ ). Subsequently, the Taguchi method coupled with grey relational analysis (GRA) is utilized to explore the optimal design of F-EC for maximizing SEA θ and minimizing PCF 0 simultaneously, which is then verified through a detailed crashworthiness comparison between the optimized design and the original design. The optimal F-EC reveals more superior crashworthiness characteristics relative to the original design and thus demonstrates enormous potential as a candidate energy absorber particularly under multiple oblique impact loading. [ABSTRACT FROM AUTHOR]

• Cyclically loaded elliptical concrete confined by FRP (FCC) is investigated. • Mechanism of non-uniform hoop strain distribution is clarified. • Cyclic behavioral characteristics of elliptical FCC are properly modeled. The previous studies on elliptical concrete confined with fiber-reinforced polymer (FRP) are mainly concerned with their monotonic compressive responses. By contrast, no research has been focused on their performance under cyclic axial loading. Motivated by this research gap, the behavioral characteristics of cyclically compressed elliptical FRP-confined concrete (FCC) were investigated in this research. The experimental parameters included the aspect ratio varying between 1.0 (circular section), 1.3, 1.7 and 2.0, the number of FRP layers, and the loading pattern (monotonic loading or two schemes of cyclic loading). The results revealed that plastic strains and stress degradation in elliptical FCC were confinement-independent parameters, regardless of confinement efficiency (affected by sectional geometry) and confinement level (governed by FRP thickness). This was similar to the case of cyclically loaded rectangular FCC (characterized by depth-to-width ratio). Moreover, the mechanism of non-uniform hoop strain distribution was dominated by two aspects, namely curvature radius-induced varying confinement stiffness and concrete cracking-induced strain localization. In contrast, the cyclic loading had a marginal effect on this distribution. Based on the monotonic model (considered as envelope curve) for elliptical FCC and the hysteretic rules originally for circular FCC, the complete compressive behavior of cyclically loaded elliptical FCC could be modeled with favorable accuracy. [ABSTRACT FROM AUTHOR]