Local and global instabilities of rolled T-section columns under axial compression. (September 2022)

• Record Type: Journal Article
• Authors: Li, Liya; Fafard, Mario; Boissonnade, Nicolas
• Is Part Of: Thin-walled structures. Volume 178(2022)
• Publication Date: 2022-09
• Subjects: Overall Interaction Concept -- T-section columns -- Coupled instabilities; Thin-walled structures -- Periodicals; 690.1
• DOI: 10.1016/j.tws.2022.109517
• Languages: English
• ISSNs: 0263-8231

Abstract

Abstract: The resistance capacity of rolled T-section columns comprising slender webs is investigated in this paper. Both (i) cross-sectional behavior influenced by local buckling and (ii) member behavior influenced by global buckling are investigated through extensive numerical analyses. Regarding cross-section resistance, current design rules rely on the traditional cross-section classification system and the Effective Width Method (EWM), while local–global coupled instabilities in members with slender plate elements are usually addressed through the EWM combined with flexural–torsional buckling curves, which leads to conservative and scattered predictions for T-section members, mainly because the effects of torsional buckling are considered twice: through the EWM and through the member buckling curves. To overcome these shortcomings, an Overall Interaction Concept (OIC) approach is proposed in this paper, providing a more economic and simple design method for both T-section members. The load resistances predicted by the OIC, Eurocode 3, the American Specifications and the Australian Standards are compared with numerical and experimental results. Overall, the results show that the OIC-based approach provides more accurate and consistent predictions than current design recommendations and is suitable to be included in current steel structural design standards. Highlights: The local–global coupled instabilities of T-section columns were investigated. The O.I.C. design for T-section columns under axial compression was proposed. More accurate O.I.C.-based resistance predictions are obtained than existing codes.