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    Local buckling strength enhancement due to non-slender flanges in web perforated plain channel columns
    (Elsevier Ltd, 2025) Francis, R.; Shabhari, A.; Jeyapragasam, V.V.K.; Chandrasekar, D.
    Cold-formed steel columns are the primary compression members in housing and industrial storage racks, with discrete holes or closely spaced web perforations. The element slenderness and web perforations influence the local buckling capacity. This study examines the local buckling capacity of slender web plain channel cross-sections with non-slender or slender flanges in the presence of web perforations. Fourteen plain channel stub column tests were conducted on two cross-section aspect ratios, two perforation shapes, with three perforation orientations. Further, a comprehensive parametric study was conducted using validated Finite Element models. The local buckling strength of unperforated and web-perforated cold-formed plain channel columns is evaluated using the Direct Strength Method (DSM) and Modified Direct Strength Method (MDSM). The increase in local buckling strength due to non-slender flanges becomes significant, depending on the aspect ratio and non-dimensional local buckling slenderness ratio of the plain channel cross-section. This research provides the scope to expand the applicability of DSM and MDSM design strength predictions from cold-formed steel design to general thin-walled steel sections, where the welded thin-walled steel sections can have different element thicknesses. As the element thickness plays a crucial role in element slenderness and inter-element interaction, the local buckling capacity prediction available for uniform cross-section thickness can be unduly conservative. This study highlights the significance of element slenderness and effective area reduction due to perforation shape and orientation in the local buckling strength of cold-formed plain channel sections. © 2025 Institution of Structural Engineers. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.