Non-Linear Analysis of Axially Loaded Built-Up Open Section Cold-Formed Columns

Built-up open cold-formed sections are commonly used in entrances, structural corners, and window frames. These elements exhibit low torsional stiffness and are highly susceptible to cross-sectional deformation. Battened built-up cold-formed steel (CFS) open columns offer enhanced load-carrying capacity when individual profiles cannot withstand applied loads. Extensive research has focused on understanding the buckling behavior of these structural elements. However, limited studies have explored the impact of spacing between cold-formed C-channel sections. Existing research suggests that battened columns with adequately spaced members exhibit superior structural performance compared to those with closely spaced channels. A critical factor affecting the performance of battened columns is the slenderness ratio of the unsupported length (Lz) between batten plates. Despite its significance, this aspect has been insufficiently explored in prior studies. The literature lacks defined limiting values for different column slenderness ratios, back-to-back distances between channel sections, and unsupported lengths between batten plates. Consequently, design methods proposed by various researchers may be unreliable. This study investigates the performance of axially loaded pin-ended columns, comprising two appropriately spaced lipped C-channels arranged back-to-back to form open built-up sections. Finite element models were developed using the ABAQUS platform and validated against test results from the literature. Following validation, the models were used for a comprehensive parametric analysis by varying key parameters, such as back-to-back distance, depth-to-width ratios, number of battens, column slenderness ratios, and the relative slenderness of unsupported chords. The study provides a detailed evaluation of how these parameters influence the structural performance of battened columns, offering valuable insights for design optimization and performance assessment.