Details

Autor(en) / Beteiligte

• Rahnavard, Rohola
• Craveiro, Hélder D.
• Lopes, Marco
• Simões, Rui A.
• Laím, Luís
• Rebelo, Carlos

Titel

Concrete-filled cold-formed steel (CF-CFS) built-up columns under compression: Test and design

Ist Teil von

• Thin-walled structures, 2022-10, Vol.179, p.109603, Article 109603

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2022

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• This paper aims to present the axial behavior of a new composite column through an experimental and computational investigation. Four distinct configurations of novel CF-CFS columns were evaluated. The test setup and results were documented in detail, including load-bearing capacity, load–deformation, and failure modes. The buckling behavior of the steel components (thin-walled steel profiles) was investigated. The mitigation of local buckling caused by concrete supporting thin-walled plates was explored. Additionally, numerical simulations were performed and calibrated against the experimental results. A comparison was made between experimental results and analytical prediction according to EN 1994-1-1 formulations to assess the validity of current codes. The effective cross-sectional areas were also evaluated for the buckling load prediction since Class 4 profiles were used. The results showed that the analytical predictions according to the EN 1994-1-1 (taking to account steel gross cross-section and buckling curve a) are conservative for square CF-CFS columns and unconservative for rectangular sections. While for the case of rectangular CF-CFS columns, the experimental results and design prediction according to the EN 1994-1-1 are in good agreement when steel effective cross-section area and buckling curve-c are considered. Reliability analysis was also performed, resulting in a more reliable design methodology by considering the effective cross-sectional area for CFS profiles. •Investigate the novel concrete-filled cold-formed steel built-up columns experimentally.•Evaluating the contribution of the composite column components.•Developing a numerical model to understand the component contribution.•Comparison of the experimental results and code predictions.