Characterisation of material and connection behaviour in sheathed cold-formed steel wall systems – Part 2: Analytical modelling. (April 2021)

• Record Type: Journal Article
• Authors: Kyprianou, Constantinos; Kyvelou, Pinelopi; Gardner, Leroy; Nethercot, David A.
• Is Part Of: Structures. Volume 30(2021)
• Page Start: 1184
• Page End: 1199
• Publication Date: 2021-04
• Subjects: Cold-formed steel -- OSB -- Plasterboard -- Pull-through -- Push-out -- Screw connectors -- Sheathing; Structural engineering -- Periodicals; 624.1
• DOI: 10.1016/j.istruc.2020.12.052
• Languages: English
• ISSNs: 2352-0124

Abstract

Abstract: Analytical models to describe the material and connection behaviour of the key components of sheathed cold-formed steel wall systems are developed and assessed in the present paper. The experimental data generated and collected in the companion paper (Kyprianou et al. [1]) are utilised for the calibration of the developed models. The assembled experimental database comprises the results of more than 400 physical tests, featuring material tests on plasterboard and oriented strand board (OSB), screw connector tests as well such as pull-through and push-out tests. The Ramberg–Osgood model (Ramberg and Osgood [2]) was shown to accurately describe the stress–strain behaviour of both plasterboard and OSB in the longitudinal and transverse direction in both tension and compression, while the Mander model (Mander et al. [3]) was also shown to accurately capture the compression behaviour for both materials and to follow the post peak unloading response. A generalised Ramberg–Osgood curve with linear post-peak unloading was adopted for describing the pull-through load-deformation behaviour of screws in OSB and plasterboard, while a similar generalised Ramberg–Osgood formulation, but with different exponents for the initial and subsequent parts of the curve was shown to accurately capture the shear load-slip behaviour of screws in steel-to-board connections. Predictive expressions for the ultimate capacities and recommended values for the remaining model parameters are provided herein. The developed predictive models are suitable for use in numerical simulations and advanced design methods.