Numerical modeling of the post-fire performance of strap-braced cold-formed steel shear walls
Shuna Ni, Xia Yan, Matthew Hoehler, Thomas Gernay
Strap-braced, cold-formed steel framed walls are frequently used as the lateral force resisting system in cold-formed steel construction. While the behavior of these walls has been studied under lateral loading and (to a lesser extent) under fire conditions, there is a need to comprehend the influence of multi-hazard interactions, in particular the effect of fire pre-damage on the lateral load resistance of the walls. In this paper, a numerical model of a strap-braced cold-formed steel wall is developed to analyze the thermal and structural response when subjected sequentially to fire followed by shear deformation. The numerical model is validated against full-scale experiments. Coupon tensile tests are conducted to characterize the post-fire properties of the cold-formed steel that are used as inputs to the model. The results show that the numerical model can capture the post-fire response of the cold-formed steel walls including the wall strength, stiffness and ductile failure by yielding of the strap. The lateral behavior of the walls depends primarily on the maximum temperature reached in the cold-formed steel members and the resulting residual properties. Thermal analysis by the finite element method can be used to predict the maximum temperatures across a wall section under a variety of design-relevant fire scenarios, but the results are strongly affected by the quality of the data on thermal properties and by the loss of integrity of the gypsum sheathing. This study validates the numerical modeling strategy and suggests that the post-fire lateral capacity of the walls can be predicted from ambient temperature methods with use of the cold-formed steel residual mechanical properties.
, Yan, X.
, Hoehler, M.
and Gernay, T.
Numerical modeling of the post-fire performance of strap-braced cold-formed steel shear walls, Thin-Walled Structures, [online], https://doi.org/10.1016/j.tws.2021.108733, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=931982
(Accessed July 7, 2022)