Continuing Education

Characterization of the Moment-Rotation Response of Cold-Formed Steel Beams

The objective of this study is to provide a prediction method for characterizing the complete moment-rotation (M-θ) response of cold-formed steel (CFS) members in bending. The work is an ancillary effort related to the National Science Foundation funded Network for Earthquake Engineering Simulation (NEES) project: CFS-NEES (www.ce.jhu.edu/bschafer/cfsnees). The goal of CFS-NEES is to enable performance-based seismic design for cold-formed steel framed buildings. A basic building block of performance-based seismic design is nonlinear structural analysis. For cold-formed steel members, which suffer from local and distortional buckling, existing codes provide peak strength and approximations for stiffness loss prior to peak strength, but no estimation of post-peak M-θ behavior. Complete M-θ response is necessary for nonlinear structural analysis of CFS framed buildings. In this research, existing data, obtained by experiments and finite element analysis, are processed to examine the complete M-θ response in cold-formed steel beams. Using a modification of the simplified model introduced in ASCE 41 for pushover analysis, the M-θ response is parameterized into a simple multi-linear curve. The parameters include the initial stiffness, fully effective limit, reduced pre-peak stiffness, peak moment, post-peak plateau, and post-peak rotation at 50% of the peak moment. It is shown herein that the parameters of this multi-linear M-θ curve may themselves be readily predicted as a function of either the local slenderness or distortional slenderness of the cross-section, as appropriate. Accuracy of the proposed M-θ approximation is assessed. The impact of utilizing the full M-θ response in a single and multi-span CFS beam is demonstrated. The proposed prediction method for M-θ provides a necessary step in the development of nonlinear structural analysis of CFS systems.

  • Date: 4/18/2012 - 4/20/2012
  • PDH Credits: 0

Speaker

D. Ayhan; B.W. Schafer; Johns Hopkins University; Baltimore; MD

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