Continuing Education

Simulation of Steel Sheet Sheathed Cold-Formed Steel Framed Shear Walls

The objective of this paper is to detail the ongoing development and validation of a high fidelity shell finite element model of steel sheet sheathed cold-formed steel (CFS)-framed shear walls. This effort is part of an ongoing research project: CFS-NHERI, which aims to advance the state of the art for seismic performance and design of mid-rise cold-formed steel framed buildings. The strength potential of steel sheet shear walls is large, but the details are critically important. Motivated by the geometry of a tested steel sheet shear wall the ideal capacity of a steel sheet shear wall is simulated and compared against a large variety of available analytical prediction models and testing. The range of potential strength is much greater than in other CFS shear wall systems. Recently, a number of phenomenological performance-based models were developed for CFS-framed shear walls. Although these models are efficient and useful, they typically do not consider buckling of the steel sheet sheathing, nor deformations outside of the localized sheathing-to-chord stud fastener zones, nor cross-section deformations in the cold-formed steel framing, nor stiffness reductions due to local and/or distortional buckling of the stud or track. All of these aspects can be incorporated in a more general modeling framework as implemented in a predominately shell finite element-based model. Both single steel sheet sheathed and double steel sheet sheathed shear wall models are examined herein. CFS members and the steel sheet sheathing are modeled with shell elements while sheathing-to-frame fasteners are modeled with springs. The developed models are being validated against available test data and show promise, but more work is required before the models can be considered complete. The models will be used to predict and augment ongoing and future testing in the CFS-NHERI project and to conduct parametric studies to determine improved details and performance.

  • Date: 4/2/2019 - 4/5/2019
  • PDH Credits: 0


Zhidong Zhang and B.W. Schafer; Johns Hopkins University; Baltimore, MD

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