Seismic Performance Improvement of Deep Wide Flange Steel Columns Using Stiffeners

Date

2025-7-30

Author

Bağçıvan, Elvan

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This thesis investigates the seismic performance of deep, wide-flange (DWF) steel columns subjected to cyclic loading, focusing on the enhancement of local stability through the implementation of longitudinal stiffeners. The need for this study arises from recent updates to AISC 341-22, which introduced more stringent slenderness limits for highly ductile members. As a result, several deep column sections previously classified as highly ductile under AISC 341-16 are now disqualified from use, creating a significant design gap. The study begins with the development and validation of finite element models using experimental data. A total of 135 models are analyzed to assess the influence of stiffener length, boundary conditions, and loading protocols. Following this, a comprehensive parametric study involving 700 additional models is conducted to propose practical design recommendations. The impact of axial load level, boundary conditions, and loading protocol type (far-field and near-fault) on the effectiveness of stiffeners is evaluated. Results reveal that longitudinal stiffeners significantly improve drift capacity without altering the nominal flexural strength of the section. Stiffener effectiveness is more pronounced at lower axial loads, and its benefit diminishes with increasing L/ry ratios and higher axial loads. Design-oriented recommendations are tabulated, including stiffener length, thickness, and section slenderness constraints. Proposed design curves allow previously excluded DWF columns to meet the 0.04 radian drift requirement specified for highly ductile members in AISC 341-22. The findings contribute to improving seismic resilience in steel moment-resisting frames.

Subject Keywords

Deep Wide Flange Columns, Local Buckling, Longitudinal Stiffeners, Seismic Performance, Finite Element Modeling

URI

https://hdl.handle.net/11511/115518

Collections

Graduate School of Natural and Applied Sciences, Thesis