Cold-formed steel member bending stiffness prediction

Ayhan, Deniz; Schafer, Benjamin W.

doi:10.1016/j.jcsr.2015.07.004

Cited by 13 publications

(8 citation statements)

References 5 publications

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“…The mean and standard deviation of observed-to-predicted ratios of prepeak energy, peak moment, flexural rigidity, and rotation at peak moment are calculated for the tests and FE models as shown in Table 2. The reduction correlates reasonably well with the observed data, and better than available methods [7]. Table 2.…”

Section: Local Buckling Distortional Bucklingsupporting

confidence: 77%

“…As Figure 2 illustrates, local and distortional cross-sectional slenderness are adequate explanatory variables for parameterizing the peak moment strength of CFS members, and are directly utilized by design specifications [2]. In addition to peak strength, the authors have recently provided new closed-form expressions to predict the pre-peak bending stiffness [7]. The proposed expressions also utilize cross-section slenderness as the explanatory variable and adequately predict the available data as well as provide a significant improvement for bending stiffness prediction when compared to current methods.…”

Section: Cold-formed Steel Beam Behavior -Existing Data and Design Mementioning

confidence: 99%

“…These results are than used herein to obtain simplified design expressions for Δθ, ΔM, etc. Design expressions for pre-peak curve is done in [7] and presented in the next section. Design expressions for post-peak are the focus of this paper and presented for local buckling in Section 5.1 and for distortional buckling in Section 5.2.…”

Section: 2simplified Backbone Response Modelmentioning

confidence: 99%

“…A prediction method for rotation and moment, up to the peak moment, has recently been developed by the authors [7]. Correlation with the appropriate local or distortional cross-section slenderness (λl or λd) is used to define simple design expressions for the fully effective moment M1, peak moment M2, and the coinciding rotations θ1 and θ2 as provided in Table 1.…”

Section: Design Expressions For Pre-peak Flexural Rigidity Predictionmentioning

confidence: 99%

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Characterization of in-plane backbone response of cold-formed steel beams

Ayhan

Schafer

2017

Journal of Constructional Steel Research

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Thin-walled cold-formed steel beams are investigated with existing experimental data and shell finite element simulations to characterize their in-plane moment-rotation behavior, up to and past peak strength, in local or distortional failure modes. Although ultimate strength prediction of cold-formed steel members is generally well addressed in design codes, pre-and post-peak member stiffness is only partially addressed; while member ductility and post-peak momentrotation response suffers from a lack of any clear guidance. Without fundamental information on cold-formed steel moment-rotation/curvature response, i.e. the backbone curve, system modeling for cold-formed steel structures to collapse remains severely hampered. Existing data on coldformed steel beams are used as the basis for the study conducted herein. Simplified momentrotation models, motivated from ASCE 41 characterizations, defined with pre-peak flexural rigidity degradation, post-peak plateau and strength drop are explored by equating the area under the backbone moment-rotation response (energy) between the available data and simplified models. In-plane response of cold-formed steel beams is parametrized with new design expressions depending on local and distortional cross-section slenderness. This research provides work for potential incorporation into design standards such as ASCE 41 and AISI S100. Out-ofplane response of cold-formed steel beams, including lateral-torsional buckling, remains as needed future work.

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Section: Local Buckling Distortional Bucklingsupporting

confidence: 77%

Section: Cold-formed Steel Beam Behavior -Existing Data and Design Mementioning

confidence: 99%

Section: 2simplified Backbone Response Modelmentioning

confidence: 99%

Section: Design Expressions For Pre-peak Flexural Rigidity Predictionmentioning

confidence: 99%

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Characterization of in-plane backbone response of cold-formed steel beams

Ayhan

Schafer

2017

Journal of Constructional Steel Research

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“…The concept of effective width also applies to cold formed steel sections[27][28][29][30]and angle connections[31][32][33][34].…”

mentioning

confidence: 99%

Element-based effective width for deflection calculation of steel-concrete composite beams

Yuan

Deng

Yang

et al. 2016

Journal of Constructional Steel Research

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Traditional definition of the effective width of steel-concrete composite beam is based on a certain beam section.Section-based effective width changes from one section to another along the beam span. Therefore, effective width for deflection calculation of composite beam should be evaluated based on an element, rather than a specific section. This paper firstly presents the development of two theoretic models for composite beams. One is shear-lag slip beam model (SSM), which takes into consideration both slip effects and shear-lag effects. The other is slip beam model (SLM), which only considers the interface slip between steel beam and concrete slab. Validation of the theoretic models is performed through comparison of the theoretic predictions with the results obtained from more complex finite element simulations. Based on the theoretic models, an element-based definition of effective width for deflection analysis of composite beams is proposed. Parametric studies are performed to find out the most important parameters influencing effective width. It is demonstrated that the effective width is mostly related to the width of the concrete slab, the span of the beam and the thickness of the floor slab. Simplified design formulas for computing the effective width are proposed. Comparisons between the results of the simplified formulas and the test results indicate the accuracy of the proposed formulas. Key word composite beam, effective width, shear-lag, deflection, design  , a c s J J J

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