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This paper proposes two new additive approaches to estimate column moment and shear demands in two-storey concentrically braced frames (CBFs) with pinned-ended beams and columns. Analyses are undertaken to obtain column moment and shear demands under strong earthquake shaking. The benchmark model employs a chevron bracing configuration with non-buckling braces, elastic beams and columns, and distributed brace strength (DBS) over the height in proportion to the lateral shear demands. Continuous columns, considering the combined stiffnesses of all those in the frame, were considered. Variations of the benchmark model include (i) changing the total column stiffness, (ii) changing the frame strength distribution to obtain similar brace strengths (SBSs) in both storeys, and (iii) considering beam moment connections to the columns. Elastic response spectrum analysis (ERSA), pushover analysis, and nonlinear time-history analysis (NLTHA) are conducted. Closed-form analytical predictions of column dynamic demands are developed, and a column demand distribution approach is also used. When the full frame was analysed elastically, column moment and shear demands were less than 1% of the column capacity. For the benchmark DBS frame, column flexural/shear demands were similarly negligible during first-mode pushover analysis, but they became significant during NLTHA. For the SBS frames, significant demands were observed during pushover analysis, especially after brace yielding at the first storey. During NLTHA average demands increased to 1.33 times those of the DBS frame. Higher mode demands from ERSA considering the columns alone were generally similar to, or greater than, those from NLTHA for low column stiffness ratios, α, less than 0.1. Adding higher-mode ERSA moments to pushover moments gave good demand estimates for stiff columns with α more than 1.0. Using these findings, a method is developed to estimate the demands on individual columns that considers column relative stiffness. A design example is provided for column flexural/shear demand estimation.
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Dehghanian et al. (2026) studied this question.
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