Dynamic Analysis of Steel Multi-Tiered Special Concentrically Braced Frames
Bibliographic record
Abstract
Steel multi-tiered concentrically braced frames (MT-CBFs) are commonly used in North America as lateral load-resisting systems of tall single-story buildings. MT-CBFs are composed of multiple tiers of diagonal braces stacked on top of each other along the height of a story. Past research showed that MT-CBF columns designed in accordance with the 2010 U.S. Seismic Provisions are prone to column buckling due to non-uniform distribution of inelastic seismic demands along the frame height. Special design provisions have been introduced in the current AISC Seismic Provisions to address limit states and ensure columns remain stable under seismic load effects. Nevertheless, the recent improvements lack full-scale experimental testing and comprehensive finite element simulations to validate the proposed design requirements further and improve design provisions. In this paper, the current seismic design provisions for multi-tiered special concentrically braced frames (MT-SCBFs) are evaluated using the finite element method. A two-tiered SCBF was first designed in accordance with the 2010 and 2016 AISC Seismic Provisions. A detailed finite element model of the frame was then created using the Abaqus program. The model was used to perform nonlinear history response analyses. The analysis results showed that the inelastic deformations in the frame, designed as per the 2010 AISC Seismic Provisions, are not uniformly distributed but rather concentrated in one of the tiers, which leads to column yielding and buckling. Whereas, the current design method led to distributing the frame’s inelastic deformation along the frame height. Furthermore, it was found that column in-plane flexural demands are overestimated when the current seismic provisions are employed; however, the out-of-plane flexural demand of columns exceeded the code-specified demands.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".