A simplified seismic design method for limited-ductility steel multi-tiered concentrically braced frames in moderate seismic regions
Bibliographic record
Abstract
Steel multi-tiered concentrically braced frames (MT-CBFs) represent a bracing configuration where two or more concentric bracing panels are stacked between the ground and roof levels in tall single-storey buildings. A large proportion of MT-CBFs in Canada are located in low-to-moderate seismic regions (seismic category 0–3) where limited ductility CBFs are often preferred in design. Nevertheless, brace tensile yielding may not occur in all tiers of such frames. Additionally, the analysis and design procedure adopted by the 2019 Canadian steel design standard (CSA S16-19) can become tedious in tall frames with multiple panels. In this paper, the seismic behaviour of limited ductility MT-CBFs in moderate seismic regions of Canada is examined to propose a simplified design method. A set of 16 prototype MT-CBFs is designed in accordance with CSA S16-19, excluding the design requirements prescribed for MT-CBF columns. Nonlinear dynamic analyses are then performed to examine their seismic response. Finally, an efficient design method is proposed in the framework of CSA S16-19.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".