Achieving a Stable Inelastic Seismic Response for Multi-Story Concentrically Braced Steel Frames
Bibliographic record
Abstract
Recent seismic design provisions (CSA, 2001; AISC, 2002) for concentrically braced steel frames (CBFs) aim at dissipating seismic input energy through inelastic deformations in the bracing members. These deformations include tension yielding of the braces as well as plastic hinge rotation that develops upon buckling of the braces in compression and subsequent straightening of the braces when pulled in tension in the next loading cycle. Over the years, researchers have gained a good understanding of the hysteretic response of steel braces (Jain, Goel, and Hanson, 1980; Popov and Black, 1981; Astaneh-Asl and Goel, 1984; Astaneh-Asl, Goel, and Hanson, 1985) and detailing requirements such as maximum b/t and KL/r ratios are now prescribed in codes to achieve ductile brace response. Capacity design rules have also been introduced in codes to prevent premature failure of the brace connections and ensure that the response of the beams and columns will remain essentially elastic (Tremblay, 2001). Concentrically braced steel frames are particularly vulnerable to dynamic instability under seismic ground motions compared to other lateral load resisting systems due to the inherent poor hysteretic response of the diagonal bracing members and the tendency to develop story mechanisms in multi-story applications. The stability of CBFs responding in the nonlinear range to earthquake ground motions is a complex problem that depends on several parameters including the properties of the bracing members, the bracing configuration, the characteristics of the ground motions, the lateral resistance of the structure relative to the seismic demand and the amount of gravity loads supported by the structure. In multi-story frames, the potential for collapse by instability is also influenced by other parameters including the number of floors and the distribution of the lateral resistance over the building height. As of today, no simple method has been proposed for design purposes to adequately capture the combined effects of all these parameters.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".