Geometric Parameters and Behavior Factor of Knee-Braced Steel Frames Using Nonlinear Static Pushover (NSP) Analyses
Bibliographic record
Abstract
During the recent years, the new knee-braced frame (KBF) system has been interested to achieve a proper seismic behavior. Briefly introducing KBF, the present study evaluates the geometric parameters and behavior factor of multi-story knee-braced steel frames. The studied models include three-, five- and eight-story steel CBFs, EBFs and KBFs. Using linear static analyses, the present study evaluates lateral stiffness of knee-braced frames and plots their co-stiffness curves. Using co-stiffness curves, then, the best range is determined for geometric parameters of KBFs to achieve the proper stiffness. In addition, ductility-related seismic force reduction factor (Rμ), incremental resistance coefficient (RS), and behavior factor (R) are calculated for the frames using incremental nonlinear static analyses, and compared with the corresponding concentric and eccentric frames.
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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) | 0.000 | 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 | 0.000 | 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".