Analysis and Design Methods for Improved Stability of Two-Tiered Steel Eccentrically Braced Frames with Continuous I-Shaped Links
Bibliographic record
Abstract
A set of seismic analysis and design requirements are presented to improve seismic stability of steel two-tiered eccentrically braced frames (EBFs) with I-shaped link beams. The proposed requirements include strength, stability, and stiffness provisions for braces, intermediate beams, and columns. In particular, these requirements aim to make use of intermediate beams to limit out-of-plane deformation of diagonal braces, torsionally brace the link beam in the intermediate level using diagonal braces, utilize column stiffness and strength to brace the intermediate beam out-of-plane, estimate and account for in-plane bending demands of the columns due to uneven yielding of the links, and control inelastic link rotation. The proposed special analysis and design requirements for two-tiered steel EBFs prevent excessive out-of-plane deformation of the intermediate beam and columns, promote sequential yielding of link beams, and limit inelastic rotation of the link in the tier experiencing the largest lateral deformation. The proposed requirements are demonstrated for a case study two-tiered EBF. Nonlinear static and dynamic analyses are performed to evaluate the seismic response of the case study frame against the frame designed without special design provisions and to validate the proposed requirements.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".