Ring Shaped-Steel Plate Shear Wall Lateral Torsional Buckling Behavior
Bibliographic record
Abstract
Steel plate shear walls (SPSWs) are a prevalent, internationally used lateral load resisting system. They have mainly been utilized in buildings in the United States, Canada, and Japan. However, despite their popularity, they also present a few challenges; their hysteretic behavior is pinched, the web plate has negligible stiffness during load reversals, and moment connections are required between the horizontal boundary elements (HBE) and vertical boundary elements (VBE). Ring shaped—steel plate shear walls (RS-SPSWs) are a novel structural system that offer improved seismic performance by mitigating the challenges of conventional SPSWs. A buckling study was performed on RS-SPSWs utilizing finite element analysis. The conclusions of the buckling study can be used to prevent lateral torsional buckling of the RS-SPSW rings, resulting in good hysteretic performance. This paper outlines how non-dimensional slenderness ratios, such as ring radius to ring width, ring radius to plate thickness, and ring width to plate thickness, affect the buckling behavior of RS-SPSW infill panels. The study concludes that the limiting rotation allowable in the quarter-arc segments of the rings before hysteretic performance starts to degrade is 0.08 radians. It was found that setting the ratio of ring width to plate thickness equal to 11 or less limits the quarter-arc ring rotation to be below the limit and lateral torsional buckling was prevented.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".