Improving Overturning Stiffness of Steel Plate Shear Walls
Bibliographic record
Abstract
Steel Plate Shear Walls (SPSWs) are efficient and economical energy dissipating systems for buildings located in regions of high seismic risk. In spite of many benefits of SPSWs, however, their overturning stiffness is relatively low, especially in mid-to-high rise buildings. Therefore, there is a need for incorporating other structural elements in conjunction with such systems to resist high overturning moments resulting from lateral loads. A logical solution that can be effectively used in SPSW systems is to rigidly connect the girders of adjacent bays to the columns of SPSWs (on both sides) forming an interacting system of shear wall and moment frame in which the adjacent girders act as outriggers to reduce the overturning moments in the SPSW. However, insufficient information exists on behavior and efficiency of such structural system, herein referred to as SPSW with Outriggers (SPSW-O). As part of a comprehensive research project on SPSWs being conducted at the University of Alberta, this paper describes different potential SPSW-O options and discusses their effectiveness in improving the flexural stiffness of the system. The performance of these options is evaluated for 20-story SPSW-O systems using nonlinear static and response history analyses.
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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 | 0.000 | 0.001 |
| 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".