Performance-Based Capacity Design of Steel Plate Shear Walls. II: Design Provisions
Bibliographic record
Abstract
This is Part II of two companion papers on performance-based capacity design of steel plate shear walls. These papers aim to provide a holistic and sound basis for capacity design of steel plate shear walls to any of three explicit performance levels (ductile, moderately ductile, and limited-ductility), with emphasis on design requirements for applications involving lower ductility demands. In this paper, Part II, existing design provisions for ductile steel plate shear walls are briefly reviewed and discussed, with some modifications recommended, and capacity design provisions for limited-ductility walls are proposed based on the development principles presented in Part I. Capacity design provisions for moderately ductile walls are then rationalized based on the development principles for the other two performance levels. The proposed capacity design methods for the limited-ductility and moderately ductile performance levels are applied to design examples, and the results are discussed in the context of the observed performance of two multistory steel plate shear walls tested under cyclic lateral loading.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".