Behaviour of Steel Plate Shear Walls with Composite Columns
Bibliographic record
Abstract
Research on conventional steel plate shear walls has developed recently to the point where their behaviour is reasonably well understood. However, the potential exists to design steel plate shear walls to take advantage of the benefits of composite columns and in this regard, considerably less information is available to designers. In addition to increasing the axial capacity of the columns, the presence of the concrete increases their flexural stiffness, thereby providing good anchorage for the development of the post-buckling capacity of the infill plate without requiring overly deep members. This research program was initiated with the aim of making partially encased composite columns a viable option available to steel plate shear wall designers. The research program involves the design and testing of three steel plate shear walls with partially encased composite columns as the vertical boundary elements. Gravity loads are applied to the columns and the steel plate shear walls are then loaded laterally under gradually increasing cyclic loads to failure. The paper describes some preliminary results of the completed first test, as well as plans for a test on a modular wall, fabricated primarily with erection economy in mind, and a test with reduced beam sections incorporated into the horizontal boundary elements.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".