Effect of shear stud clusters in composite girder bridge design
Bibliographic record
Abstract
As part of ongoing efforts to accelerate bridge construction in Ontario, the Ministry of Transportation of Ontario (MTO) has turned increasingly to prefabricated bridge technology as a bridge construction method when conditions allow. One of the prefabricated deck systems commonly used by MTO involves installing precast full-depth deck panels with pre-formed shear pockets on top of the naked steel girders, which are then made composite with the girders through shear studs installed inside the shear pockets. Construction of the deck slab is completed by filling the shear pockets with in situ concrete. Recent prefabricated bridge projects have shown an increasing tendency to concentrate the shear studs into clusters of closely-spaced studs in shear pockets that are spaced at relatively large distances apart. Concerns have been raised about the effectiveness of the resulting composite action between the precast panels and the supporting girders. As a result, MTO’s Bridge Office recently carried out a comprehensive experimental research study to investigate the issue by using reduced scale models of single composite beam systems as well as shear push-out specimens. This paper describes the laboratory research project and the tests that were carried out and discusses the results obtained. Comparisons with theoretical results are made to assess the composite action that is developed. Experimental test results indicate that closely-spaced studs in the shear pockets in the precast deck panels provide adequate composite action in composite bridge girder design.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".