STR-923: FATIGUE OF STUD SHEAR CONNECTORS IN STEEL-PRECAST COMPOSITE BRIDGES
Bibliographic record
Abstract
Modular bridge systems consisting of precast concrete deck panels connected to steel girders are becoming increasingly popular due to their rapid construction and optimal material utilization. The shear connection is a critical element of the system, having significant impacts on construction time, economic and environmental cost, structural integrity, and durability. Today welded shear studs are by far the most common type of shear connection. In steel-precast composite bridges, the studs are commonly grouped together so that the precast deck panels can be affixed to the girders by providing full depth “shear pockets” filled with grout. A laboratory beam testing program is underway at the University of Waterloo to investigate the effect of cyclic loading on stud shear connectors in cast-in-place and precast bridge girders. The program consists of twelve beam specimens, uniquely tested using a variable amplitude load history simulating Canadian highway truck traffic. In addition to yielding valuable S-N (stress plotted vs. the number of cycles until fatigue failure) data, initial test results provide evidence of the benefits of redundancy in the structural system and the value of beam tests over push-out tests. Calculating connector stresses in a composite beam is made complicated by interfacial slip and neutral axis migration. The end goal of this research is to provide Canadian bridge designers and erectors with improved design and construction recommendations in order to improve the efficiency and economy of this structural system for rapid bridge replacement projects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".