Experimental Assessment of Fatigue and Ultimate Strength of Stud Clusters in UHPC-filled Shear Buckets for Full-depth, Precast, Concrete Bridge Deck Panel- Steel Girder System
Bibliographic record
Abstract
Accelerated Bridge Construction (ABC) is becoming an innovative construction solution to minimize construction cost and delivery time while increasing durability and improving safety. The common approach in ABC involves installing full-depth precast concrete deck panels on top of steel girders such that the shear pockets in the panels are aligned with a cluster of studs welded to the top flanges of the girders. This thesis presents a study on fatigue and static behavior of headed shear studs in composite girders where ultra-high-performance concrete (UHPC) was used as the connection grout in the shear pockets. The experimental program consisted of both static and fatigue testing on composite sections. The first phase of this research involved static and fatigue push-out tests on six specimens in which studs were grouped in different arrangements and spacings. The second phase of this research involved fatigue tests, followed by static tests to collapse on 5 composite beams. Three shear pocket spacings were considered in this study, namely: 600 mm, 1200 mm, and 1500 mm, along with a control cast-in-place specimen that was constructed using evenly distributed studs. Results were analyzed in comparison with the CSAS6:19 code provisions. Then, conclusions for the fatigue and ultimate strength of the clustered studs in UHPC-filled shear pockets were drawn.
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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 | 0.000 |
| 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) | 0.001 | 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".