Experimental study of static and fatigue push-out test on headed stud shear connectors in UHPC composite steel beams
Bibliographic record
Abstract
Steel-concrete composite girder bridges utilize shear connectors to connect concrete deck slabs and steel girders . In current practice, the headed shear stud connector is the most used due to its reliability and ease of installation. Several studies are available on the static and fatigue behavior of welded-headed shear studs embedded in normal-strength concrete. However, relatively little is known about the static and fatigue behavior of headed shear connectors in composite beams when shear studs are embedded in ultra-high-performance concrete (UHPC). This study reports a series of pushout results carried out on headed shear connectors embedded in UHPC at pre-fatigue and post-fatigue stages. Six pushout specimens were first tested under static load to collapse. The precast normal-strength concrete slabs in the pushout specimens were reinforced with glass fiber-reinforced polymer (GFRP) bars to promote sustainable construction. This practice, commonly used in Canada, aims to eliminate the corrosion of steel bars caused by de-icing salts used during winter. The results from these tests were used to determine the applied fatigue stress range of another six identical pushout specimens, which were subjected to constant amplitude fatigue loading over 2 million cycles. Results show that the fatigue cycles applied to the specimens prior to testing them to collapse did not alter the failure mode or the crack pattern of the tested specimens . Furthermore, the studied pushout specimens considered 6 different shapes of shear pockets in which the arrangement and spacing of studs were varied. It was found that the studs in a square pocket form yielded a shear capacity of 13.9 % and 16.7 % greater than those for similar studs arranged in a single row-oriented longitudinally and transversally, respectively. The accuracy of the various design formulas specified in design codes in estimating the shear resistance of the tested specimens, as well as empirical formulas proposed to develop load-slip curves of tested specimens, is studied. It was found that the European and Japanese codes significantly underestimated the stud shear capacity, whereas the Canadian code provides a more accurate estimation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".