Behavior of GFRP-RC Interior Slab-Column Connections with Shear Studs and High-Moment Transfer
Bibliographic record
Abstract
Six full-scale reinforced-concrete (RC) interior slab-column connections of glass fiber–reinforced polymer (GFRP) were constructed and tested to failure. The specimen consisted of a square slab with a 2,800-mm side length and a 200-mm thickness in addition to a 300-mm-square column stub extended for 1,000 mm above and below the slab. The test specimens were subjected to vertical shear forces and unbalanced moments. The test variables included the moment-to-shear ratio, GFRP double-headed shear studs ratio, and the type of GFRP bar surface texture (ribbed or sand-coated). The test results revealed that increasing the moment-to-shear ratio reduced the vertical shear capacity and increased the deflections and the strains at failure. Moreover, the presence of the GFRP shear studs enhanced the slab capacity but was not able to change the punching shear mode of failure. Furthermore, the used two types of GFRP bars showed comparable behavior. The results were compared with the predictions of the available fiber-reinforced polymer (FRP) design provisions such as those from Canada, the United States, and Japan. Finally, a new method is proposed to predict the punching shear capacity for the slabs with FRP shear studs.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".