Tests and Design Provisions for Reinforced-Concrete Beams Strengthened in Shear Using FRP Sheets and Strips
Bibliographic record
Abstract
Numerous investigations of RC beams strengthened in shear with externally-bonded (EB) fibre-reinforced polymer (FRP) sheets, plates and strips have been successfully conducted in recent years. These valuable studies have highlighted a number of influencing parameters that are not captured by the design guidelines. The objective of this study was: (1) to highlight experimentally and analytically the influential parameters on the shear contribution of FRP to RC beams strengthened in shear using EB FRP sheets and strips; and (2) to develop a set of transparent, coherent, and evolutionary design equations to calculate the shear resistance of RC beams strengthened in shear. In the experimental part of this study, 12 tests were performed on 4,520-mm-long T-beams. The specimens were strengthened in shear using carbon FRP (CFRP) strips and sheets. The test variables were: (1) the presence or absence of internal transverse-steel reinforcement; (2) use of FRP sheets versus FRP strips; and (3) the axial rigidity of the EB FRP reinforcement. In the analytical part of this study, new design equations were proposed to consider the effect of transverse-steel in addition to other influential parameters on the shear contribution of FRP. The accuracy of the proposed equations has been verified in this study by predicting the FRP shear contribution of experimentally tested RC beams.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".