Review of Current Design Guidelines for Circular FRP-Wrapped Plain Concrete Cylinders
Bibliographic record
Abstract
With the widespread use of fiber-reinforced polymer (FRP) composites in the construction sector as a strengthening technique, the development of design guidelines for the field application of externally bonded FRP systems is ongoing in Europe, Japan, Canada, and the United States. The main goal of this study is to evaluate the current seven international design guidelines and four other design models for the prediction of confined concrete compressive strength of FRP-wrapped plain concrete cylinders against the experimental results of a large database of 812 specimens reported in the literature. The results clearly show that the reliability of predictions of confined concrete compressive strength of FRP-wrapped plain concrete cylinders by the design guidelines significantly varies for different ranges of unconfined concrete compressive strength. For example, the gain in confined concrete compressive strength of FRP-wrapped low- and medium-strength concrete cylinders is larger than that of high- and ultrahigh-strength concrete cylinders. Furthermore, a simplified model for the prediction of design/characteristic–confined concrete compressive strength is developed based on the design-assisted-by-testing approach. The developed simplified model accounts for the variation in confinement effectiveness for different ranges of unconfined concrete strengths.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".