Bond of FRP bars in air-entrained concrete: Experimental and statistical study
Bibliographic record
Abstract
The combined use of Fibre Reinforced Polymer (FRP) and Air-Entrained Concrete (AEC) can be an alternative to traditional steel-reinforced concrete as this system is less affected by the corrosion of the reinforcement and by the freeze-thaw cycles induced concrete degradation. However, the viability of this system hinges on the bond performance of the reinforcing bars. A total of 236 pull-out specimens were prepared and tested to study the effect of air-entraining admixtures (AEA) on the bond behaviour of FRP bars to concrete with varying compressive strengths. Failure modes and bond stress-slip curves were reported and discussed. The bond energy, calculated as the area under the bond stress-slip diagram, was also analyzed. The experimental peak bond stresses (bond strength) were compared to the theoretical ones characterized by the formula proposed for steel bars by the Model Code 2010. In addition, the statistical significance of the effect of AEA on bond characteristics was determined, yielding a reduction factor to account for the effect of AEA on bond strength. The test results show that the bond strength of FRP bars in AEC was statistically significantly lower than in normal concrete. However, the decrease is sufficiently small that could be accounted for, during the design stage, by merely increasing the reinforcement development length.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".