Bond between single and bundled high-modulus ribbed GFRP bars with short embedment lengths and concrete
Bibliographic record
Abstract
The bond between glass fiber-reinforced polymer (GFRP) rebar and concrete is one of the most important parameters in the design of GFRP-reinforced structures. This study investigates the bond behavior of single and bundled high-modulus ribbed GFRP rebars with short embedment lengths in concrete. To achieve this, a total of 48 pullout specimens were constructed and tested. The effect of various parameters, including GFRP rebar embedded length, the concrete block dimensions, GFRP surface characteristics, presence of transverse reinforcement, and bundling of rebars on the bond behavior of high-modulus ribbed GFRP rebar was studied. The experimental results indicated that the failure mode changed from pullout to splitting failure as the embedment length increased. The presence of transverse reinforcement, in many cases, changed brittle splitting failure to partial splitting failure followed by pullout failure. The variation in rebar surface characteristics resulted in differences in the bond-slip behavior of GFRP rebar in concrete. The experimental findings illustrated that rebar stress at failure for specimens with bundled GFRP was generally higher than that of corresponding individual bar with approximately same cross-sectional area. This observation suggests that the equivalent area method may serve as a conservative approach for evaluating the embedment length of bundled ribbed GFRP rebars. Furthermore, the adhesion between ribbed GFRP rebars and concrete was quantified for various bar sizes. Finally, the experimental results were employed to refine and calibrate existing bond-slip models of ribbed GFRP rebar to concrete.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".