Durability assessment of GFRP bars in concrete exposed to field environment based on interlaminar shear strength
Bibliographic record
Abstract
The interlaminar shear strength (ILSS) can be an indicator of the deterioration of glass fibre-reinforced polymer (GFRP) bars. This property is normally evaluated by using a sample with a length equal to four to seven times the bar diameter, which can be extracted from in-service structures. First, this study conducted an intensive review to establish the relationship between tensile strength (TS) and ILSS retentions of vinyl-ester based GFRP bars, including the effect of sustained stress. TS and ILSS retentions show 0.18–0.92 and 0.30–0.92, respectively, when fibre, resin, and fibre-resin interface damage is observed near the exposed surface. This relationship demonstrates the applicability of assessing the durability of GFRP bars based on ILSS. Available ILSS retentions range from 0.71 to 0.93 on the field durability of GFRP bars extracted from 11- to 20-year-old bridge barriers, bridge decks, a dry-dock, and exposed bars. The reported field durability is compared with a prediction model established from laboratory immersion tests for GFRP bars embedded in concrete. It is shown that predictions based on the immersion in tap water or saline solution in the laboratory can explain the reduction in ILSS of GFRP bars extracted from actual structures while a prediction based on the immersion in alkaline solution is conservative.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".