Development of cost-effective PL-3 concrete bridge barrier reinforced with sand-coated glass fibre reinforced polymer (GFRP) bars: static load tests
Bibliographic record
Abstract
One of the main factors concerning durability and service life of steel-reinforced bridges is corrosion of steel bars especially when exposed to a harsh environment. The use of glass fibre reinforcing polymer (GFRP) bars as non-corrosive material has emerged as an innovative solution to corrosion related problems, reduce the maintenance cost, and increase the service life of bridge structures. A recent cost-effective design of PL-3 bridge barrier was developed at Ryerson University incorporating high-modulus GFRP bars with headed ends. This paper presents results of full-scale static tests to collapse performed on the developed PL-3 bridge barrier at interior and exterior locations to investigate the ultimate load carrying capacity to be compared with Canadian Highway Bridge Design Code (CHBDC). The experimental ultimate load carrying capacity of the barriers was observed to be far greater than CHBDC factored design transverse load. The failure pattern was initiated by a trapezoidal crack pattern at the front face of the barrier, followed by punching shear failure at the transverse load location. Based on the punching shear failure developed in the barrier wall and comparison with available punching shear equations in the literature, an empirical punching shear equation is proposed to determine the transverse load carrying capacity of PL-3 bridge barrier walls reinforced with GFRP bars.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".