Vehicle Crash Testing on a GFRP-Reinforced PL-3 Concrete Bridge Barrier
Bibliographic record
Abstract
Corrosion of steel reinforcement due to environmental effects is a major cause of deterioration problems in bridge barriers. Glass fibre reinforced polymer (GFRP) not only addresses this durability problem but also provides exceptionally high tensile strength and Young's modulus. A recent design work conducted at Ryerson University on PL-3 bridge barrier proposed the use of 16 mm and 12 mm diameter GFRP bars as vertical reinforcement in the barrier front and back faces, respectively, with 12 mm diameter GFRP bars as horizontal reinforcement in the barrier wall, all at 300 mm spacing. The connection between the deck slab and the barrier wall utilized the GFRP headed end bars for proper anchorage. This paper summarizes the procedure and the results of a recent vehicle crash test conducted on the developed barrier. The crash test was performed in accordance with MASH Test Level 5 (TL-5), which involves the 36000V tractor trailer impacting the barrier at a nominal speed and angle of 80 km/h and 15 degrees, respectively. Crash test results showed that the barrier contained and redirected the vehicle. The vehicle did not penetrate, underride or override the parapet. No detached elements, fragments, or other debris from the barrier were present to penetrate or show potential for penetrating the occupant compartment, or to present undue hazard to others in the area. No occupant compartment deformation occurred. The test vehicle remained upright during and after the collision event. For the covering abstract of this conference see record contro number 201111RT334E.
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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 | 0.000 |
| 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 | 0.001 | 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".