Fibre reinforced polymer composite bars for the structural concrete slabs of a Public Works and Government Services Canada parking garage
Bibliographic record
Abstract
Public Works and Government Services Canada (PWGSC) is currently undertaking the reconstruction of the interior structural slabs of the Laurier-Taché parking garage (Hull, Quebec). An agreement between PWGSC and the Université de Sherbrooke was reached to use fibre reinforced polymer (FRP) reinforcement technology in some demonstration areas of the Laurier–Taché parking garage. Based on this agreement, three different designs using carbon and glass FRP bars were carried out in collaboration with the project consultant. These designs were made according to CAN/CSA-S806-02, Design and Construction of Building Components with Fibre-Reinforced-Polymers. To verify the design, it was agreed to conduct laboratory testing on full-scale slab prototypes of the proposed designs. This paper presents the results of the experimental tests where six full-sized one-way slabs were constructed and tested. The slabs were 3100 mm long × 1000 mm wide × 150 mm deep and were tested under four-point bending. The test results along with a comparison to the predictions of CAN/CSA-S806-02 Code and ACI 440.1R-03 design guidelines are presented. Recommendations for design of FRP-reinforced concrete slabs are also given.Key words: concrete slabs, parking garages, FRP bars, flexural behaviour, cracking, deflection.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.007 | 0.001 |
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".