Development of sustainable concrete bridge deck slab systems using corrosion-resistant GRFP bars
Bibliographic record
Abstract
This research investigates the use of glass fiber reinforced polymer (GFRP) bars to reinforce the bridge deck slabs as well as jointed precast bridge deck slab in prefabricated bulb-tee pre-tensioned bridge girders. The experimental program included two phases. In phase (I), six precast slab joint details between flanges of precast bulb-tee girders were developed incorporating GFRP bars with straight ends, L-shaped ends and headed ends, embedded in a closure strip filled with non-shrink cement grout or ultra-high-performance concrete (UHPC). A total of 11 actual-size specimens representing the one-way slab system with the proposed joint details, in addition to 5 cast-in-place control specimens, were built and tested to failure to examine the structural adequacy of the proposed joint details. Based on the results from Phase (I), the best joint was selected for further tests in Phase (II) to examine its fatigue life and ultimate load carrying capacity under vehicular wheel loading. A total of 8 actual-size, GFRP-reinforced, 3500 X 2500 X 200 mm concrete deck slabs were designed for this purpose according to CHBDC specifications. Ultimate strength, fatigue behavior and fatigue life of the GFRP-reinforced deck slabs were investigated using different schemes of fatigue loading, namely: accelerated variable amplitude fatigue loading and constant amplitude fatigue loading. Overall, the experimental results indicated that GFRP-reinforced deck slabs showed high fatigue performance. A new prediction model for fatigue life of the GRFP-reinforced deck slabs was developed. The failure mode of the tested composite slabs was punching shear. Correlation between the experimental findings and the prediction models for punching shear resistance available in the literature showed that the prediction models by CSA S806-12 (2012) and El-Gamal et al. (2005) can accurately predict the punching shear capacity of the cast-in-place and precast jointed bridge deck slabs reinforced with GFRP bars. In addition, the average observed mid-depth punching shear perimeter for the cast-in-place deck slabs and the precast jointed deck slabs were measured to be 1.25 d and 1.33d away from the sides of the loaded area, respectively, which are more than twice the corresponding distance specified in ACI 440.1R-06 and CSA S806-12 for calculating the critical punching shear perimeter.
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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 | 0.000 | 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".