Two-Way Shear Behavior of GFRP-Reinforced Concrete Box Culverts with 70 MPa Concrete under CL-625 Truck Loading
Bibliographic record
Abstract
Although high-strength concrete is becoming more common in bridge and highway structures, its performance in glass fiber–reinforced polymer (GFRP)-reinforced box culverts under two-way shear remains unexplored. This study aimed to fill that gap and provide insights into their structural behavior. Four full-scale GFRP-reinforced concrete box culverts cast using concrete with a compressive strength (fc′) of 70 MPa were tested under the CL-625 truck wheel load, in compliance with the Canadian Highway Bridge Design Code. The experimental program examined key parameters, including longitudinal GFRP-reinforcement ratio (ρf), top-slab thickness (h), and concrete compressive strength (fc′). The use of concrete with grade of 70 MPa enhanced the performance, reducing deflection by 37% and increasing two-way shear strength by 21% compared to specimens with 40 MPa reported in a previous study. Comparisons revealed, however, that increasing the GFRP-reinforcement ratio (ρf) or slab thickness (h) was more effective for specimens with a concrete compressive strength (fc′) of 40 MPa than specimens with a concrete compressive strength (fc′) of 70 MPa. Experimental two-way shear strengths were assessed and compared to predictions from existing provisions and equations proposed in the literature. The findings provide critical insights into the effectiveness of using concrete with high compressive strength in enhancing the structural performance of GFRP-reinforced concrete box culverts, which are essential for supporting highways and serve as critical elements within bridge systems. This research contributes to advancing design practices for more efficient, durable, and reliable bridge infrastructure elements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".