Interface Shear Capacity of Basalt FRP-Reinforced Composite Precast Concrete Girders Supporting Cast-in-Place Bridge-Deck Slabs
Bibliographic record
Abstract
Using composite precast concrete bridge girders supporting cast-in-place bridge-deck slabs is a cost-efficient method because it merges precast and cast-in-place elements while maintaining the monolithic construction’s integrity and continuity. In terms of horizontal shear transfer in composite girders, there is a lack of experimental data on the performance of full-scale fiber-reinforced polymer (FRP)-reinforced composite girders. This study explored an innovative and sustainable approach using noncorroding basalt fiber–reinforced polymer (BFRP) as shear transfer reinforcement in precast concrete bridge girders supporting cast-in-place concrete bridge-deck slabs. Five full-scale composite reinforced concrete T-beams measuring 4,200 mm in length, 420 mm in depth, and 250 mm in width were designed, cast, and tested until failure. The main experimental variables evaluated were the interface shear reinforcement type (BFRP versus steel stirrups), the interface shear reinforcement ratio (0.32% versus 0.48%), and the interface shear reinforcement shape (stirrups versus bent bars). The test results were analyzed in terms of ultimate horizontal shear stress, deflection, slippage, and shear reinforcement strain. The experimental results indicated that the BFRP shear reinforcement provided reasonable shear transfer capacities compared to steel when provided across rough concrete interfaces. In addition, the existing equations in North American bridge design guidelines yielded overly cautious predictions of the BFRP bars’ interface shear strength. The study conclusively demonstrates the viability and potential of using BFRP bars as shear connectors in composite precast concrete girders supporting cast-in-place bridge-deck slab applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".