Shear rehabilitation of G-girder bridges in Alberta using fibre reinforced polymer sheets
Bibliographic record
Abstract
Many bridges were built in Alberta after World War II with type G-girder precast concrete elements. Today, there are approximately 1500 G-girder bridges still in service all over the province. These bridges are typical short span (approximately 6 m long), simply supported, and without shear keys between girders. Structural deficiency of the G-girders, especially in shear, plus the economic constraints of the government demand that an economical and efficient method for rehabilitation of these bridges be developed. A research program at the University of Alberta, in collaboration with Alberta Transportation and Utilities and ISIS Canada, has been established to study the feasibility of using fibre reinforced polymers (FRP) to rehabilitate concrete bridge girders deficient in shear. This paper will address the structural deficiency of the G-girders and present eight full-scale test results from four G-girders removed from existing bridges. Carbon and glass FRP sheets and two repair schemes were used in the rehabilitation. Three commonly used shear strength evaluation methods, strut-and-tie model, modified compression field theory, and grid analysis, are investigated. The loads predicted by these three methods are in good agreement with the experimental results. The shear contribution of the FRP sheets at any angle can be accurately accounted for in the analysis. All three methods are found to be consistent.Key words: analysis, beams, bridges, composite materials, design, fibre reinforced polymers, rehabilitation, reinforced concrete, shear strengthening.
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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 | 0.001 |
| 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".