Fiber-Optic Sensors Monitor FRP-Reinforced Bridge
Bibliographic record
Abstract
Rebar corrosion in reinforced concrete bridge decks is a major problem. Most technical solutions forthe problem attempt to slow the corrosion rate or prevent corrosion, but an alternate approach isreplacing the steel with a more durable material such as fiber reinforced polymer (FRP).The University of Sherbrooke, Quebec, Canada, recently conducted a field project in which FRP rebar and grids were used to reconstruct portions of a concrete deck slab that had severely deteriorated when the reinforcing steel corroded. The project included analysis and design of the bridge structure, construction of the concrete deck slab, and field performance monitoring of the completed construction using fiber optic sensors (FOSs). The integration of FOSs to monitor long-term performance of RC structures is a fairly recent development that deserves more attention from practicing engineers and field personnel.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".