Field and laboratory performance of bridge columns repaired with wrapped glass-fibre-reinforced-polymer sheets
Bibliographic record
Abstract
Several bridge columns, in which concrete was delaminated as a result of steel corrosion, were repaired in the mid 1990s. Different types of grout, including one based on expansive cement, were used to rebuild the damaged columns to their original shape; the columns were then wrapped with glass-fibre-reinforced polymers (GFRPs). The associated lab study indicated that the observed damage caused a reduction of about 20% in the axial-load-carrying capacity of the columns and much larger reductions in ductility and energy-dissipating capacity. The experimental results also showed that the strength and ductility of the columns could be recovered by repairing them with GFRP. Long-term monitoring of three columns repaired in the field using GFRP has indicated their excellent performance. No deterioration has been observed in the fibre-reinforced polymer or in the columns in more than 10 years. Monitoring has also shown a reduction in the rate and associated risk of corrosion over time; thus, this is a more durable retrofitting technique than traditional ones, such as steel jacketing.Key words: concrete, columns, corrosion, cyclic loading, ductility, expansive cement, glass-fibre-reinforced polymers, monitoring, repair, strength.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".