Behaviour of reinforced concrete beams strengthened with carbon fibre reinforced polymer laminates subjected to corrosion damage
Bibliographic record
Abstract
The viability of carbon fibre reinforced polymer (CFRP) laminates for the strengthening of corrosion damaged reinforced concrete bridge girders is addressed in this paper. Ten reinforced concrete beams (100 × 150 × 1200 mm) with variable chloride levels (0-3%) were constructed. Six beams were strengthened by externally epoxy bonding CFRP laminates to the concrete surface. The tensile reinforcements of three unstrengthened and four strengthened specimens were subjected to accelerated corrosion by means of impressed current to 5, 10, and 15% mass loss. Strain gauges were placed on the CFRP laminates to monitor and quantify tensile strains induced by the corrosion process. Following the corrosion phase, the specimens were tested in flexure in a four-point bending regime. Test results revealed that CFRP laminates successfully confined the corrosion cracking, and the total expansion of the laminate exhibited an exponential increase throughout the corrosion process. All the strengthened beams exhibited increased stiffness over the unstrengthened specimens and marked increases in the yield and ultimate strength. The CFRP strengthening scheme was able to restore the capacity of corrosion damaged concrete beams up to 15% mass loss.Key words: CFRP laminates, corrosion, confinement, expansion, load tests, strengthening, bond strength, reinforced concrete.
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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 | 0.000 | 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) | 0.001 | 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".