CFRP-Strengthened and Corroded RC Beams under Monotonic and Fatigue Loads
Bibliographic record
Abstract
An experimental program has been carried out to investigate the structural behavior of RC beams strengthened by carbon-fiber–reinforced polymer (CFRP) sheets and exposed to a corrosive environment. A total of eight specimens (120 × 175 × 2,000 mm) were tested. Six specimens were CFRP strengthened and corroded, one specimen was unstrengthened and corroded, and one specimen was neither strengthened nor corroded. Two different strengthening schemes were applied: (1) wrapping the specimen with CFRP sheets; and (2) both specimen wrapping and flexural strengthening. Three specimens were tested under monotonic loading and five specimens were tested in fatigue. The results showed that the use of CFRP sheets for strengthening RC beams that are experiencing steel reinforcement corrosion is an efficient technique that can maintain the structural integrity and enhance the structural behavior of such beams. The ultimate monotonic strength of the CFRP strengthened-corroded specimens increased to a level between 37 and 87% above the predicted strength of a similar unstrengthened-uncorroded (virgin) specimen. The fatigue life of the CFRP strengthened-corroded specimens was increased within a range of 2.5–6.0 times that of a similar unstrengthened-corroded specimen but was lower than that of the uncorroded (virgin) specimen.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".