Fatigue strength of fibre-reinforced-polymer-repaired beams subjected to mild corrosion
Bibliographic record
Abstract
Infrastructure corrosion is an expensive problem worldwide. In the case of reinforced concrete (RC) structures, corrosion reduces the steel cross sectional area and thus decreases the capacity of the corroded RC members. The expansion of the corroded steel also induces tensile stresses in the concrete causing the concrete cover to crack and spall, thus reducing the bond capacity between concrete and steel. This paper reports on a research program conducted at the University of Waterloo that studied the effect of corrosion on flexural and bond fatigue strength. The effect of the addition of fibre-reinforced-polymer (FRP) sheets on the fatigue life of corroded RC beams was also assessed. Eighteen beams (152 mm × 254 mm × 2000 mm) were tested in two groups, with each group consisting of three sets of tests. Group F was designed to study the fatigue flexural behaviour; the repaired beams in this group were strengthened with a flexural FRP sheet along their tension side and confined by intermittent U-shaped FRP sheets along their length. Group B was designed to study the fatigue bond behaviour; hence, the repaired beams in this group were confined with U-shaped FRP sheets in the anchorage zone. The variables in each group were the percentage of corrosion (0% and 5% theoretical mass loss), the load range, and the use or omission of a FRP repair method. Results showed that a mild level of corrosion (5% theoretical mass loss) caused on average 10% and 20% reductions in flexural and bond fatigue strength, respectively. Strengthening the corroded beams with FRP sheets enhanced the fatigue behaviour of the beams. In both groups, the fatigue strength was on average 15% higher than that of the corroded unrepaired beams.Key words:corrosion, fibre-reinforced-polymer (FRP) sheets, fatigue strength, steel–concrete bond, flexural performance, durability.
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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) | 0.000 | 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".