Performance of Corrosion-Aged Reinforced Concrete (RC) Beams Rehabilitated with Fabric-Reinforced Cementitious Matrix (FRCM)
Bibliographic record
Abstract
This paper reports on the feasibility of using fabric-reinforced cementitious matrix (FRCM) systems to rehabilitate corrosion-damaged reinforced concrete (RC) beams. Seven large-scale RC beams were constructed and tested to failure under four-point load configuration. Six beams were subjected to an accelerated corrosion process for 70 days to obtain an estimated mass loss of 10% in the tensile steel reinforcing bars. One virgin beam and one corroded unrepaired beam were used as benchmarks for comparison purpose. The other five corroded beams were repaired before applying the FRCM system. The test parameters included the number of fabric plies (1, 2, and 4) and the strengthening schemes (endanchored bottom flexural strips and fully U-wrapped flexural strips). Test results showed that corrosion insignificantly reduced the yield and the ultimate strength of the specimen. However, the corroded specimen failed to meet the provisions of the ACI 318 code for crack width criteria. The use of FRCM increased the ultimate capacity of corroded beams between 6% and 46% and their yield strength up to 20% in comparison with those of the control virgin beam. The specimens repaired with U-wrapped FRCM strips showed higher capacity and higher ductility than those repaired with the end-anchored bottom strips having similar number of layers. A higher gain in the flexural capacity and a lower ductility index were reported for specimens with higher amount of FRCM layers.
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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) | 0.001 | 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".