Flexural Performance of Beams Strengthened with FRP Laminates and Alternative U-Wrap Anchors
Bibliographic record
Abstract
Premature debonding is identified as the main failure mode in reinforced concrete (RC) beams strengthened with externally bonded Fiber-Reinforced Polymer (FRP) laminates. This issue leads to the underutilization of FRP materials and needs to be addressed. Research has shown that end anchorage systems can effectively delay/mitigate delamination failures and enhance the performance of strengthened beams. FRP U-wraps are an effective means to prevent debonding failure; however, as open-form anchors, U-wraps cannot always guarantee complete resistance to debonding failures. This study proposes an alternative U-wrapping technique where the ends of the U-wraps are flared and inserted into the concrete substrate. The feasibility and effectiveness of this technique were studied by comparing it with conventional U-wraps. The experimental phase involved testing seven RC beams, each measuring 1.96×0.15×0.3 meters, under four-point bending. The results showed that the anchorage technique improved beam performance in terms of load-deflection behavior, failure modes, ductility, and FRP strain. Additionally, finite element simulations were conducted using Abaqus software to assess the effectiveness of the alternative U-wrap scheme. These models incorporated various nonlinear material constitutive laws, including cohesive zone modeling to replicate debonding failures at the CFRP-concrete interface. The numerical predictions were found to be in good agreement with the experimental test data. Doi: 10.28991/CEJ-2024-010-08-01 Full Text: PDF
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".