Flexural Performance of Steel Girders Retrofitted Using CFRP Materials
Bibliographic record
Abstract
There are many existing deteriorated steel bridges that need to be retrofitted. This paper investigates the effectiveness of using carbon fiber-reinforced (CFRP) composite systems in retrofitting deteriorated steel beams. A total of 13 medium-scale steel I-beams with a span of 1.6 m was tested in a four-point bending setup. The tested beams were divided into four groups according to their studied parameter. Group 1 consists of four unretrofitted beams with different percentages of artificial deterioration to simulate corrosion in the bottom flange with the aim to investigate their behavior and to determine the residual flexural capacity. The other three groups have deteriorated steel beams that were retrofitted with different CFRP systems with the aim to evaluate the effectiveness of the proposed retrofit schemes. Four deteriorated beams were retrofitted with CFRP sheets bonded to the tension flange and were tested in Group 2. Group 3 consists of two deteriorated steel beams that were retrofitted with CFRP plates externally bonded to the bottom flange of the tested beams. Group 4 consists of three beams retrofitted using an unbonded CFRP sheet attached to two ductile anchorage systems at the beams’ ends. The study shows that steel beams retrofitted with external bonded CFRP systems experienced limited ductility upon the failure of the CFRP either by debonding or rupture at higher load capacities than that of the unretrofitted beams. The proposed anchorage system could increase the strength of the deteriorated beam, behave in a ductile manner, and eliminate the early peel off of the CFRP sheet.
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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".