Application of SRP Composite Sheets for Retrofitting Reinforced Concrete Beams: Cracking and Tension Stiffening
Bibliographic record
Abstract
This paper presents the contribution of steel-reinforced polymer (SRP) composites to the serviceability of reinforced concrete beams when retrofitted, with particular emphasis on cracking behavior and tension stiffening. SRP composite sheets, consisting of high-carbon steel unidirectional fabrics embedded in epoxy resin, provide high tensile strength and modulus at a reasonable cost. Six reinforced concrete beams, five of which are retrofitted using various widths of SRP sheets with or without end anchorage, are tested in three-point bending to examine their flexural performance, including crack width and depth progression, crack patterns, flexural rigidity, and tension stiffening. A 3D non-linear finite element analysis is conducted and compared to the code provisions and experimental findings. The trend of crack width progression of the SRP-retrofitted beams includes an almost linear response with respect to the SRP strain development. Clear differences in crack spacing are observed between the mid-span and shear-span regions of the test beams. The end anchorage significantly improves flexural rigidity and narrows the crack spacing of SRP-retrofitted beams. A characteristic area, including the tension stiffening factor, is proposed to evaluate the contribution of SRP composites to the flexural rigidity of SRP-retrofitted beams.
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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) | 0.000 | 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".