Behavior of Large-Scale Concrete Columns Wrapped with CFRP and SFRP Sheets
Bibliographic record
Abstract
Circumferential wrapping of fiber-reinforced polymer (FRP) sheets is one of the most common applications for repair and rehabilitation of large-scale columns. Common types of fibers used for wrapping are carbon FRP (CFRP), glass FRP (GFRP), and aramid FRP (AFRP). Recently, steel FRP (SFRP) has been introduced as a new class of composites for strengthening applications. Up to now, there has been no experimental data available on the behavior of large-scale columns wrapped with SFRP sheets. Thus, in this paper, the behavior of nonreinforced and reinforced large-scale columns (300×1,200 mm) wrapped with CFRP and SFRP sheets is examined and compared with that of unwrapped columns. The experimental results include stress-strain behavior, ultimate stress, ultimate strain, dilation, and ductility of large-scale columns. This study presents the first ever insight into the strain variation of large-scale circular columns wrapped with CFRP and SFRP sheets using the digital image correlation technique (DICT). This technique is a photogrammetric technique that allows capturing strains from the surface of FRP-confined concrete. Results from DICT were used to analyze the strain efficiency of the SFRP sheets. Results indicate that the overall performance of the SFRP-wrapped concrete columns is superior to that of the CFRP-wrapped concrete columns.
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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".