Performance Enhancement of Steel Columns Using Concrete-Filled Composite Jackets
Bibliographic record
Abstract
This paper studies the cross-sectional behavior of steel columns strengthened with fiber-reinforced polymers (FRPs). The composite column is constructed by wrapping the steel I-section column with epoxy-saturated glass- and carbon-FRPs (GFRP and CFRP) sheets in the transverse direction and subsequently filling the voids between the FRP and the steel with concrete. Experimental tests were performed on stub columns under axial compression including one to three CFRP wraps. A corner treatment technique, to avoid stress concentration at the corners and to improve confinement efficiency, was also investigated. A simplified analytical model was developed to predict the axial behavior of the composite columns. Experimental results showed significant enhancement in the behavior of the composite columns primarily attributable to the confinement mechanism imposed by the FRP jacket and concrete. Increasing the corner radius resulted in higher compressive strength of the confined concrete and ultimate axial strain of the composite columns. Good agreement between the analytically developed axial load-displacement relationships and the test data indicates that the model can closely simulate the cross-sectional behavior of the composite 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".