Bending and Buckling Behavior of Hollow-Core FRP–Concrete–Steel Columns
Bibliographic record
Abstract
This article presents a numerical study on the behavior of hollow-core fiber-reinforced polymer–concrete–steel (HC-FCS) columns under combined axial compression and lateral loadings. The investigated HC-FCS columns consisted of an outer circular fiber-reinforced polymer (FRP) tube, an inner square steel tube, and a concrete wall between them. The HC-FCS column has several advantages over RC columns. The tubes act a stay-in-place formwork, providing continuous confinement and reinforcement. The concrete shell prevents the outward buckling of the steel tube, which improves the column strength. Three-dimensional (3D) numerical models were developed and validated against experimental results. The models subsequently were used to conduct a parametric finite-element (FE) study investigating the effects of the concrete wall thickness, steel tube width-to-thickness (B/ts) ratio, confinement ratio, concrete strength, applied axial load level, and buckling instabilities on the behavior of the HC-FCS columns, with a particular emphasis on local buckling of the inner tube. This study revealed that the behavior of HC-FCS columns is complicated due to the interaction of the stiffness of the three different materials: concrete, steel, and FRP. In general, in the HC-FCS columns with square steel tubes, failure was triggered by local buckling of the steel tube followed by FRP rupture. The presence of the concrete wall restrained by the outer FRP and inner steel tubes significantly affected the steel tube buckling. Expressions were also developed to predict the local buckling stresses and strains of the square steel tube.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".