Axial Load Behavior of Ultrahigh Strength Concrete-Filled Steel Tube Columns of Various Geometric and Reinforcement Configurations
Bibliographic record
Abstract
This paper presents the behavior of concrete-filled steel tube (CFST) columns infilled with fiber-reinforced self-consolidating ultrahigh strength concrete (UHSC) subjected to axial concentric monotonic loading to failure. UHSC is expected to improve ease of fabrication, strength, and ductility of CFST columns. Seventeen columns having varying geometric properties such as tube wall thickness, cross-sectional shape (circular, rectangular, and square), and slenderness were constructed and tested by applying load through both steel tube and concrete core. Circular columns were further distinguished by the presence or absence of main and hoop steel reinforcing bars in the core concrete. Axial load-displacement response, axial/transverse strain development, and failure modes were recorded during the loading history to analyze the performance. Experimental confined concrete strength and axial strength of UHSC-filled CFST columns were compared with those obtained from three suggested analytical models and three code-based design procedures including Eurocode 4, Canadian CAN/CSA S16, and American AISC. Analytical models were found to over-predict the confined concrete strength and the axial strength of CFST columns. Canadian and American codes were found to be most applicable for predicting axial strength of UHSC-filled CFST columns while remaining conservative.
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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".