Numerical Investigation of Optimized Chamfered Concrete-Filled Steel Tubular Columns under Axial and Lateral Loads
Bibliographic record
Abstract
The study presents a new iterative corner-chamfering strategy to optimize tapered Concrete-Filled Steel Tubular (CFST) columns under axial and lateral loads.Finite element simulations examine square, octagonal, and chamfer-optimized sections at taper angles of 0°, 2°, and 4°.Through systematic iteration, a 14.65% chamfer level is identified that exceeds the unchamfered square column's axial strength by approximately 1.6%, while consuming less material.Compared to the octagonal column, this chamfer-optimized geometry provides a 20% improvement in axial capacity and up to 16% higher lateral capacity.As the taper angle increases, both axial and lateral strengths consistently rise, with the chamfer-optimized column demonstrating a 31% enhancement in axial capacity from 0° to 4°, alongside a near 100% escalation in lateral load capacity.Nonetheless, these gains accompany a modest reduction in ductility, attributed to the stiffening effect of taper.Overall, this research underscores that precisely controlled corner-chamfering, in tandem with tapered geometry, effectively augments CFST columns' load-bearing capacity, achieving a balance between strength and ductility.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".