Comparison of the predictability of the ultimate axial strength of elliptical CFST columns using existing square and circular section-based code formulae
Bibliographic record
Abstract
The elliptical hollow section has been recently included in the family of the structural steel hollow sections. This type of steel section is also used in the production of concrete-filled steel tubular (CFST) members. For the elliptical CFST compression members, there is no specific design formulation in the current provisions, except the code called “Technical code for concrete-filled tubular structures” prepared by the Ministry of Housing and Urban-Rural Development of the People’s Republic of China. However, the formula proposed by this code for estimating the ultimate strength of the elliptical CFST columns was achieved by modifying the formula for predicting the ultimate strength of the square CFST members. In this context, the objective of this study is to evaluate the applicability of the existing code formulae that were proposed for the axially loaded CFST columns with rectangular or circular sections to that of columns with an elliptical section. To this, a data repository consisting of 97 experimentally tested elliptical CFST columns was compiled. Herein, the main criterion in the selection of the data was the axial loading condition. Thereafter, the prediction performance of these code formulae was assessed in terms of statistical parameters. The results indicated that the code formulae proposed for the circular-sectioned CFST columns have better prediction capability than that suggested for the rectangular sections. Among these design formulae proposed for the CFST columns with a circular section, the formulae recommended by the American Institute of Steel Construction, British Standard Institute, Canadian Standards Association, and Eurocode 4 performed the best prediction capability. These code formulae had the lowest mean absolute percent error values and R-squared values of higher than 0.8.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".