O.I.C.-based design of extruded aluminium rectangular hollow sections under simple load cases
Bibliographic record
Abstract
This paper investigates the influence of local buckling on the ultimate capacity of extruded aluminium sections with rectangular and square hollow sections under simple loading conditions, including axial compression, major-axis bending and minor-axis bending. Advanced non-linear shell finite element models were first developed and validated against existing experimental data. This validation was carefully conducted, relying on many experimental measurements, including section dimensions, material properties, and actual geometrical imperfections. Subsequently, comprehensive numerical parametric analyses were performed, accounting for a range of parameters such as different section dimensions, three aluminium alloys, and three simple load cases. The numerical results collected then served as reference data for the development of a new design method for extruded rectangular and square hollow aluminium sections, relying on the Overall Interaction Concept (O.I.C.). The O.I.C.-based design proposals were assessed by comparing their resistance predictions with the reference numerical results and resistance estimates from the European, Canadian, and American aluminium design standards. Detailed analyses revealed that the O.I.C. approach provides significantly more accurate and consistent results than these standards while remaining simple and efficient. Furthermore, the reliability of the proposed O.I.C. approach was found to be excellent, as demonstrated through statistical analyses conducted in accordance with EN 1990 guidelines.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".