Design of Class 4 hollow structural section compression members
Bibliographic record
Abstract
This paper presents a study on the CSA S16:19, AISC 360-16, and EN 1993-1-1 approaches to determine the nominal capacity (Cn) of Class 4 hollow structural section compression members. Class 3 limits and effective width (be) equations are compared, and the effect of member slenderness (KL/r), width-(or diameter-)to-thickness ratio, and height-to-width (or aspect) ratio on the relative Cn predictions are evaluated. For Class 4 rectangular hollow sections, CSA S16:19 is shown to under-predict Cn by up to 34% relative to AISC 360-16. A more economical, yet still safe, method to calculate be (and hence, Cn) is proposed. For Class 4 circular hollow sections, a new method to calculate Cn utilizing the “effective area method” is proposed. This new method removes the need for having an “effective yield stress method” in CSA S16 Clause 13.3.4.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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".