Proposals for limit states torsional strength design of wide-flange steel members
Bibliographic record
Abstract
This paper addresses the design of wide-flange steel members subjected to torsional forces as well as axial forces and moments about their strong and weak axes. The current Canadian steel design standard (CSA S16–01) gives no specific guidance on methodology with respect to torsional design. Codes of other countries (American, British, Australian) provide useful insight but are different in format from the Canadian standard and cannot be used directly in conjunction with it. Specialized second-order finite element programs have the capacity for torsional analysis, but are too complicated and costly to use in design practice. There is, therefore, a need for a practical design method that would allow engineers to account for the effects of torsion simply and accurately. This paper, written by a practicing design engineer, suggests a number of approaches that, subject to discussion and approval by experts in the field, could constitute the basis for design of steel members in torsion.
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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 | 0.001 | 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) | 0.000 | 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".