Distortional Buckling of Cold-Formed Stainless Steel Sections: Experimental Investigation
Bibliographic record
Abstract
This paper describes the experimental investigation of cold-formed, thin-walled stainless steel sections subject to distortional buckling under compression. Austenitic 304, ferritic 430 stainless steel, and ferritic-like 3Cr12 chromium weldable steel sheets were brake-pressed into simple-lipped channels and lipped channels with intermediate stiffeners. A full set of coupon tests reveal material nonlinearity with low proportionality stress and low n-parameter, anisotropy, and yield strength enhancements up to 2.33 times due to cold-forming. A total of 19 channel sections were tested and failed by distortional buckling at average ultimate stresses greater than the proportionality stress, and hence were influenced by material nonlinearity, with greater nonlinearity evident for sections with intermediate stiffeners. This paper presents comprehensive procedures to determine stainless steel mechanical properties and their influence on the distortional buckling mode of cold-formed sections. Experimental data required to calibrate finite element models and assess current design guidelines for distortional buckling of stainless steel compression members are provided herein.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".