Resistance Factor for Cold-Formed Steel Compression Members
Bibliographic record
Abstract
This research investigates if the LRFD strength reduction factor for cold-formed steel compression members can be increased above its current value of Ï c = 0.85, which was established by the LRFD Cold-Formed Steel Design Manual (1991) on the basis of 264 column tests. The resistance factor in the Canadian code for cold-formed steel compression members is also evaluated. A total of 675 concentrically loaded plain and lipped C-section columns, plain and lipped Z-section columns, hat and angle columns, including members with holes, are considered in the study. The predicted strengths are calculated with the AISI-S100-07 Main Specification and the AISI Direct Strength Method. The test-to-predicted strength statistics are employed with the first order second moment reliability approach in AISI-S100-07 Chapter F as well as a higher order method to calculate the resistance factor per cross-section type, ultimate limit state, and considering partially and fully effective columns. The observed trends support a higher resistance factor for columns buckling in a distortional buckling limit state and an expansion of the current DSM prequalified limits. The results also show that DSM predicts the column capacity more accurately than the Main Specification. The test-to-predicted ratios for plain and lipped angle columns exhibit a high coefficient of variation and become more and more conservative as global slenderness increases. It is concluded that fundamental research on the mechanics of angle compression members is needed to improve existing design methods.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".