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Record W7005598097

Resistance Factor for Cold-Formed Steel Compression Members

2010· dissertation· en· W7005598097 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueVTechWorks (Virginia Tech) · 2010
Typedissertation
Languageen
FieldMedicine
TopicBiological and pharmacological studies of plants
Canadian institutionsnot available
Fundersnot available
KeywordsBucklingCompression (physics)Limit state designResistance FactorsColumn (typography)Moment (physics)Limit (mathematics)Strength reductionReduction (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.031
GPT teacher head0.327
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it