MétaCan
Menu
Back to cohort
Record W2006030034 · doi:10.1139/l10-028

Behaviour of steel single angles subjected to eccentric axial loads

2010· article· en· W2006030034 on OpenAlexaffvenue
Yi Liu, Linbo Hui

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEccentricity (behavior)EccentricStructural engineeringBucklingBendingCompression (physics)Finite element methodMaterials scienceNeutral axisReduction (mathematics)MechanicsMathematicsGeometryComposite materialEngineeringBeam (structure)Physics

Abstract

fetched live from OpenAlex

The response of steel single angles subjected to axial eccentric loading is investigated by means of numerical modeling based on finite element techniques. Results show that in the case of eccentric compression causing major axis bending, a critical eccentricity for each slenderness ratio investigated exists and below this eccentricity, any reduction in the ultimate capacity due to eccentricity is marginal. The critical eccentricity increases with the slenderness ratio of the angle. In contrast, for the case of eccentric compression causing minor axis bending, the reduction in ultimate capacity, as affected by increasing eccentricity, is more pronounced and no similar critical eccentricity is identified. When compared with values determined from the design equations suggested in the AISC specification 2005, results indicate that the AISC equations, in general, give a satisfactory estimate of the ultimate capacity for angles subjected to axial compression and minor axis bending. For the case of eccentric compression causing major axis bending, AISC equations are conservative over a large range of parameters while they overestimate capacities in some other angles.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.005
GPT teacher head0.173
Teacher spread0.168 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicStructural Load-Bearing AnalysisFrench-language works237,207