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Record W2006598453 · doi:10.1061/9780784413357.211

Experimental Behavior of Bolted Angles and Beam-to-Column Connections

2014· article· en· W2006598453 on OpenAlexafffund
Thierry Béland, Cameron R. Bradley, J. Nelson, Ali Davaran, Eric M. Hines, Robert Tremblay, Larry A. Fahnestock

Bibliographic record

VenueStructures Congress 2014 · 2014
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaPolytechnique MontréalNational Science Foundation
KeywordsStructural engineeringColumn (typography)Beam (structure)Moment (physics)Joint (building)Frame (networking)Ductility (Earth science)Rotation (mathematics)Test dataEngineeringGeometryMaterials scienceCreepConnection (principal bundle)MathematicsPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

Low-ductility braced steel frames are widely used in moderate seismic regions of North America. A research project has been initiated to examine the possible benefits of considering the moment resistance of beam-to-column connections in the gravity load-carrying system to provide such braced frame building structures with minimum dependable lateral reserve capacity. Beam-to-column moment connections are constructed using top and seat angles acting together with beam web clip angles. A first test program has been developed to characterize the inelastic behavior of individual angles subjected to monotonic and cyclic demands. Test results are presented to illustrate the influence of several parameters, including the angle geometry and the loading sequence. A second test program has been undertaken to examine the cyclic inelastic response of the proposed beam-to-column joints. The test program is described and joint rotation capacity predictions based on individual angle test results are presented and discussed.

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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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

Citations5
Published2014
Admission routes2
Has abstractyes

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Same venueStructures Congress 2014Same topicSeismic Performance and AnalysisFrench-language works237,207