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Record W4394745924 · doi:10.62913/engj.v40i1.799

Design Recommendations for Bolted Rectangular HSS Flange-Plate Connections in Axial Tension

2003· article· en· W4394745924 on OpenAlexafffund
S. Willibald, Jeffrey A. Packer, Ram Puthli

Bibliographic record

VenueEngineering Journal · 2003
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of TorontoDeutsche Forschungsgemeinschaft
KeywordsFlangeStructural engineeringTrussStiffnessTension (geology)BucklingEngineeringFastenerMaterials scienceUltimate tensile strengthComposite material

Abstract

fetched live from OpenAlex

In recent years the use of closed sections/tubes as structural members has increased significantly. Designers all around the world approve of the advantages that round as well as rectangular hollow structural sections (HSS) can offer, such as uniform strength and stiffness independent of the loading direction, high torsional and buckling strength and the aesthetic appearance. Splicing structural members is a common practice in construction to allow for long spanning trusses, changes in cross sections and transportation to site, to name but a few. The results of an experimental investigation of four bolted flange-plate connections between rectangular hollow structural sections, with bolts on all four sides, have been presented. A brief overview of different design methods for bolted flange-plate connections for square and rectangular hollow structural sections under tension load has also been given. A comparison of the load predictions of the various methods for the specimens in the experimental program supports the use of the design procedure that can be found in the AISC HSS Connections Manual (AISC, 1997).

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.025
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0030.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0250.013

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 head0.020
GPT teacher head0.229
Teacher spread0.209 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations15
Published2003
Admission routes2
Has abstractyes

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