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Record W1968931185 · doi:10.1139/l01-059

Design method for bolted connections loaded perpendicular-to-grain

2001· article· en· W1968931185 on OpenAlexfundvenueno aff
J. H. P. Quenneville, Mazian Mohammad

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2001
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
FundersMinistère de la Défense Nationale
KeywordsRivetStructural engineeringPerpendicularFastenerConnection (principal bundle)Failure mode and effects analysisYield (engineering)EngineeringBolted jointFinite element methodMaterials scienceComposite materialMathematicsGeometry

Abstract

fetched live from OpenAlex

A new design approach to evaluate the resistance of bolted timber connections loaded perpendicular-to-grain is presented in this paper. The design method consists of calculating the resistances of the ductile failure modes, based on the original European yield model, and that of the splitting mode, and of using the smallest of the two. The splitting calculations are adapted from the wood resistance calculation for timber rivet connections. The new design method is based on the assumption that the bolted connection is forming a cluster considered to be equivalent in dimension to a cluster of timber rivets. The rivet design equations were modified to reflect the fact that bolts extend to the full thickness of the wood members, whereas rivets do not. In this paper, the research program is described, results are presented and the alternative design approach is proposed to predict the failure modes and the ultimate strengths of steel–wood–steel, wood–wood–wood, and wood–steel–wood bolted connections.Key words: connections, strength, design, bolt, connection, prediction, failure, perpendicular-to-grain.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.217
Teacher spread0.196 · 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

Citations19
Published2001
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicWood Treatment and PropertiesFrench-language works237,207