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Record W3045644507 · doi:10.1177/1558925020946449

Improving two-dimensional braided composite tensile properties by including low angle yarn twist: Production, experimental verification, and modeling

2020· article· en· W3045644507 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Engineered Fibers and Fabrics · 2020
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsYarnMaterials scienceUltimate tensile strengthTwistComposite materialComposite numberTextileStiffnessManufacturing processProcess (computing)Structural engineeringComputer scienceEngineeringMathematicsGeometry

Abstract

fetched live from OpenAlex

Tubular braided composites combine manufacturing technologies from textiles and composites industries. The design of the reinforcing textile structure plays a significant role in the mechanical characteristics of the final composite. Twisted yarns have shown improved strength over untwisted ones, even for continuous multifilament yarns where twist is not necessary for the manufacturing process. In this work, a manufacturing process is piloted in which twisted yarns are introduced to the braiding process. Static testing is then done to determine the impact of yarn twist on the stiffness and strength. Finally, the Ramberg–Osgood model is adapted to the results in order to provide a descriptive model for the behavior of tubular braided composites beyond the proportional limit.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.201
Teacher spread0.182 · 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