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Record W2014353277 · doi:10.1177/0021998312436990

Thermo-mechanical properties of 5-harness satin fabric composites

2012· article· en· W2014353277 on OpenAlexaff
Loleï Khoun, Krishna Challagulla, Pascal Hubert

Bibliographic record

VenueJournal of Composite Materials · 2012
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsLaurentian UniversityMcGill UniversityNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceComposite materialWavinessComposite numberWoven fabricShrinkageMaterial propertiesFinite element methodModulusFabric structureStructural engineering

Abstract

fetched live from OpenAlex

The use of woven textile reinforcements in composite structures increased significantly in the past decades due to their interesting properties over unidirectional fibres. Therefore, the prediction of the thermo-mechanical properties of woven fabric composites is essential from a design and manufacturing standpoint. A micromechanical approach based on finite element method that utilizes three-dimensional unit cell was applied to predict the effective properties of a periodic woven fabric composite material. Using the resin processing properties models such as cure kinetics, shrinkage, glass transition temperature and elastic modulus models, the development of the periodic woven fabric composite material thermo-mechanical properties, as the cure progresses was predicted. The residual strains and stresses generated in the composite unit cell during the cure were also predicted and linked with the development of the material properties. The effective properties of the cured woven fabric composite material were compared to the one of an equivalent cross-ply composite material to verify the validity of neglecting the fibre waviness while modelling woven fabric composite.

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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.024
GPT teacher head0.229
Teacher spread0.205 · 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 teacher head, 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

Citations12
Published2012
Admission routes1
Has abstractyes

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