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Record W1979695491 · doi:10.1177/0892705703016001206

Modeling of 3D Angle Interlock Woven Fabric Composites

2003· article· en· W1979695491 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 Thermoplastic Composite Materials · 2003
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComposite materialMaterials scienceWoven fabricInterlockComposite numberStiffnessStructural engineeringEngineering

Abstract

fetched live from OpenAlex

A three dimensional micromechanical modeling approach was previously developed for predicting elastic constants of 2D woven fabric composites [Sheng, S.Z. and Hoa, S.V. (2001). Three dimensional micromechanical modeling of woven fabric composites. Journal of Composite Materials, 35(19): 1701-1729.]. In this paper, the approach is extended for predicting elastic constants of 3D angle interlock woven fabric composites. The micro fabric geometry of general 3D woven composites is described by using a three dimensional geometric model first. Then a variational potential method is proposed to obtain the continuous integration transformation of the three-dimensional stiffness and compliance matrices associated with the micro fabric geometry for 3D woven fabric composites. Finally, elastic constants are obtained by using the method based on the fabric geometry for several 3D angle interlock woven fabric composites. Good agreement is shown between the present predicted results and experimental results available in the literature.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.024
Threshold uncertainty score0.997

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)0.0040.000

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 head0.023
GPT teacher head0.259
Teacher spread0.236 · 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