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Record W2018351288 · doi:10.1177/002199803031054

Triaxial Woven Fabric (TWF) Composites with Open Holes (Part I): Finite Element Models for Analysis

2003· article· en· W2018351288 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.

Bibliographic record

VenueJournal of Composite Materials · 2003
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis and Optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsSuperelementFinite element methodStructural engineeringMaterials scienceComposite materialVibrationEngineeringExtended finite element methodFinite element limit analysisPhysics

Abstract

fetched live from OpenAlex

Two finite element models (Superelement 1 and Superelement 2)are developed for prediction of mechanical behavior of triaxial woven fabric (TWF) composites with open holes. Superelement 1 is a 15-node superelement constructed of six identical 8-node 3-D isoparametric elements and three identical 4-node 2-D isoparametric laminate elements. Superelement 2 is similar to the first element except that this element takes into account the geometric and material properties of the twisted yarns. The assembly is done by the pseudo element technique suggested herein and the static condensation procedure. The availability of these elements allows for the analysis of complex structures of the triaxial fabric with open holes. Superelement 1 can be used for the vibration analysis with some economy of computer space and time. Superelement 2 can be used for detailed stress analysis and for strength prediction. Although these two elements are developed for the TWF composites with open holes, they can be applicable for analytical models for other materials and structures made of other types of textile composites.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.578

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.244
Teacher spread0.220 · 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