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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 OpenAlexaff
Qi Zhao, Suong V. Hoa

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
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

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 designSimulation or modeling
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

Citations32
Published2003
Admission routes1
Has abstractyes

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