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Record W3049098225 · doi:10.1177/0021998320949635

Measuring fibre orientation and predicting elastic properties of discontinuous long fibre thermoplastic composites

2020· article· en· W3049098225 on OpenAlexafffund
Réjean Belliveau, Éric Léger, Benoit Landry, Gabriel LaPlante

Bibliographic record

VenueJournal of Composite Materials · 2020
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsUniversité de Moncton
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceComposite materialAnisotropyDiscontinuity (linguistics)Elastic modulusModulusOrientation (vector space)Compression (physics)LaminationEnhanced Data Rates for GSM EvolutionGeometryOpticsMathematics

Abstract

fetched live from OpenAlex

Elastic properties in critical areas of 3 D shells made from discontinuous long fibre (DLF) composites are difficult to determine via traditional methods, due to the heterogeneity of the material and the geometry of the part. In this paper, a method is proposed to predict the local modulus of DLF composites based on a micrograph of the polished edge of a specimen. The position and orientation of each fibre are extracted from the micrograph and used in conjunction with classical lamination theory to predict the elastic modulus. Fibre discontinuity is accounted for by including a correction factor based on the Cox formula for averaged elastic constants. Model predictions successfully matched the experimental tests results. In a previous study, material flow during compression moulding of recycled DLF panels led to anisotropic behaviour, which was hypothesized to be caused by chip alignment in the flow direction. By using the proposed method, chip alignment due to flow was confirmed and the anisotropy in the elastic modulus was accurately predicted.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.811

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 head0.019
GPT teacher head0.190
Teacher spread0.171 · 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

Citations6
Published2020
Admission routes2
Has abstractyes

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