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Record W2335857027 · doi:10.1177/0021998315613129

Characterization of mechanical properties of randomly oriented strand thermoplastic composites

2015· article· en· W2335857027 on OpenAlexafffund
Marina Selezneva, Larry Lessard

Bibliographic record

VenueJournal of Composite Materials · 2015
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsMcGill University
FundersNational Research Council CanadaPratt and Whitney CanadaMcGill University
KeywordsMaterials scienceComposite materialUltimate tensile strengthComposite numberThermoplastic compositesShear (geology)PeekFormabilityPolymer

Abstract

fetched live from OpenAlex

There is an emerging interest in the aerospace industry to manufacture components with intricate geometries using discontinuous fibre carbon/polyether–ether–ketone moulding systems (obtained by cutting unidirectional tape into strands). This type of material system is termed randomly oriented strand composites and is appealing for structural applications as it bridges the gap between the lack of formability of continuous fibre composites and the lack of performance of short fibre composites. The objective of this study was to investigate mechanical properties (tensile, compressive, shear and fatigue) of randomly oriented strand composites and to quantify the effect of strand size on their properties. Overall, properties were found to be highly variable and dependent on the strand length. Interestingly, tensile, compressive and shear strength had similar magnitudes and exhibited the same failure mechanisms (strand fracture and debonding). This experimental work expands the knowledge base for randomly oriented strand composite materials.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.219
Teacher spread0.197 · 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 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

Citations121
Published2015
Admission routes2
Has abstractyes

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