MétaCan
Menu
Back to cohort
Record W4255645318 · doi:10.1515/iupac.69.0595

Characterization of Finite Length Composites: Part II. Mechanical Performance of Injection Moulded Composites

2016· dataset· en· W4255645318 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

VenueIUPAC Standards Online · 2016
Typedataset
Languageen
FieldEngineering
TopicInjection Molding Process and Properties
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsComposite materialMaterials scienceStiffnessUltimate tensile strengthPolypropyleneInjection mouldingToughnessKevlarGlass fiberPolyamideStress (linguistics)ModulusCreepAramidTensile testingFiberEpoxy

Abstract

fetched live from OpenAlex

An overview is given of the mechanical performance (stiffness, strength, toughness, creep ...) of finite fibre length reinforced thermoplastics based on polypropylene and polyamide as the matrices and glass, carbon and Kevlar as the reinforcement. Different degrees of fibre orientation distribution and fibre attrition as produced by classical injection moulding and multiple-live feed moulding were evaluated. It was found that the simple test geometry used (injection moulded plaques) resembled more a complicated structure than a material. The properties measured therefore were more the complex response of a strongly anisotropic structure than simple material properties. Increased alignment of the fibres in a given direction affected all the mechanical properties, but the effect was largest for the tensile stiffness. A higher degree of fibre orientation, was not accompanied by an increase in properties related to failure (ultimate stress, KIc. The modelling of ultimate stress showed that this could be explained by the more severe fibre attrition which resulted from the forces applied to orient the fibres.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.101
Threshold uncertainty score1.000

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 head0.013
GPT teacher head0.295
Teacher spread0.282 · 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