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Record W2736385494 · doi:10.1002/pc.24512

Foam injection molding of glass fiber reinforced polypropylene composites with laminate skins

2017· article· en· W2736385494 on OpenAlexafffund
Pibulchai Kasemphaibulsuk, Marcel Holzner, Takashi Kuboki, Andrew N. Hrymak

Bibliographic record

VenuePolymer Composites · 2017
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsWestern University
FundersTransport Canada
KeywordsMaterials scienceComposite materialPolypropyleneGlass fiberFlexural strengthComposite numberMolding (decorative)Core (optical fiber)Flexural rigidityFlexural modulusFiberMold

Abstract

fetched live from OpenAlex

Sandwich panels which consist of discontinuous glass‐fiber reinforced polypropylene composite foam core and continuous glass‐fiber reinforced polypropylene laminate skins were manufactured using industry‐scale equipment in a streamlined manner. The streamlined process included two stages: (1) continuous glass‐fiber reinforced polypropylene laminates as the face skins were produced using an automated, rapid tape layup machine and a hydraulic press, and (2) discontinuous glass‐fiber reinforced polypropylene composite as the core was foam injection‐molded onto the laminate skins (i.e., overmolding), which eliminated bonding process of the foam core and laminate skins, with a physical blowing agent, nitrogen. Optical microscopy results suggested that the increase of void fraction by the core‐back (or mold opening) technique increased the average cell size and cell size distribution, but had little effect on the cell density of the foam core. Mechanical test results suggested that the addition of laminate skins increased the flexural modulus and flexural strength of the solid as well as foam composites significantly. In addition, the material indices were calculated for the sandwich panels manufactured in this study, and the results suggested that the addition of the laminate skins and foaming by the core‐back (or mold opening) technique can greatly reduce the weight of material needed to have the same bending stiffness and maximum bending force. COMPOS., 39:4322–4332, 2018. © 2017 Society of Plastics Engineers

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 categoriesMeta-epidemiology (narrow)
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 score0.004
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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.011
GPT teacher head0.236
Teacher spread0.226 · 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.

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

Citations14
Published2017
Admission routes2
Has abstractyes

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