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Record W1976628178 · doi:10.1002/pen.20730

Rheology studies of foam flow during injection mold filling

2007· article· en· W1976628178 on OpenAlexaff
Xingzong Qin, Michael R. Thompson, Andrew N. Hrymak

Bibliographic record

VenuePolymer Engineering and Science · 2007
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceRheologyComposite materialMoldBlowing agentPolymerShear ratePolyolefinMolding (decorative)ViscosityThermoplasticPolyurethane

Abstract

fetched live from OpenAlex

Abstract This work studies the flow behavior of a developing two‐phase gas‐polymer suspension during injection into the instrumented mold cavity of an injection molding machine. In the experiments, blowing agent type and concentration were varied along with processing conditions, to generate controlled cell structures in two different polymers, low density polyethylene and thermoplastic polyolefin. Experimental results indicate that the rheological properties of two phase gas‐polymer suspensions were sensitive to shear rate, blowing agent concentration, melt temperature, and mold temperature. The viscosity of all gas‐polymer suspensions revealed a reduction compared with neat polymer melt in the presence of gas bubbles, because of the reduced volume fraction of polymer matrix. A two‐phase rheological model has been used for fitting with our experimental results for estimating the shear viscosity of two‐phase flow in the mold cavity of the injection molding machine. POLYM. ENG. SCI., 47:522–529, 2007. © 2007 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 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: 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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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

Citations27
Published2007
Admission routes1
Has abstractyes

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