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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 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

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.

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)0.001
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 score0.012
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.243
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