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Record W2040321951 · doi:10.1002/pen.11227

Mixing analysis of reactive polymer flow in a single‐screw extruder channel

2000· article· en· W2040321951 on OpenAlexaff
David Strutt, Costas Tzoganakis, Thomas A. Duever

Bibliographic record

VenuePolymer Engineering and Science · 2000
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceDragMixing (physics)Flow (mathematics)MechanicsPlastics extrusionPolypropyleneVolumetric flow rateIsothermal flowComposite materialOpen-channel flowPhysics

Abstract

fetched live from OpenAlex

Abstract In this study, the finite element method was used to investigate the influence of screw speed, entering peroxide distribution, pressure‐to‐drag flow ratio, and channel geometry on the mixing characteristics of steady non‐isothermal reactive flows. The reaction considered was the peroxide‐initiated degradation of a polypropylene resin in the metering zone of a single‐screw extruder. The predicted average degree‐of‐freedom profiles from the simulations largely conformed to expectations. The average flow efficiencies for all runs were found to vary little along the channel length, remaining at values close to that for two‐dimensional flow. No significant effect of either screw speed or peroxide distribution was found on the flow efficiencies. However, both the pressure‐to‐drag flow ratio and the channel aspect ratio were found to have significant influences.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.008
GPT teacher head0.209
Teacher spread0.201 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations6
Published2000
Admission routes1
Has abstractyes

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