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Record W2054160005 · doi:10.3139/217.1718

Modeling Filler Dispersion along a Twin-Screw Extruder

2003· article· en· W2054160005 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

VenueInternational Polymer Processing · 2003
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsAgglomeratePlastics extrusionMaterials sciencePolypropyleneDispersion (optics)Composite materialFiller (materials)Particle-size distributionCalcium carbonateResidence time distributionPolymerFlow (mathematics)Particle sizeMechanicsEngineeringOpticsChemical engineering

Abstract

fetched live from OpenAlex

Abstract Particle size distribution strongly affects physical and mechanical properties of filled polymers. A new model has been developed to predict agglomerate size distribution in a twin-screw extruder (TSE). The model considers the break-up and erosion processes and it uses agglomerate size population balance in its mathematical formulation. The model parameters were evaluated in simple field flow. This paper shows the validation of the model along the extruder using different screw configurations of a short twin screw extruder. Flow parameters along of the TSE necessaries to apply the new dispersion model have been calculated with ©Ludovic software. Calcium carbonate filled polypropylene system was used as model compound. The agglomerate size distribution was evaluated from micrographs of polished samples at different locations along the extruder obtained by reflected light microscopy in conjunction with-semiautomatic image analysis.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.013
GPT teacher head0.249
Teacher spread0.236 · 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