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Record W2050919830 · doi:10.3139/217.2118

Studying the Effective Thermal Properties of Solids in Extrusion Machinery using a Discrete Particle Simulation Approach

2008· article· en· W2050919830 on OpenAlexaff
Paul A. Moysey, K. L. Cloet, Michael R. Thompson

Bibliographic record

VenueInternational Polymer Processing · 2008
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceHigh-density polyethyleneThermal conductivityThermal conductionParticle (ecology)Composite materialHeat transferExtrusionPolystyrenePolyethylenePolymerPlastics extrusionThermalThermal diffusivityPorosityParticle sizeMechanicsThermodynamicsChemical engineering

Abstract

fetched live from OpenAlex

Abstract In this paper, both experimental trials and numerical simulations are presented to improve our understanding of the heat transfer within granular polymer beds for systems with and without shear. Both amorphous polymer, polystyrene (PS), and a semi-crystalline polymer, high-density polyethylene (HDPE) of varying particle size from 6 mm to 25 mm were examined. The estimated effective thermal conductivity data from the experimental trials was found by fit to two simple semi-empirical models allowing readers to readily approximate the property based on porosity of the bed and solid thermal properties. Discrete particle simulations, i. e. DEM, were used to recognize the importance of heat transport through the stagnant interstitial gas phase in comparison to particle-particle conduction. The results underscore the importance of including an effective thermal conductivity for granular solids in an extruder when using continuum models.

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 score0.406
Threshold uncertainty score0.333

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 head0.030
GPT teacher head0.252
Teacher spread0.223 · 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

Citations10
Published2008
Admission routes1
Has abstractyes

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