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Record W2072304426 · doi:10.3139/217.2351

Three-dimensional Finite Element Solution of the Flow in Single and Twin-Screw Extruders

2010· article· en· W2072304426 on OpenAlexaff
F. Ilinca, J.‐F. Hétu

Bibliographic record

VenueInternational Polymer Processing · 2010
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceFinite element methodMechanicsRotation (mathematics)Plastics extrusionNewtonian fluidFlow (mathematics)Work (physics)ViscosityIsothermal processExtrusionMechanical engineeringShear rateNon-Newtonian fluidGeometryStructural engineeringMathematicsComposite materialEngineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract This work is aimed at the numerical modeling of the flow inside single and twin-screw extruders. Numerical solutions are obtained using a recently developed immersed boundary finite element method capable of solving the flow in the presence of complex non-stationary solid boundaries. The method is first validated against the solution obtained on a body-conforming grid for a single screw extruder and then applied to a twin-screw mixer. The time dependent single screw problem can also be solved in a rotating reference frame for which a steady state solution can be obtained. This allows the evaluation of time integration errors of the moving immersed interface algorithm. For instance the flow is considered isothermal and the material behaves as a Generalized Newtonian fluid. Because the viscosity depends on the shear rate, solutions will be shown for various rotation velocities of the screw and compared with solutions obtained on body-conforming grids. The method is shown to give very accurate results and can be used for a more in-depth investigation of the material behavior in extruders.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.244
Teacher spread0.228 · 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 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

Citations30
Published2010
Admission routes1
Has abstractyes

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