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Record W2024510778 · doi:10.1002/adv.20195

Helical flow of polymer melts in extruders, part 1: Model development

2010· article· en· W2024510778 on OpenAlexaff
Farshid Sanjabi, Simant R. Upreti, Ali Lohi, Farhad Ein‐Mozaffari

Bibliographic record

VenueAdvances in Polymer Technology · 2010
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMaterials scienceExtrusionMolding (decorative)Mechanical engineeringWork (physics)MechanicsFlow (mathematics)Mathematical modelPolymerCompressibilityEngineering drawingComputer scienceComposite materialMathematicsEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract Operating and processing conditions as well as the selection of the screw design in injection molding industry are largely based on trial‐and‐error exercise, which is expensive and time consuming. A better approach is to develop mathematical models to help select the conditions and parameters and predict the process performance. However, most of the models developed and used so far contain unrealistic geometrical and mathematical simplifications. The objective of this work is to develop a steady‐state three‐dimensional mathematical model to describe the flow of an incompressible polymer melt inside a helical geometry, which represents the polymer's true motion in extrusion and injection molding processes. The mathematical model is first developed in a natural cylindrical system. Transformers are then derived to obtain the model in helical coordinates. A novel feature of this work is the consideration of tapered screws, i.e., screws tapered either upward or downward along the direction of the flow. © 2010 Wiley Periodicals, Inc. Adv Polym Techn 29:249–260, 2010; View this article online at wileyonlinelibrary.com . DOI 10.1002/adv.20195

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: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.005
GPT teacher head0.236
Teacher spread0.231 · 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
GenreMethods

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
Published2010
Admission routes1
Has abstractyes

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