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Record W2783073174 · doi:10.1515/polyeng-2017-0164

Plastic pipe solidification in extrusion

2018· article· en· W2783073174 on OpenAlex
P. Poungthong, Chanyut Kolitawong, Chaimongkol Saengow, A. Jeffrey Giacomin

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

VenueJournal of Polymer Engineering · 2018
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsExtrusionMaterials scienceResidual stressDie swellQuenching (fluorescence)Isothermal processAdiabatic processMechanicsComposite materialStress (linguistics)ConvectionMetallurgyThermodynamics

Abstract

fetched live from OpenAlex

Abstract In plastic pipe extrusion, hot molten extrudate emerges from an annular. This highly viscous liquid is then cooled and solidified, called quenching , in a quench tank. In this paper, we focus on the external cooling system. We use an adiabatic inner wall and differing outer wall boundary conditions: isothermal and convection. The solid-liquid interface, at the solidification temperature, moves inward with deceleration. We adimensionalize the energy balance and solve for the interface speed in terms of the solidifcation coefficient, λ . We arrive at the exact solutions for the evolving solidified thickness. Finally, we use the residual stress model developed by Jansen [ Int. Polym. Proc . 1994, 9, 82–89]. to predict the compressive residual stress at the outer pipe surface. Our new exact solution for the solidification time agrees well with the data from the plastic pipe industry. The goals of this paper are to help plastics engineers calculate the solidification time, to design the cooling chamber and to predict the residual quenching stress.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.364

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 head0.007
GPT teacher head0.220
Teacher spread0.213 · 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