MétaCan
Menu
Back to cohort
Record W2014980680 · doi:10.3139/217.3002

Slip Heating in Die Drool with Viscous Dissipation

2015· article· en· W2014980680 on OpenAlex
P. H. Gilbert, 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Polymer Processing · 2015
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsQueen's University
FundersLos Alamos National LaboratoryCanada Research ChairsGovernment of Canada
KeywordsSlip (aerodynamics)DissipationMaterials scienceExtrusionComposite materialMechanicsThermalThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Abstract Plastics can build-up on the die lip during extrusion. This phenomenon is called die drool and can be costly for plastics producers, requiring periodic shutdowns for die cleaning. Die drool has been attributed to the cohesive fracture of the melt into a drool layer and a bulk layer. The bulk layer slips on the drool layer after fracture, resulting in heating at the slip interface, called slip heating. The heat generated through slip heating can contribute to polymer thermal degradation, and to the die drool degradation. The impact of slip heating on die temperature rise has been investigated by neglecting viscous dissipation (Gilbert and Giacomin, 2014). This work considers viscous dissipation and its importance to slip heating. We find that viscous dissipation and slip heating contribute equally to the melt temperature rise, and we conclude with a worked example showing the importance of these two heating sources during polymer processing. We also develop two sufficient conditions for the accurate use of our results, Pé ≤ 1 and ∂Θ/∂ς ≪ ∂ 2 Θ/∂ζ 2 .

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score0.375

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 head0.014
GPT teacher head0.265
Teacher spread0.251 · 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