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Record W2770949465 · doi:10.3139/217.3430

Transient Swell of a High Density Polyethylene Using Adjustable Gap Slit Die

2017· article· en· W2770949465 on OpenAlexaff
Vinod Kumar Konaganti, Ehsan Behzadfar, Rhokyun Kwak, Evan Mitsoulis, Savvas G. Hatzikiriakos

Bibliographic record

VenueInternational Polymer Processing · 2017
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSwellDie swellMaterials scienceDie (integrated circuit)Steady state (chemistry)Transient (computer programming)MechanicsComposite materialThermodynamicsPlastics extrusionPhysicsComputer scienceChemistry

Abstract

fetched live from OpenAlex

Abstract A novel slit die with an adjustable gap is designed to perform transient swell measurements while changing the die gap dynamically. A generalized control model is developed to predict time-dependent swell using characteristic relaxation time and corresponding steady state swell as model parameters. Further, a series of slit dies are designed and used to measure steady state thickness swell of a high-molecular-weight blow-molding grade high density polyethylene resin under various operating and geometrical conditions. A generalized expression for steady state thickness swell is obtained by applying multi-variable nonlinear regression on thus obtained steady state thickness swell data, and is used in the empirical control model to predict transient extrudate swell.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.463
Threshold uncertainty score0.594

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 head0.024
GPT teacher head0.278
Teacher spread0.254 · 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 designBench or experimental
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

Citations4
Published2017
Admission routes1
Has abstractyes

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