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Record W2017718190 · doi:10.3139/217.1625

Numerical Study of Internal Bubble Cooling (IBC) in Film Blowing

2001· article· en· W2017718190 on OpenAlexaff
V. Sidiropoulos, J. Vlachopoulos

Bibliographic record

VenueInternational Polymer Processing · 2001
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBubbleAirflowMechanicsTurbulenceMaterials scienceInletInternal flowComputer simulationInternal heatingStack (abstract data type)CompressibilityAir bubbleAir coolingFlow (mathematics)Heat fluxMechanical engineeringHeat transferPhysicsEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract Numerical simulation of turbulent airflow emerging from an Internal Bubble Cooling (IBC) stack and directly impinging on the internal surface of a blown film bubble has been carried out. The streamline pattern and heat flux are determined through a finite volume numerical technique using a version of k-∊ turbulence modeling. It is shown that balancing the airflow between the multiple slits of the stack is useful to increase the internal cooling rates, but may require more elaborate designs of the inlet pipe. As the air flows towards the internal bubble surface there is significant deceleration which diminishes the effectiveness of the heat removal mechanisms. Depending on the flow rates and geometrical configurations the airflow may induce compressibility effects at the exhaust pipe. The numerical results suggest that Internal Bubble Cooling (IBC) equipment introduces distinctive design and operation challenges.

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)0.000
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: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.247
Teacher spread0.238 · 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

Citations13
Published2001
Admission routes1
Has abstractyes

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