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Record W2045558374 · doi:10.3390/coatings3040208

A Study of a Powder Coating Gun near Field: A Case of Staggered Concentric Jet Flow

2013· article· en· W2045558374 on OpenAlexafffund
Graham Payne, Darko Matovic, E. W. Grandmaison

Bibliographic record

VenueCoatings · 2013
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsQueen's University
FundersGovernment of Ontario
KeywordsMechanicsGambitJet (fluid)Reynolds-averaged Navier–Stokes equationsNozzleTurbulencePitot tubeCoaxialFluentMaterials scienceFlow (mathematics)Computational fluid dynamicsMechanical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

This paper examines, experimentally and numerically, an isothermal coaxial air jet, created by an innovative nozzle design for an air propane torch, used for the thermal deposition of polymers. This design includes staggering the origins of the central and annular jets and creating an annular air jet with an inward radial velocity component. The experimental work used a Pitot tube to measure axial velocity on the jet centerline and in the fully developed flow. The static gauge pressure in the near field was also measured and found to be positive, an unexpected result. The numerical work used Gambit and Fluent. An extensive grid sensitivity study was conducted and it was found that results from a relatively coarse mesh were substantially the same as results from a mesh with almost 11 times the number of control volumes. A thorough evaluation of all of the RANS models in Fluent 6.3.26 found that the flow fields they calculated showed at most partial agreement with the experimental results. The greatest difference between numerical and experimental results was the incorrect prediction by all RANS models of a recirculation zone in the near field on the jet axis. Experimental work showed it did not exist.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.547

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 head0.009
GPT teacher head0.227
Teacher spread0.217 · 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 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

Citations3
Published2013
Admission routes2
Has abstractyes

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