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Record W2120167108 · doi:10.1109/icmtma.2013.186

Numerical Simulation on Flow Field of Laval-style Atomizer by Fluent

2013· article· en· W2120167108 on OpenAlexaboutno aff
Chaorun Si

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Heat Transfer
Canadian institutionsnot available
Fundersnot available
KeywordsBody orificeFluentJet (fluid)InjectorSupersonic speedMechanical engineeringNozzleMechanicsFlow (mathematics)Field (mathematics)Analytical Chemistry (journal)Computational fluid dynamicsMaterials sciencePhysicsAerospace engineeringChemistryEngineeringMathematicsChromatography

Abstract

fetched live from OpenAlex

Gas atomization can be used in producing high-quality metal powder and the atomizer has great influence on the production quality. In this paper, the annular orifice atomizer is optimized by adopting Laval nozzle as the shape of gas jet orifice and a three-dimensional model of supersonic annular orifice atomizer is adopted to investigate the flow field characteristic at different atomization gas pressure (P0), including gas velocity, static pressure and aspiration pressure at the delivery tube tip. The numerical results indicate that the maximum gas velocity in the atomization zone increases with increasing P0. The aspiration pressure is also found to increase as P0increases. Comparing with annular slit atomizer, there is no airflow shock wave in the flow field, which can weak the atomization effect.

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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.004
GPT teacher head0.208
Teacher spread0.204 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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