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Record W4416994919 · doi:10.1063/5.0301133

Numerical study of the gas flow characteristics formed by composite nozzles under oxygen blowing conditions

2025· article· en· W4416994919 on OpenAlexaboutno aff
Т. S. Golub, L. S. Мolchanov, Олександр Мінай, Andrii Koveria

Bibliographic record

VenuePhysics of Fluids · 2025
Typearticle
Languageen
FieldEngineering
TopicRadiative Heat Transfer Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleComposite numberJet (fluid)Flow (mathematics)Computer simulationDischarge coefficient

Abstract

fetched live from OpenAlex

The paper involves results of numerical modeling in ANSYS of the behavior of gas flows emanating from composite nozzles (consisting of two concentrically placed hollow cylinders with different shares of the peripheral annular part; the same gas (oxygen) is supplied through the inner and outer parts). The study was conducted for different designs of composite nozzles: with 25%, 50%, and 75% peripheral fractions of the nozzle with the same outer nozzle diameter and equal total cross-sectional area. The results were compared with the results of numerical modeling of blowing through a cylindrical nozzle and a Laval nozzle with similar equivalent nozzle diameters. It was found that the peripheral part of the composite-type flow is more responsible for the characteristics of the gas jet formed and its axial velocity parameters. Accordingly, at a peripheral fraction of 25%, a flow is formed with characteristics close to the flow that is formed by a Laval nozzle. When the peripheral fraction is increased to 50% and 75%, a more complex multi-node structure of interacting flows is formed. It is reflected and confirmed by the shadow imaging method and by interaction with a liquid bath using the air–water model.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score0.462

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 head0.012
GPT teacher head0.246
Teacher spread0.234 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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