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Record W2075079916 · doi:10.1109/cecnet.2011.5768755

Numerical simulation of gas-particle two phase flow in Aluminum-oxide ceramics powder spraying process

2011· article· en· W2075079916 on OpenAlexaboutno aff
Liu Chuanshao, Song Chen, Jianxin Zheng

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleMaterials scienceParticle velocityParticle (ecology)MechanicsGas dynamic cold sprayParticle sizeCeramicAccelerationTwo-phase flowFlow (mathematics)Computer simulationComposite materialThermodynamicsChemistryPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

The quality of spraying is influenced by the gas velocity and particle velocity in the cold spraying process. A physical model for supersonic gas-particle two phase flow in cold spraying process is established. Numerical simulation for inlet and outlet flow field of Laval nozzle is carried out. The effects of throat diameter, spraying pressure, temperature and particle size on the gas velocity and particle velocity are investigated. The simulation results show that the gas velocity and particle velocity increase with the increment of spraying pressure and temperature, and the smaller throat diameter, the better gas acceleration in the nozzle, while the particle velocity increases when particle diameter decreases.

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 score0.169
Threshold uncertainty score0.598

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 head0.026
GPT teacher head0.294
Teacher spread0.268 · 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
Published2011
Admission routes1
Has abstractyes

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