MétaCan
Menu
Back to cohort
Record W4392482464 · doi:10.31399/asm.cp.itsc2013p0654

Numerical Simulation of Gas Dynamics and Particle Behavior in Low-Temperature Oxygen Fuel Spray Process

2013· article· en· W4392482464 on OpenAlexaboutno aff
Chen Shen, Y. Shan, Laibing Jia

Bibliographic record

VenueThermal spray · 2013
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
Fundersnot available
KeywordsOxygenProcess (computing)Particle (ecology)Materials scienceComputer simulationMechanicsNuclear engineeringComputer scienceChemistryPhysicsEngineering

Abstract

fetched live from OpenAlex

Abstract Low-temperature oxygen fuel (LTOF) spraying is a modification of the high-velocity oxyfuel (HVOF) process. By injecting room temperature gas into the mixing chamber, process temperature is reduced, allowing temperature-sensitive materials to be successfully deposited. In the LTOF process, the gas mixture is accelerated to supersonic speeds through a Laval nozzle. The purpose of this work is to establish a 2D mathematical model to simulate gas dynamics and particle behavior during LTOF spraying. The model is used to predict the temperature and velocity of flow fields and the heating and trajectory of in-flight particles for different gas mixes, mass flow rates, particle sizes, and injection conditions.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.873

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.262
Teacher spread0.253 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueThermal spraySame topicCatalytic Processes in Materials ScienceFrench-language works237,207