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Record W2054939513 · doi:10.1115/imece2002-33913

Numerical Modeling of a Lifted Laminar Coflow Methane Diffusion Jet Flames Using Detailed Chemistry and Non-Grey Gas Radiation Models

2002· article· en· W2054939513 on OpenAlexaff
Fengshan Liu, Hongsheng Guo, Gregory J. Smallwood

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadiative Heat Transfer Studies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsLaminar flowMethaneRadiative transferDiffusion flameJet (fluid)Absorption (acoustics)Thermal radiationDiffusionChemistryRadiationHeat transferFlame structureCarbon fibersThermodynamicsAnalytical Chemistry (journal)Materials sciencePhysical chemistryCombustionOpticsPhysicsEnvironmental chemistry

Abstract

fetched live from OpenAlex

Two lifted laminar coflow non-sooting methane diffusion jet flames, one diluted by nitrogen and the other diluted by carbon dioxide, at atmospheric pressure were calculated using detailed chemistry and complex thermal and transport properties. Chemical reactions were modeled using the GRI-Mech 3.0 mechanism with species and reactions related to NOx formation removed. Radiation heat transfer by CO, CO2, and H2O was calculated using the discrete-ordinates method coupled with a statistical narrow-band correlated-k based band model. Calculations of each flame were performed with and without radiation absorption term in the radiative transfer equation in order to provide a quantitative evaluation of the importance of radiation absorption in these two lifted flames. Numerical results show that radiation absorption is relatively unimportant in the nitrogen diluted flame but becomes important in the carbon dioxide diluted flame.

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 score0.242
Threshold uncertainty score0.835

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 head0.022
GPT teacher head0.218
Teacher spread0.196 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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