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Record W2031240324 · doi:10.1115/gt2014-27225

Large Eddy Simulation of a Turbulent Swirling Jet-A1 Spray Flame Incorporating Chemical Non-Equilibrium Effects Through the Flamelet Model

2014· article· en· W2031240324 on OpenAlexafffund
Alain Fossi, Alain deChamplain, Ali Ghazlani, Bernard Paquet, Smail Kalla, Jeffrey M. Bergthorson, Benjamin Akih‐Kumgeh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsMcGill UniversityUniversité Laval
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsLarge eddy simulationJet (fluid)TurbulenceCombustionMechanicsJet fuelChemistryThermodynamicsProbability density functionFlame structureMaterials sciencePhysicsPhysical chemistryOrganic chemistryCombustorMathematics

Abstract

fetched live from OpenAlex

A large eddy simulation (LES) of a turbulent swirl stabilized jet-A1 flame is presented. The scope of the study is to incorporate a reduced chemistry model, as well as, coupling the turbulent flow characteristics to the chemical reactions and at the same time model the local chemical non-equilibrium due to the turbulent strain. Standard Eulerian and Lagrangian approaches are used to describe both gas and liquid phases, respectively. A joint presumed probability density function (PDF) is used to model turbulent-chemistry interactions in swirling jet-A1 spray flames. A one-component fuel, n-decane, is used as a surrogate for jet-A1. The combustion chemistry of the one component is represented through a reduced chemical kinetic mechanism (CKM) which comprises 139 species and 1 045 reactions, derived from the detailed jet fuel surrogate model, JetSurf 2.0. Numerical results of the gas velocity, the gas temperature and the species mole fractions are compared with a set of published experimental data of a steady flame. In addition to the overall reasonable agreement obtained with the experimental data, it is observed that, by combining a sufficiently realistic chemistry model with LES to simulate a jet-A1 spray flame, the prediction of major species is significantly improved while pollutants such as carbon monoxide (CO) and other species involved in slow reactions, are under predicted for reasons discussed in the paper.

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: none
Teacher disagreement score0.512
Threshold uncertainty score0.660

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 head0.007
GPT teacher head0.222
Teacher spread0.216 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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