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Record W2075129527 · doi:10.1115/icnmm2014-21832

Finite Element Volume Analysis of Propane Preheated Air Flame Passing Through a Minichannel

2014· article· en· W2075129527 on OpenAlexaff
Masoud Darbandi, Majid Ghafourizadeh, G. E. Schneider

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsUniversity of Waterloo
FundersSharif University of Technology
KeywordsTurbulenceUpwind schemeMechanicsCombustionCurrent (fluid)Materials scienceFinite element methodThermodynamicsPhysicsChemistryMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

A hybrid finite-element-volume FEV method is extended to simulate turbulent non-premixed propane air preheated flame in a minichannel. We use a detailed kinetics scheme, i.e. GRI mechanism 3.0, and the flamelet model to perform the combustion modeling. The turbulence-chemistry interaction is taken into account in this flamelet modeling using presumed shape probability density functions PDFs. Considering an upwind-biased physics for the current reacting flow, we implement the physical influence upwinding scheme PIS to estimate the cell-face mixture fraction variance in this study. To close the turbulence closure, we employ the two-equation standard κ-ε turbulence model incorporated with suitable wall functions. Supposing an optically thin limit, it needs to take into account radiation effects of the most important radiating species in the current modeling. Despite facing with so many flame instabilities in such small size configuration, the current method performs suitably with proper convergence, and the encountered instabilities are damped out automatically. Comparing with the experimental measurements, the current extended method accurately predicts the flame structure in the minichannel configuration.

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 score0.796
Threshold uncertainty score0.496

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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

Citations9
Published2014
Admission routes1
Has abstractyes

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