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Record W2320568831 · doi:10.1021/ef402057w

Detailed Emissions Prediction for a Turbulent Swirling Nonpremixed Flame

2013· article· en· W2320568831 on OpenAlex
Rory F.D. Monaghan, Råbi Tahir, Gilles Bourque, Robert L. Gordon, Alberto Cuoci, Tiziano Faravelli, Alessio Frassoldati, Henry J. Curran

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy & Fuels · 2013
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsRolls-Royce (Canada)
FundersIrish Research CouncilTranslation Centre for the Bodies of the European UnionEuropean Commission
KeywordsComputational fluid dynamicsTurbulenceDiscretizationMechanicsCombustionCombustorMomentum (technical analysis)Large eddy simulationTurbulence modelingTurbulence kinetic energyKinetic energyThermodynamicsChemistryPhysicsClassical mechanicsMathematics

Abstract

fetched live from OpenAlex

This paper describes the validation of a previously described CFD-CRN method (computational fluid dynamics–chemical reactor network) for emissions predictions for the laboratory benchmark TECFLAM S09c flame. It details CFD simulation, solution strategy, validation using, CRN generation, detailed emissions predictions and reaction pathway studies. Steady-state 3D CFD models of a 45° sector of the combustor, employing standard numerical techniques; steady-state k–ω SST turbulence, P1 radiation, finite-rate eddy-dissipation turbulence-chemistry interaction, and a three-step methane combustion mechanism, were created in ANSYS FLUENT v14. Steady-state models were used as they are of interest to industrial researchers, who are often limited to their use by extremely complex geometries. The models differ in their handling of pressure-velocity coupling and discretization of the momentum equation. The solution which uses SIMPLE coupling and second-order upwind discretization of the momentum equation was generally found to give better results. Satisfactory agreement with experimental profiles for velocity, turbulent kinetic energy, temperature, and species mass fractions has been achieved. Some errors are seen in temperature and CO mass fractions at the highest temperatures (T > 2000 K) and are due to the fact that the highly simplified three-step kinetic mechanism employed due to practical limitations on computational resources, underestimates CO2 dissociation. The results compare satisfactorily with the state-of-the-art. Nonzero concentrations of CO are predicted in the external recirculation zone, which has not been achieved in previous modeling efforts. The validated solution was used as the basis to generate a CRN using the CFD-CRN method. The CFD-CRN method uses user-defined criteria to divide the CFD domain into a set of interconnected perfectly stirred reactors (PSRs) (i.e., a CRN). This CRN is then solved using detailed chemical kinetic mechanisms in the Kinetic Post-Processor (KPPSMOKE) solver. CRN size-independence studies are performed, and it is determined that 5000+ PSRs were needed to adequately capture pollutant formation in the complex recirculating flow field. Validation of CFD-CRN predictions of major species show similar accuracy to steady-state CFD simulation, with improvements over state-of-the-art CFD in CO profile predictions. Satisfactory agreement with previously published experimental NOx contour plots is also seen. The CFD-CRN is used to study NOx formation pathways in the swirling, turbulent environment of the S09c diffusion flame. As expected, NOx is seen to form primarily in the high-temperature internal recirculation zone (IRZ). The prompt pathway is predicted to be of greatest importance in this area. Significant NOx reburning is seen in the low temperature fuel–air jets immediately adjacent to the IRZ. Overall, the prompt pathway is responsible for 77% of NOx leaving the system, with 12% due to thermal and 11% due to N2O intermediate.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.696
Threshold uncertainty score0.548

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 head0.008
GPT teacher head0.194
Teacher spread0.187 · 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