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Record W3095030027 · doi:10.1108/hff-03-2020-0136

Large eddy simulation of an ignition sequence and the resulting steady combustion in a swirl-stabilized combustor using FGM-based tabulated chemistry

2020· article· en· W3095030027 on OpenAlexaff
Alain Fossi, Alain deChamplain, Benjamin Akih‐Kumgeh, Jeffrey M. Bergthorson

Bibliographic record

VenueInternational Journal of Numerical Methods for Heat &amp Fluid Flow · 2020
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsMcGill UniversityUniversité Laval
Fundersnot available
KeywordsCombustionCombustorLarge eddy simulationMechanicsIgnition systemComputational fluid dynamicsMaterials sciencePremixed flameTurbulenceThermodynamicsChemistryPhysics

Abstract

fetched live from OpenAlex

Purpose This study aims to deal with the large eddy simulation (LES) of an ignition sequence and the resulting steady combustion in a swirl-stabilized liquid-fueled combustor. Particular attention is paid to the ease of handling the numerical tool, the accuracy of the results and the reasonable computational cost involved. The primary aim of the study is to appraise the ability of the newly developed computational fluid dynamics (CFD) methodology to retrieve the spark-based flame kernel initiation, its propagation until the full ignition of the combustion chamber, the flame stabilization and the combustion processes governing the steady combustion regime. Design/methodology/approach The CFD model consists of an LES-based spray module coupled to a subgrid-scale ignition model to capture the flame kernel initiation and the early stage of the flame kernel growth, and a combustion model based on the mixture fraction-progress variable formulation in the line of the flamelet generated manifold (FGM) method to retrieve the subsequent flame propagation and combustion properties. The LES-spray module is based on an Eulerian-Lagrangian approach and includes a fully two-way coupling at each time step to account for the interactions between the liquid and the gaseous phases. The Wall-Adapting Local Eddy-viscosity (WALE) model is used for the flow field while the eddy diffusivity model is used for the scalar fluxes. The fuel is liquid kerosene, injected in the form of a polydisperse spray of droplets. The spray dynamics are tracked using the Lagrangian procedure, and the phase transition of droplets is calculated using a non-equilibrium evaporation model. The oxidation mechanism of the Jet A-1 surrogate is described through a reduced reaction mechanism derived from a detailed mechanism using a species sensitivity method. Findings By comparing the numerical results with a set of published data for a swirl-stabilized spray flame, the proposed CFD methodology is found capable of capturing the whole spark-based ignition sequence in a liquid-fueled combustion chamber and the main flame characteristics in the steady combustion regime with reasonable computing costs. Research limitations/implications The proposed CFD methodology simulates the whole ignition sequence, namely, the flame kernel initiation, its propagation to fully ignite the combustion chamber, and the global flame stabilization. Due to the lack of experimental ignition data on this liquid-fueled configuration, the ability of the proposed CFD methodology to accurately predict ignition timing was not quantitatively assessed. It would, therefore, be interesting to apply this CFD methodology to other configurations that have experimental ignition data, to quantitatively assess its ability to predict the ignition timing and the flame characteristics during the ignition sequence. Such further investigations will not only provide further validation of the proposed methodology but also will potentially identify its shortfalls for better improvement. Practical implications This CFD methodology is developed by customizing a commercial CFD code widely used in the industry. It is, therefore, directly applicable to practical configurations, and provides not only a relatively straightforward approach to predict an ignition sequence in liquid-fueled combustion chambers but also a robust way to predict the flame characteristics in the steady combustion regime as significant improvements are noticed on the prediction of slow species. Originality/value The incorporation of the subgrid ignition model paired with a combustion model based on tabulated chemistry allows reducing computational costs involved in the simulation of the ignition phase. The incorporation of the FGM-based tabulated chemistry provides a drastic reduction of computing resources with reasonable accuracy. The CFD methodology is developed using the platform of a commercial CFD code widely used in the industry for relatively straightforward applicability.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.433
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.056
GPT teacher head0.375
Teacher spread0.319 · 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

Citations8
Published2020
Admission routes1
Has abstractyes

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