Large eddy simulation of an ignition sequence and the resulting steady combustion in a swirl-stabilized combustor using FGM-based tabulated chemistry
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».