Direct numerical simulation of nonpremixed ignition under gasoline compression-ignition engine conditions
Notice bibliographique
Résumé
We present an analysis of the ignition process in thermochemical conditions relevant to gasoline compression-ignition (GCI) engines using direct numerical simulation (DNS). Two-dimensional DNS modelling the interaction of turbulence with an igniting double mixing layer are carried out. Three different primary reference fuel (PRF) blends, PRF0, PRF70, and PRF90, to span a range of different possible compression ignition scenarios are investigated. The fuel chemistry is shown to significantly affect the ignition process and the transition to a fully burning high-temperature flame. All three cases exhibit a diffusively supported cool flame which propagates towards richer mixtures faster than expected from homogeneous ignition delays. High-temperature combustion (HTC) initiates in rich mixtures in the PRF0 case, in both rich and lean mixtures in the PRF70 case, and in lean mixtures in the PRF90 case, which is consistent with expectations from homogeneous ignition delays. Budget analysis shows that HTC flames are diffusively supported in all cases, and as a result progress more rapidly from the ignition location to surrounding mixtures than homogeneous ignitions suggest. A quantitative model is proposed for the premixed flame propagation speed in the stratified and autoignitive mixtures. By considering the effects of normalised residence time of reactant at the flame surface, the conditional mean turbulent flame speed, conditioned upon mixture fraction, can be related to 1D referenced laminar flame speeds. The mechanism of consumption of the stoichiometric surface is examined by considering both displacement speed statistics and by tracking each single edge flame front. In the PRF0 case the results show the stoichiometric surface is consumed mostly by propagating HTC fronts that are almost parallel to it, which is referred to parallel consumption mode, while results in the PRF70 and PRF90 cases show signatures of edge-flame propagation as a secondary mechanism. For edge-flame mode the contribution of tangential-to Z diffusion to the displacement speed prevails over that of normal-to- Z diffusion. Overall the results demonstrate significant fuel-chemistry effects on the evolution of the ignitions, which will probably translate into significant differences in flame structure in a practical GCI engine. Novelty and significance statement This work presents the first DNS of turbulent, nonpremixed autoignition targeting fuel chemistry effects in gasoline compression ignition (GCI) engines. The novelty further arises from two aspects. First, it is the first study to quantitatively model flame displacement speed in autoignitive, stratified mixing layers using the residence time concept. Second, the evolution of edge flame fronts is tracked in complex turbulent flows to enable temporal characterisation of edge flame dynamics and reveal how tangential-to-mixture-fraction diffusion varies across different propagation modes. The significance lies in the implications for practical GCI engine design, as fuel chemistry significantly affects the flame structure, akin to how unravelling the diesel flame structure advanced engine design. These findings also highlight the need to improve practical CFD models, such as incorporating residence time into level-set-based approaches for accurate flame speeds, or characterising conditional fluctuations arising from mixed edge flame modes in flamelet or CMC models.
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 | 0,000 | 0,000 |
| 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 ».