Direct numerical simulation of nonpremixed ignition under gasoline compression-ignition engine conditions
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".