Fundamental study on lean operation limit of super lean-burn spark ignition engines
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Bibliographic record
Abstract
Fuel-lean combustion is challenging because of the difficulty in successful ignition-to-flame propagation transition in intense turbulence conditions. This study aims to elucidate the governing factor of fuel dependence on the lean limit through fundamental ignition experiments and numerical simulations. Previous scaling analysis has reported strong correlations between lean engine operation limit and Minimum Ignition Energy (MIE) transitions. Additionally, the temporal evolution of turbulent intensity in the engine cylinder plotted on Peters diagram suggested that the flame kernel growth occurs only in relatively weak turbulent intensity, u ′ , the condition under which u ′ is lower than the MIE transition. To investigate the behavior of flame kernel growth in the vicinity of the MIE transition condition, we conducted ignition experiments under both laminar and turbulent conditions utilizing a constant volume chamber with counter-rotating fans. Flame initiation was achieved by spark discharge at various turbulent intensities. The results showed notable distinctions in flame kernel growth processes between below and above the MIE transition condition. For u ′ < MIE transition, flame kernel development is governed by molecular transports showing an apparent Lewis number effect, whereas for u ′ > MIE transition, the effect seems to disappear. Subsequently, experiments and numerical simulations on spherically propagating flames in quiescent mixtures with various blended fuels were conducted. The results indicated that fuels facilitating rapid flame kernel growth generally exhibited leaner engine operation limits, regardless of engine specifications. The present study successfully demonstrated that the fuels suitable for lean combustion could be predicted by investigation of spherically propagating flames in quiescent mixtures.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it