Effect of spark discharge energy scheduling on ignition under quiescent and flow conditions
Bibliographic record
Abstract
The enhancement of the breakdown power during the spark discharge process has been proved to be beneficial for the flame kernel formation process under lean/diluted conditions. Such a strategy is realized by using a conventional transistor coil ignition system with an add-on capacitance in parallel to the spark plug gap in this paper. In practical application, the use of different ceramic material other than aluminum oxide can change the parasitic capacitance of the spark plug, achieving similar effect in terms of rescheduling the discharge energy released during the breakdown phase. Detailed research has been carried out to investigate the effect of the parallel capacitance and the cross flow velocity on the flame kernel formation and propagation process. With the increase in parallel capacitance, more spark energy is delivered during the breakdown phase, while less energy is released during the arc/glow phase. Shadowgraph images of the spark plasma reveal that the high-power spark discharge can generate a larger high-temperature area with enhanced electrically prompted turbulence under quiescent conditions, as compared with that using the conventional transistor coil ignition discharge strategy under the same condition. The breakdown enhanced turbulence of the high-power spark is proved to be beneficial for the flame kernel development, especially with the lean or exhaust gas recirculation diluted combustible mixtures, given that sufficient spark energy is available for the high-power spark strategy to successfully generate the breakdown event. The results of combustion tests under flow conditions reveal that the breakdown enhanced turbulence of the high-power spark tends to be overshadowed by the turbulence generated from the flow field, and both the increase in flow velocity and parallel capacitance contribute to the reduction in discharge duration of the arc/glow phase. Therefore, the benefits brought about by the high-power spark discharge tend to diminish with the intensification of flow velocity.
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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".