Ignition Improvement of Premixed Methane-Air Mixtures by Distributed Spark Discharge
Bibliographic record
Abstract
In order to improve the fuel economy for future high-efficiency spark ignition engines, the use of advanced combustion strategies with an overall lean and/or exhaust gas recirculation diluted cylinder charge is deemed to be beneficial, provided a reliable ignition process available. In this paper, experimental results of igniting methane-air mixture by means of capacitive coupled ignition and multi-coil distributed spark ignition are presented. It is found that with a conventional spark plug electrode configuration, increase of spark energy does not proportionally enhance the ignition flame kernel development. The use of capacitive coupled ignition to enhance the initial transient power resulted in faster kernel growth compared to the conventional system. The distribution of the spark energy across a number of spark gaps shows considerable benefit. The multi-coil distributed spark ignition with multiple low energy sparks produces faster early flame kernel growth than that of a single high energy spark with the same amount of total energy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".