A Partially Stratified-Charge Approach for Reduced Emissions From Gas Engines
Bibliographic record
Abstract
<div class="htmlview paragraph">Previous work has shown that a novel partially stratified-charge approach can be effective in extending the lean limit of combustion and reducing the exhaust emissions from natural gas-fueled engines. The new technique provides a relatively rich mixture in the vicinity of the spark plug, while maintaining an ultra-lean homogeneous charge in the main chamber area. In order to provide the near-stoichiometric mixture near the spark gap, a small quantity of "pilot" fuel is injected through the spark plug just prior to ignition. It has been found that for most operating conditions the required pilot fuel quantity is less than 5% of the total fuel charge. This paper also reports the results of some recent one-dimensional computer modelling in which the partially stratified-charge technique has been investigated over a range of air-fuel ratios. The results show that the improved combustion performance, particularly during ultra-lean operation, provides reduced levels of both fuel consumption and exhaust emissions.</div>
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".