Injection Parameter Effects on a Direct Injected, Pilot Ignited, Heavy Duty Natural Gas Engine with EGR
Bibliographic record
Abstract
Pilot-ignited direct injection of natural gas fuelling of a heavy-duty compression ignition engine while using recirculated exhaust gas (EGR) has been shown to significantly reduce NOx emissions. To further investigate emissions reductions, the combustion timing, injection pressure, and relative delay between the pilot and main fuel injections were varied over a range of EGR fractions while engine speed, net charge mass, and oxygen equivalence ratio were held constant. PM emissions were reduced by higher injection pressures without significantly affecting NOx at all EGR conditions. By delaying the combustion, NOx was reduced at the expense of increased PM for a given EGR fraction. By reducing the delay between the pilot and main fuel injections at high EGR, PM emissions were substantially reduced at the expense of increased total hydrocarbon (tHC) emissions. In this research, no attempt was made to optimize the injector or combustion chamber for natural gas fuelling with EGR.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".