Cycle-to-Cycle NO and NOx Emissions From a HSDI Diesel Engine
Bibliographic record
Abstract
Engine-out NOx emissions from diesel engines continue to be a major topic of research interest. While substantial understanding has been obtained of engine-out (i.e., before any aftertreatment) NOx formation and reduction techniques, not least exhaust gas recirculation (EGR) which is now well established and fitted to production vehicles, much less data are available on cycle resolved NOx emissions. In this work, crank-angle resolved NO and NOx measurements have been taken from a high-speed light duty diesel engine at test conditions both with and without EGR. These have been combined with 1D data of exhaust flow, and this used to form a mass average of NO and NOx emissions per cycle. These results have been compared with combustion data and other emissions. The results show that there is a very strong correlation (R2 > 0.95) between the NOx emitted per cycle and the peak cylinder pressure of that cycle. In addition, the crank-angle resolved NO and NOx measurements also reveal that there is a difference in NO : NO2 ratio (where NO2 is assumed to be the difference between NO and NOx) during the exhaust period, with proportionally more NO2 being emitted during the blowdown period compared to the rest of the exhaust stroke.
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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 | 0.001 | 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".