Hydrocarbon impact on NO <i> <sub>x</sub> </i> survivability during diesel low-temperature combustion cycles
Bibliographic record
Abstract
Low-temperature combustion (LTC) cycles are inherently inclined to produce higher amounts of combustibles because the burning of a homogeneous cylinder charge that is lean and/or exhaust gas diluted is closer to the non-combustion regions (flame-out limits). However, the impact of the hydrocarbons produced during the LTC cycles on the attainment of ultra-low levels of nitrogen oxides (NO x ) is less understood, and it is unclear whether the hydrocarbon species are a precursor to the ultra-low NO x and also contribute in part to the NO x reduction. Therefore, the impact of the hydrocarbon emissions on the NO x emission of the LTC cycles has been empirically investigated on a number of common-rail diesel engine platforms of high compression ratios. The empirical studies have been conducted under independently controlled exhaust gas recirculation, intake boost, and exhaust back pressure. The survivability of NO x under the compression and combustion processes has been presented in the context of the quasi-steady exhaust NO x and the effect of the hydrocarbons on the NO x survivability has been quantified. The chemical impact of the hydrocarbon species on the NO x emission under LTC cycles has been examined with crank-angle-resolved in-cylinder sampling techniques and fast-response emission analysers. Furthermore, the ratio of nitric oxide to nitrogen dioxide under the LTC cycles has been quantified and compared with that in conventional diesel combustion. This paper intends to identify the major impacts of the hydrocarbons on the NO x emission of diesel LTC cycles.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".