Hydrocarbon Impacts on Diesel HCCI Engine Cycles
Bibliographic record
Abstract
Thermal efficiency and NOx emission comparisons are made between the homogeneous charge compression ignition (HCCI) and the conventional diesel cycles on a number of common-rail diesel engine platforms of high compression ratios with conventional diesel fuel and dimethyl ether as a surrogate fuel. The empirical studies have been conducted under independently controlled exhaust gas recirculation (EGR), intake boost, and exhaust backpressure. The energy relevance of the combustible substances such as carbon monoxide and hydrocarbon species in the engine exhaust has been evaluated quantitatively. However, the impact of the hydrocarbons produced during the HCCI cycles on the attainment of ultra low levels of NOx is less understood and it is unclear if the hydrocarbon species are a precursor to the ultra low NOx and also contribute in part to the NOx reduction. Therefore, the chemical impact of the hydrocarbon species on the NOx emission under low temperature combustion cycles has been examined with crank-angle resolved in-cylinder sampling techniques and fast-response emission analyzers. This paper intends to identify the major impacts of the hydrocarbons on the fuel efficiency and emissions of diesel HCCI cycles.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".