An Enabling Study of Neat n-Butanol HCCI Combustion on a High Compression-ratio Diesel Engine
Bibliographic record
Abstract
This work investigates the benefits and challenges of enabling neat n-butanol HCCI combustion on a high compression ratio (18.2:1) diesel engine. Minor engine modifications are made to implement n-butanol port injection while other engine components are kept intact. The impacts of the fuel change, from diesel to n-butanol, are examined through steady-state engine tests with independent control of the intake boost and exhaust gas recirculation. As demonstrated by the test results, the HCCI combustion of a thoroughly premixed n-butanol/air lean mixture offers near-zero smoke and ultralow NOx emissions even without the use of exhaust gas recirculation and produces comparable engine efficiencies to those of conventional diesel high temperature combustion. The test results also manifest the control challenges of running a neat alcohol fuel in the HCCI combustion mode. The rapid heat release and the resultant excessive pressure rise rates prevent engine operation at higher loads, while a minimum level of intake boost is required to avoid misfire incidences at lower loads. With the use of intake boost and exhaust gas recirculation, clean and efficient n-butanol HCCI combustion is achieved from engine low load up to 10bar IMEP.
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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 | 0.000 | 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".