An HCCI Engine Fuelled with Iso-octane and Ethanol
Bibliographic record
Abstract
This paper investigates Homogeneous Charge Compression Ignition (HCCI) combustion on an engine that is fuelled with ethanol, iso-octane, and ethanol/iso-octane. The engine is a four-stroke three cylinder indirect injection type diesel engine converted to a single cylinder HCCI operation. In order to clarify the effects of fuel chemistry on HCCI combustion, the trials were done at a constant engine speed, a fixed initial charge temperature and engine coolant temperature. The HCCI engine was fuelled with a lean mixture of air and fuel (ethanol, iso-octane or mixture of ethanol/iso-octane). The engine performance parameters studied here include indicated mean effective pressure (IMEP) and thermal efficiency. Heat-release rate (HRR) analysis was done to determine the effect of fuels on combustion on-set. The experimental results demonstrate that the addition of iso-octane to ethanol retards the on-set of combustion and subsequently leads to a reduction of the IMEP and thermal efficiency. For a particular fuel, the on-set of combustion depends closely on the intake charge temperature (as reported by several other researchers) and any increase in the initial charge temperature leads to advances in the on-set of combustion. Furthermore, the experimental results demonstrate that operating the engine on a lean charge reduces engine-out NOx emissions significantly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".