Investigating renewable fuel combustion I: comparative simulations of a diesel engine fuelled with n‐c<sub>12</sub>alkane and n‐c<sub>18</sub>fatty acid‐derived liquid‐property fuel
Bibliographic record
Abstract
Biodiesel oil and esters, fuels of renewable origin, may be used in unmodified diesel engines. They are nevertheless likely to produce NOx and carbon deposits, but the associated chemical and physical fundamentals are still not well understood. This paper deals with simulations of a single‐cylinder research diesel engine using virtual fuels which show the effects of different liquid properties in a cumulative manner. These properties are representative of conventional fuel and fatty‐acid bio‐oils (including biodiesel‐esters). The aim is to investigate the impact on the in‐cylinder processes of each property change from a conventional alkane to a fatty acid. Critical temperature, which makes fatty‐acid biodiesels much less volatile than conventional diesel, has the biggest impact. It strongly delays the release of fuel in the gas phase and extends the combustion time. The effects of droplet break‐up, heating and density of the droplets are marginal. Globally, a longer survival time of droplets tends to spread the combustion and rich mixture zones.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".