Effect of Renewable Diesel and Jet Blending Components on Combustion and Emissions Performance of a HCCI Engine
Bibliographic record
Abstract
Renewable diesel and jet blending components may be produced by hydrotreating waste fats and vegetable oils. The resulting hydrocarbon components are paraffinic in nature and free of sulfur and aromatics. An isomerization process may follow to improve the cold weather properties. The main differences between renewable diesel and jet blending components is that the jet blending components are more volatile, have a lower cetane number and a much lower cloud point. In this study, different percentages of hydrotreated renewable diesel and jet components were blended into an ultra-low sulfur diesel (ULSD) fuel and their effect on homogeneous charge compression ignition (HCCI) combustion and emissions performance was investigated. The experiments were conducted using a Co-operative Fuel Research (CFR) engine coupled to an eddy-current dynamometer. The percentage of renewable blending components was varied from 0 to 100%. HCCI combustion and emissions data was collected at a single relative air/fuel ratio (λ) = 1.2 and engine speeds of 900 and 1200 rpm for each fuel blend. The experimental results indicate that the renewable diesel and jet blending components increased the heat release during low temperature stage and reduced the auto-ignition temperature compared to the ULSD fuel, which tended to advance the combustion phasing at a fixed compression ratio. The thermal efficiency was not significantly affected by renewable jet and diesel blends up to 10% by volume, but the renewable jet improved the thermal efficiency while the renewable diesel blends deteriorated thermal efficiency for higher percentage blends. The renewable jet fuel component improved unburned hydrocarbon (HC) emissions, but the renewable diesel component did not have a significant effect on HC emissions. Both renewable fuel components reduced CO emissions at a fixed compression ratio, but there was not a clear trend for CO emissions at the optimal thermal efficiency condition when renewable components were blended with the ULSD fuel. The NOx emissions were extremely low and did not show a clear trend as the percentage of renewable blending components increased.
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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 | 0.000 | 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) | 0.000 | 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".