Influence of Aromatic Type on Diesel Emissions Investigated by Blending Narrow-Cut Components and Pure Hydrocarbons Into a Base Fuel
Bibliographic record
Abstract
Abstract The influence of fuel aromatic content and type on the exhaust emissions from a heavy-duty diesel engine were investigated by blending predetermined amounts of aromatic compounds with a known chemical structure into a low-aromatic base fuel. Seven test fuels were blended with constant cetane numbers and densities, but with mono-, di-, and tri-aromatic contents ranging from 10 to 30%, 0 to 10%, and 0 to 8%, respectively. The engine experiments were run using the AVL eight-mode steady-state simulation of the EPA transient test procedure. The results show that fuel total aromatic content or type did not significantly affect the engine’s PM emissions. NOx emissions, however, increased by 4.3% as the fuel mono-aromatic content increased from 10 to 30%.
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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".