Postinjection Strategy for the Reduction of the Peak Pressure Rise Rate of Neat n-Butanol Combustion
Bibliographic record
Abstract
Enhanced premixed combustion of neat butanol in a compression ignition engine can have challenges with regards to the peak pressure rise rate (PRR) and the peak in-cylinder pressure. It was proposed to utilize a butanol postinjection to reduce the peak PRR and the peak in-cylinder pressure while maintaining a constant engine load. Postinjection timing and duration sweeps were carried out with neat n-butanol in a compression ignition engine. The postinjection timing sweep results indicated that the use of an early butanol postinjection reduced the peak PRR and the peak in-cylinder pressure and it was observed that there was an optimal postinjection timing range for the maximum reduction of these parameters. The results also showed that an early postinjection of butanol increased the nitrogen oxide emissions, and a Fourier transform infrared spectroscopy (FTIR) analysis revealed that late postinjections increased the emissions of unburned butanol. The postinjection duration sweep indicated that the peak PRR was significantly reduced by increasing the postinjection duration at constant load conditions. There was also a reduction in the peak in-cylinder pressure. Measurements with a hydrogen mass spectrometer showed that there was an increased presence of hydrogen in the exhaust gas when the postinjection duration was increased but the total yield of hydrogen was relatively low. It was observed that the coefficient of variation for the indicated mean effective pressure was significantly increased and that the indicated thermal efficiency was reduced when the postinjection duration was increased. The results also showed that there were increased nitrogen oxide, carbon monoxide, and total hydrocarbon (THC) emissions for larger postinjections. Although the use of a postinjection resulted in emission and thermal efficiency penalties at medium load conditions, the results demonstrated that the postinjection strategy successfully reduced the peak PRR, and this characteristic can be potentially useful for higher load applications where the peak PRR is of greater concern.
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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 | 0.001 |
| 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".