Speciation Analysis of Light Hydrocarbons and Hydrogen Production During Diesel Low Temperature Combustion
Bibliographic record
Abstract
The simultaneous reduction in engine-out NOx and soot emissions with diesel low temperature combustion (LTC) is generally accompanied by high levels of hydrocarbon (THC) and carbon monoxide (CO) emissions in the exhaust. To achieve clean diesel combustion in terms of low regulated emissions (NOx, soot, THC, and CO), the exhaust combustibles must be dealt with the exhaust aftertreatment (typically a diesel oxidation catalyst). In this work, engine tests were performed to realize LTC on a single-cylinder common-rail diesel engine up to 12 bar IMEP. A single-shot fuel injection strategy was employed to push the diesel cycles into LTC with exhaust gas recirculation (EGR). The combustibles in the exhaust were generally found to increase with the LTC load and were observed to be a function of the overall equivalence ratio. A Fourier transform infrared (FTIR) spectroscopy analysis of light hydrocarbon emissions found methane to constitute a significant component of the hydrocarbon emissions under the tested LTC conditions. The relative fraction of individual species in the hydrocarbons also changed, indicating a richer combustion zone and a reduction in engine-out THC reactivity. The hydrogen production was found to correlate consistently with the CO emissions, largely independent of the boost pressure or engine load under the tested LTC conditions. This research intends to identify the major constituents of the THC emissions and highlight the possible impact on exhaust aftertreatment.
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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 | 0.001 |
| 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".