Chemical Reactivity Control of DME/Ethanol Dual Fuel Combustion
Bibliographic record
Abstract
The use of renewable fuels in place of conventional hydrocarbon fuels can minimize the carbon footprint of internal combustion engines. DME has been treated as a suitable surrogate to diesel fuel because of its high reactivity and soot-less combustion characteristics. The lower energy density of DME fuel demands a higher fuel supply rate to match the engine loads compared to diesel, which was achieved through prolonged injection duration and larger nozzle holes. When used as a pilot fuel to control the combustion behavior in a dual-fuel application, the fuel energy delivery rate becomes less critical allowing the use of a standard diesel common-rail injector for DME direct injection. In this work, the combustion of DME-Ethanol dual-fuel reactivity-controlled compression ignition was experimentally investigated. Compare with diesel, the high volatility of neat DME fuel can enhance its mixing with port injected fuel even under very early fuel injection timing, which is critical for reactivity-controlled compression ignition. On the other hand, the high chemical reactivity can enhance the combustion efficiency under high ethanol ratio conditions by enhancing ignition. Both factors make DME suitable as the direct injected fuel for the dual-fuel combustion process. The impact of DME pilot injection timing and DME/ethanol ratio on combustion characteristics was investigated under various engine load conditions. The results are then compared with diesel/ethanol dual fuel combustion, to discuss the impact of chemical reactivity of direct injected fuel on dual fuel combustion process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".