Study of Dimethyl Ether Fuel Spray Characteristics and Injection Profile
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">The majority of transportation systems have continued to be powered by the internal combustion engine and fossil fuels. Heavy-duty applications especially are reliant on diesel engines for their high brake efficiency, power density, and robustness. Although engineering developments have advanced engines towards significantly fewer emissions and higher efficiency, the use of fossil-derived diesel as fuel sets a fundamental threshold in the achievable total net carbon reduction. Dimethyl ether can be produced from various renewable feedstocks and has a high chemical reactivity making it suitable for heavy-duty applications, namely compression ignition direct injection engines. Literature shows the successful use of DME fuels in diesel engines without significant hardware modifications. The lower energy density of DME calls for adjustments in injection parameters (such as injection pressure and duration) or modifications to the injector geometry to align with the energy levels found in diesel fuels. However, detailed direct comparisons between diesel and DME fuel injection characteristics over a wide testing range is lacking.</div><div class="htmlview paragraph">This study investigates the injection characteristics of DME and diesel fuels in a common rail fuel injection system using the Bosch tube method. It is demonstrated that this method can be effectively applied to measure DME fuel injection characteristics, albeit with some limitations in predicting injector closing delay. The research emphasizes the presence of hydraulic delay, resulting in a ratio of actual to commanded injection duration for DME between 1.5 to 2 under the testing conditions. The study finds that mass-based injection quantities for diesel and DME fuels are quite similar at matching conditions, although the lower heating value of DME results in lower energy-based injection quantities and thus fuel injection scheduling need to be adapted to compensate that. Furthermore, the paper offers valuable insights and suggestions for those considering the modification of diesel-operated engines into DME-operated engines.</div></div>
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".