A Numerical Investigation of Natural Gas-Diesel Dual Fuel Engine Combustion and Emissions Using CFD Model
Bibliographic record
Abstract
A Numerical Investigation of Natural Gas-Diesel Dual Fuel Engine Combustion and Emissions Using CFD Model Yu Li Natural gas (NG)-diesel dual fuel engines have been highlighted for their fuel flexibility and high thermal efficiency comparable to diesel engines.However, the addition of NG to compression ignition diesel engines was reported to elongate ignition delay and to increase the emissions of carbon monoxide (CO), unburned methane (CH4), and nitrogen dioxide (NO2).Past research on dual fuel engines has focused on the experimental research on the engine performance, combustion process, and exhaust emissions.The research on detailed mechanism dominating the impact of CH4 on formation of CO and NO2 in cylinder, and the mechanism for CH4 to survive the combustion process and slip through the cylinder is limited.The examinations of these mechanisms require the simulation of dual fuel engine combustion using a CFD model coupled with chemical kinetic mechanism.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".