Three-Dimensional Computational Fluid Simulation of Diesel and Dual Fuel Engine Combustion
Bibliographic record
Abstract
A 3D computational fluid dynamics model with a reduced detailed chemical kinetics of the combustion of diesel and methane fuels is developed while considering turbulence during combustion to simulate the mixture flow, formation, and combustion processes within diesel and diesel/methane dual fuel engines having swirl chambers. The combustion characteristics of the pilot injection into a small prechamber are also investigated. Modeled results were validated by a group of corresponding experimental data. The spatial and temporal distributions of the mixture temperature, pressure, and velocity under conditions with and without liquid fuel injection and combustion are compared. The effects of engine speed, injection timing, and the addition of carbon dioxide on the combustion process of dual fuel engines are investigated. It is found that in the absence of any fuel injection and combustion, the swirl center is initially formed at the bottom-left of the swirl chamber, and then moved up with continued compression in the top-right direction toward the highest point. The swirling motion within the swirl and main combustion chambers promotes the evaporation of the liquid pilot and the combustion processes of diesel and dual fuel engines. It was observed that an earlier autoignition can be obtained through injecting the pilot fuel into the small prechamber compared with the corresponding swirl chamber operation. It is to be shown that reduced engine emissions and improved thermal efficiency can be achieved by a two-stage homogenous charge compression ignition combustion.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".