Modeling of Air-Fuel Mixing in a Two-Stroke Direct Injection Engine
Bibliographic record
Abstract
<div class="htmlview paragraph">This paper presents a numerical study on air-fuel mixing in a two-stroke direct injection spark ignition engine under homogeneous operation. The simulated engine is loop scavenged and uses an outwardly opening swirl injector. A generic mesh-snapping algorithm is developed to enable the moving piston to snap through transfer ports with complicated geometry. A spray model based on Linear Instability Sheet Atomization is used to describe the primary breakup of fuel sprays, and the initial rotational velocity of the conical sheet is determined from a CFD simulation of the nozzle internal flow. A wall film model accounting for the effect of contacting area is also developed to avoid the severe grid-dependence of the original film model in KIVA. Comparisons between simulations and experiments were made for sprays in quiescent ambient conditions, and a good agreement of the spray characteristics was obtained. The simulations were performed for four different injection timings. The model was shown to be capable to predict engine-out unburned hydrocarbon emission. It was also found that the mixture preparation around the spark plug is directly related to the engine-out emission, and leaner mixture tends to yield higher engine-out emission.</div>
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".