An Improved Soot Formation Model for 3-D Diesel Engine Simulations
Bibliographic record
Abstract
In this study, a phenomenological three-equation soot model was developed for modelling soot formation in diesel engine combustion based on considerations of acceptable computational demand and a qualitative description of the main features of the physics of soot formation. The model was developed based on that of Tesner et al. The model was implemented into the commercial STAR-CD CFD package and was demonstrated in the modelling of soot formation in a single-cylinder research version of Caterpillar 3400 series diesel engine with exhaust gas recirculation. Numerical results show that the new soot formulation overcomes most of the drawbacks in the existing soot models and demonstrates a robust and consistent behaviour with experimental observation. Compared to the existing soot models for engine combustion modelling, some distinct features of the new soot model include: no soot is formed at low temperature, minimal model parameter adjustment for application to different fuels, and there is no need to prescribe the soot particle size.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".