A Numerical Investigation of Thermal Diffusion Influence on Soot Formation in Ethylene/Air Diffusion Flames
Bibliographic record
Abstract
Thermal diffusion, caused by temperature gradients, tends to draw lighter molecules to warmer regions and to drive heavier molecules to cooler regions of a mixture. The influence of thermal diffusion on soot formation in coflow laminar ethylene/air diffusion flames is numerically investigated in this paper. Detailed reaction mechanisms and complex thermal and transport properties are employed. The fully elliptic governing equations are solved. Radiation heat transfer from the flames is calculated by the discrete-ordinates method coupled to an SNBCK-based wide band model. A simplified two-equation soot model is used. The interactions between soot and gas-phase chemistry are taken into account. The thermal diffusion velocities are calculated according to the thermal diffusion coefficients evaluated based on multicomponent properties. The results show that thermal diffusion does affect soot formation in ethylene/air diffusion flames. Although the effect on soot formation in pure ethylene/air flame is not significant, the influence is enhanced if lighter species, such as helium, are added to the fuel or the air stream. The peak integrated soot volume fraction doubles if thermal diffusion is not taken into account in the simulation of the flame with helium addition to the air stream.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".