Modelling the Effect of Pressure on Soot Formation in Varying-Pressure Coflow Laminar Diffusion Flames
Bibliographic record
Abstract
Soot formation from combustion devices is a health and environmental concern. Therefore, a comprehensive understanding of soot is a necessity; however, due to its complexity, it is poorly understood, especially with high-pressure combustion. In this thesis, a detailed numerical soot formation code, CoFlame, has been successfully utilized to model varying-pressure coflow laminar diffusion flames. The results of this thesis are divided into two sections; first, an investigation of the impact of a novel pressure-based reaction rate of acetylene addition in the Hydrogen- Abstraction-Carbon-Addition (HACA) mechanism on soot formation in varying pressure flames is addressed in chapter 4. Second, an assessment of the influence of pressure on the formation of recirculation zones along the centerline of the flame and the subsequent effect of the flow field on soot formation in elevated-pressure coflow diffusion flames is addressed in chapter 5.
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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) | 0.000 | 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 | 0.000 |
| 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".