Influence of pressure on near nozzle flow field and soot formation in laminar co-flow diffusion flames
Bibliographic record
Abstract
Soot formation from combustion devices, which tend to operate at high pressure, is a health and environmental concern, thus investigating the effect of pressure on soot formation is important. While most fundamental studies have utilised the co-flow laminar diffusion flame configuration to study the effect of pressure on soot, there is a lack of investigations into the effect of pressure on the flow field of diffusion flames and the resultant influence on soot formation. A recent work has displayed that recirculation zones can form along the centreline of atmospheric pressure diffusion flames. This present work seeks to investigate whether these zones can form due to higher pressure as well, which has never been explored experimentally or numerically. The CoFlame code, which models co-flow laminar, sooting, diffusion flames, is validated for the prediction of recirculation zones using experimental flow field data for a set of atmospheric pressure flames. The code is subsequently utilised to model ethane-air diffusion flames from 2 to 33 atm. Above 10 atm, recirculation zones are predicted to form. The reason for the formation of the zones is determined to be due to increasing shear between the air and fuel steams, with the air stream having higher velocities in the vicinity of the fuel tube tip than the fuel stream. This increase in shear is shown to be the cause of the recirculation zones formed in previously investigated atmospheric flames as well. Finally, the recirculation zone is determined as a probable cause of the experimentally observed formation of a large mass of soot covering the entire fuel tube exit for an ethane diffusion flame at 36.5 atm. Previously, no adequate explanation for the formation of the large mass of soot existed.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".