Experimental investigation of soot formation characteristics on gasoline-diesel blend flames
Bibliographic record
Abstract
Stable laminar diffusion flames of different gasoline-diesel blends, namely G0, G20, G50, G80 and G100, were formed using a novel pre-vaporized liquid fuel burner system to investigate the soot formation characteristics in these flames. A two-dimensional line-of-sight attenuation technique was employed to acquire the twodimensional transmissivity images followed by an effective tomographic inversion algorithm for soot volume fraction distributions. Soot particles were also sampled using a rapid insertion probe for transmission electron microscope(TEM)image analysis to get soot morphology and primary particle size information. Test results show that, with the increase of gasoline to diesel, soot concentrations decrease to different levels at different heights, showing the stronger soot generation propensity of diesel. Soot particle sizes also decrease when more gasoline is added to diesel but primary soot particle diameters remain in the range from 14 nm, to 39, nm.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".