A numerical study on the effect of CO addition on extinction limits and NO<sub><i>x</i></sub>formation in lean counterflow CH<sub>4</sub>/air premixed flames
Bibliographic record
Abstract
The effect of CO addition on extinction and NO x formation in lean premixed counterflow CH4/air flames was investigated by numerical simulation. Detailed chemistry and complex thermal and transport properties were employed. A method that gradually switched off the initial reactions of NO formation from different routes was used to analyse the variation of NO formation mechanism. The results indicate that the addition of certain amount of CO increases the strain extinction limits and reduces the radiation extinction limits. As a result, the lean flammability limit of CH4/air premixed flame is extended to leaner side by the addition of CO. The formation of NO in a flame is increased with the addition of CO at a constant equivalence ratio. For an ultra-lean flame, the increase in the formation of NO is mainly because of the increase in the contribution from the NNH intermediate route, while for a near stoichiometric flame, this increase is mainly attributable to the rise in the contribution from the thermal route. With the fraction of added CO being gradually increased, the formation of NO2 in a flame first decreases and then increases at a given equivalence ratio. The addition of CO reduces the formation N2O in an ultra-lean flame, while affects little on the formation of N2O in a near stoichiometric flame.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".