ANALYSIS OF NO FORMATION IN COUNTER-FLOW PREMIXED HYDROGEN-AIR FLAME
Bibliographic record
Abstract
Though hydrogen fuel reduces the carbon dioxide emission, it still produces NO x . However, gaps exist in the fundamental understanding of hydrogen-air combustion and the NO emission; most previous research has focused on the flames burning with mixture such as H 2 mixed with CH4, rather than pure H 2 flame. Here, a computational study is presented to investigate the stretch effect on NO formation in counter-flow premixed hydrogen-air flame. The simulation of premixed hydrogen flame was performed with OPPDIF code and UCSD chemical mechanism. Result indicates that the NO formation is affected by three factors: radical concentration, flame temperature, and residence time of reactants. The flame temperature, the reaction rate of NO, and the NO emission index all decrease when the stretch rate increases. Moreover, the formation of NO through thermal mechanism, NNH mechanism, and N 2 O mechanism is discussed, as well as the percentage of their contribution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".