LES of a Hydrogen-Enriched Lean Turbulent Premixed Flame
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The application of large-eddy simulation (LES) to the prediction of H2-enriched lean methane-air turbulent premixed combustion is considered. A presumed conditional moment (PCM) subfilter-scale combustion model is coupled with the flame prolongation of intrinsic low-dimensional manifold (FPI) chemistry tabulation technique. The LES and PCM-FPI modelling procedures are then applied to the prediction of laboratory-scale axisymmetric Bunsen-type turbulent premixed flames. Both premixed methane-air and H2-enriched methane-air flames are considered and the predicted solutions are examined and compared to available experimental data. The enriched flame has 20% H2 in terms of mole fraction and lies in the methane-dominated regime. The capability of the LES model to predict the observed behaviour is examined. Hydrogen-hydrocarbon fuel blends appear to be a promising option to synergistically pave the way toward pure hydrogen-based combustion systems while alleviating green-house gas and pollutant emissions related to fossil fuel combustion. The possibility of using hydrogen-enriched hydrocarbon fuels as a means for enabling greater stability of lean premixed flames with significantly reduced emissions of nitrogen oxides is also very appealing. While promising, the wide-spread application of hydrogen-enriched hydrocarbon fuels in practical premixed combustion devices has been limited by an incomplete understanding of hydrogen-enriched combustion. In particular, the current understanding, in terms of theoretical and computational models, is unable to fully explain the experimental observations for such flames.
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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 | 0.001 | 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 | 0.001 | 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) | 0.000 | 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 it