Large-eddy simulation of turbulent premixed hydrogen-air Bunsen flames using PCM-FPI combustion model
Bibliographic record
Abstract
Hydrocarbon fueled combustion offers an effective pathway to reducing harmful green-house gas emissions associated with carbon dioxide. Nevertheless, diffusion effects are known to be important in turbulent premixed flames involving hydrogen as a fuel, and the ability to predict these effects accurately will be fundamental to arriving at effective numerical combustion models needed for hydrogen flames. For perfectly premixed flames, the further away from the preferential diffusion neutral condition with an equivalence ratio, ?, of ?=1.8, the stronger its effects. In addition, diffusive thermal effect, for which the neutral condition is located at around ? = 0.8 manifest their contribution too. In this study, Large Eddy Simulation (LES) of turbulent premixed hydrogen-air flames is considered using the so-called Presumed Conditional Moment Flame Prolongation of Intrinsic low-dimensional manifold (PCM FPI) combustion model for a number of flames around the neutral condition towards both the lean and rich limits. Premixed Bunsen type flames with equivalent ratios in the range 0.8 ? ? ? 3.57 and for Reynolds numbers of Re = 20,000 and 40,000 are examined and the LES predictions are compared to available experimental data from previous studies. The comparisons illustrate the mutual influence of turbulence and diffusion phenomena on the turbulent f lame structure, burning rate, and flame height. In the lean limit with unstable diffusion conditions, overprediction of flame height and underprediction of turbulent burning rate are observed. Furthermore, the contribution of the instabilities on flame wrinkling decreases with turbulence intensity leading to reductions in these predicted errors. The opposite is true in the rich limit.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".