Numerical study of the impact of hydrogen addition, swirl intensity and equivalence ratio on methane-air combustion
Bibliographic record
Abstract
Abstract Hydrogen-blended fuel is a promising resource for future generations of gas turbine engines, due to its capability of reducing carbon-based emissions. This paper presents a numerical study to assess hydrogen-enriched combustion in a laboratory-scale burner operating at a high turbulence level and under lean and stoichiometric burning conditions. Moreover, a wide range of H 2 (up to 90 %) is used for enriching CH 4 -air combustion in combination with two different swirl levels. The results show that a high swirl intensity results in shorter flames, due to the increased turbulent intensity, which reduces the flame surface area and uniformness the reacting zone. Besides, increasing swirl intensity further increase flame temperature for a given H 2 -blended fuel. Overall, the results suggest that high swirl intensity in combination to lean mixtures is favorable when using H 2 -blended fuel with high H 2 concentrations. The simulation results also demonstrate that considering radiation heat loss is influential, as it yields a reduction of the outlet temperature by not less than 100 K, bringing down NO x emissions by half.
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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 | 0.000 |
| 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".