Entrainment effects on combustion and emission characteristics of turbulent non‐premixed ammonia/air and methane/air swirl flames through a developed perforated burner
Bibliographic record
Abstract
Abstract A fuel/oxidizer mixture can be burned using a colourless distributed combustion (CDC) process to obtain low emissions and homogeneous combustion. As an alternative way, a perforated burner can be designed to achieve homogeneous combustion and low emissions without changing the combustion performance by having entrainment effects on the combustion chamber. In this study, computational fluid dynamics (CFD) 3D modelling was performed in a perforated burner for ammonia/methane fuels in order to obtain the distributed regime and focus on the entrainment effects. In numerical analysis, the eddy break‐up was used as combustion model, k‐Ɛ as turbulence model, and P‐1 as radiation model. In this study, 10% and 20% entrainment rates were provided from the flame holder wall of the perforated burner. The effects of entrainment rates on temperature, velocity, and NO X emission values were examined. According to the results, when the entrainment rate was increased from 10% to 20%, the overall temperature values of ammonia and methane combustion slightly increased by approximately 1.0%, while on the other hand the maximum temperature levels in the near burner zone decreased by about 5.0%. The findings demonstrated that temperature and velocity distributions got more uniform and the flame zones became thinner. This provided a more colourless and invisible flame appearance. In this way, an improvement in the thermal field has been achieved. In conclusion, when the effect of the distributed regime on NO X emission levels was examined, it has been noted that entrainment effects enable the achievement of low emission levels (approximately 9.0%).
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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 | 0.000 |
| 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 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".