A Parametric Study on Nox Emissions From Ammonia Containing Product Gas in Rich Quench Lean Combustion
Bibliographic record
Abstract
Abstract Due to climate change, demand for fuels that can accelerate the transition from fossil fuels to clean energy has been increasing. Humidified product gas obtained from gasifying biomass is a promising candidate to replace natural gas. However, the gasification process releases nitrogen bearing compounds into the product gas, resulting in substantial increases in nitric oxides, NOx, in the exhaust. To mitigate these emissions at the source, a better understanding of the underlying kinetics is needed. In this study, a simplified CRN model for a gas turbine Rich-Quench-Lean (RQL) type combustor was developed in Cantera. The following parameters were investigated in this study: primary section equivalence ratio, overall equivalence ratio, steam dilution, postflame residence time and recirculation. Additionally, a benchmark CRN representing a Lean Burner (LB) as also developed. Results obtained from the CRN model suggest that, when comparing to LB, a RQL type combustor delivers up to a 75% reduction in emissions. Additionally, it was found that, for both the LB and RQL combustors, for temperatures between 1400-1600K it is preferable to burn lean, while for temperatures greater than 1800K it is preferable to operate at overall slightly rich equivalence ratios. This is because, at low temperatures and lean conditions, conversion of ammonia to nitrogen occurs readily. While, at moderate temperatures and rich conditions, NO reacts with ammonia to form Nitrogen in the reburn process. Finally, it was found that recirculation does not affect the emission minima, yet it allows for more flexible operational conditions.
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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 | 0.001 | 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".