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Record W4401942860 · doi:10.1115/gt2024-123900

A Parametric Study on NOx Emissions From Ammonia Containing Product Gas in Rich Quench Lean Combustion

2024· article· en· W4401942860 on OpenAlexaff
Ahmed Raslan, Silin Yang, Antoine Durocher, Felix Güthe, Jeffrey M. Bergthorson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadiative Heat Transfer Studies
Canadian institutionsNational Research Council CanadaMcGill University
Fundersnot available
KeywordsNOxCombustionWaste managementEnvironmental scienceAmmoniaProcess engineeringChemistryEngineering

Abstract

fetched live from OpenAlex

Abstract Due to climate change, there has been an increasing demand for fuels that can accelerate the transition away from fossil fuels to clean energy. Humidified product gas obtained from gasifying biomass is emerging as a promising candidate to replace natural gas, as it is composed of a gaseous mixture of hydrogen, steam, carbon monoxide and methane. However, the gasification process releases ammonia and other nitrogen bearing compounds into the product gas, resulting in substantial increases in nitric oxides, NOx, in the exhaust. As such, there has been a recent push to understand the underlying chemical kinetics that drive NOx formation in order to optimize gas turbines to mitigate emissions at the source. 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: equivalence ratio of the primary section (1.1 to 1.6), overall equivalence ratio (0.6 to 1.1), steam dilution (25% and 50% molar dilution), post flame residence time (0 to 75 ms) and recirculation from the post quench region to the primary section (0 and 40% by mass). Additionally, a benchmark CRN representing a Lean Burner (LB) as also developed. Results of 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, an overall lean to stoichiometric equivalence ratio is well suited to reduce emissions in highly humidified fuels, while for moderately humidified fuels it is preferable to operate in an overall slightly rich equivalence ratio. The difference observed is mainly due to the fact that, at high humidification and lean conditions, the temperature is favourable for the conversion of ammonia to nitrogen. While, at moderate humidification and rich conditions, NO reacts with ammonia in the reburn process. Finally, it is suggested that the incorporation of recirculation from the secondary section to the primary section of the RQL burner results in a broader low emission region, due to more favourable conditions for ammonia conversion to nitrogen in the primary section.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.273
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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