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Record W4401942686 · doi:10.1115/gt2024-125090

Micro-Mixing Combustion: Experimental Assessment of the Impact of Fuel Preheating on Combustion Stability

2024· article· en· W4401942686 on OpenAlexaff
Xavier Bellavance, Alexandre Landry-Blais, Jean‐Sébastien Plante, Mathieu Picard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCombustionMixing (physics)Materials scienceNuclear engineeringStability (learning theory)MechanicsComputer scienceEngineeringChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract Micro-mixing combustion is a promising technology in the field of gas turbine combustion because of its safeness against autoignition and flashback while having NOx emissions near premixed levels. This technology is especially well suited for the combustion of hydrogen because of its high reactivity. Because of the potential safety and low NOx emissions of micro-mixing combustion, there is the desire to use this technology with a larger fuel spectrum. However, using micro-mixing technologies, stable combustion is limited to reactive fuels such as hydrogen or high hydrogen fuel blends. Our previous work demonstrated excellent combustion stability with high inlet temperatures up to 1000K with hydrogen, propane, natural gas or Jet fuel A1 as fuels. However, using propane as fuel, stable combustion was limited to inlet temperatures higher than 600K. In this paper, the impact of preheating the fuel prior to its injection on the combustion stability is assessed using propane as fuel because of its stability limitation. For micro-mixing injector configuration discussed in this publication, preheating fuel prior its injection allowed to decrease dynamic instability magnitude under 3 dB for most of the unstable data points (Sound pressure level variation at instability dominant frequency). Those stability gains were obtained while achieving similar levels of NOx emissions. Thermoacoustic instabilities were then linked to observed flame positions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.297
Teacher spread0.280 · 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 designSimulation or modeling
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

Citations3
Published2024
Admission routes1
Has abstractyes

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