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Record W1781961764 · doi:10.1115/fedsm2002-31073

An Experimental Investigation of the Flow Downstream of a Low NOx Gas Turbine Nozzle

2002· article· en· W1781961764 on OpenAlexaff
Mohamed Boutazakhti, Ibrahim Yimer, Murray J. Thomson, Pierre E. Sullivan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsNational Research Council CanadaUniversity of Toronto
Fundersnot available
KeywordsNozzleSauter mean diameterInjectorMechanicsTurbineNOxTurbulenceMaterials scienceFlow (mathematics)Mixing (physics)Exhaust gasEnvironmental scienceNuclear engineeringCombustionMechanical engineeringEngineeringChemistryPhysicsWaste management

Abstract

fetched live from OpenAlex

Achieving rapid mixing is the main challenge to reducing NOx levels in non-premixed liquid fired gas turbine combustors. Multipoint lean direct injection (LDI) is among the techniques used to achieve low emissions and good mixing by injecting fuel in small amounts through different injection ports. This study looks at the flow characteristics of a nozzle using this concept. The Parker Hannifin injector used is a square matrix of nine simplex fuel nozzles. Phase Doppler particle analyzer was used to measure both the spray characteristics as well as the gaseous phase turbulence flow field. The average velocities, Reynolds stresses and the Sauter Mean Diameter were measured at a series of positions downstream of the nozzle exit, x3, ranging from 0.6 to 7 times the swirl cup diameters.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.509

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 head0.008
GPT teacher head0.190
Teacher spread0.182 · 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 designBench or experimental
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

Citations0
Published2002
Admission routes1
Has abstractyes

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