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Record W2889015751 · doi:10.1115/gt2018-75647

Blowoff and Reattachment Dynamics of a Linear Multi-Nozzle Combustor

2018· article· en· W2889015751 on OpenAlexaff
Wilson Kwong, Adam M. Steinberg

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNozzleCombustorMechanicsTuyereDischarge coefficientMaterials scienceParticle image velocimetryFlow (mathematics)Planar laser-induced fluorescenceEntrainment (biomusicology)ChemistryOpticsPhysicsCombustionAcousticsTurbulenceThermodynamicsLaserLaser-induced fluorescence

Abstract

fetched live from OpenAlex

This paper describes the coupled flow and flame dynamics during blowoff and reattachment events in a combustor consisting of a linear array of five interacting nozzles using 10 kHz repetition-rate OH planar laser induced fluorescence and stereoscopic particle image velocimetry. Steady operating conditions were studied at which the three central flames randomly blew-off and subsequently reattached to the bluff-bodies. Transition of the flame from one nozzle was rapidly followed by transition of the other nozzles, indicating cross-nozzle coupling. Blow-off transitions were preferentially initiated in one of the off-center nozzles, with the transition of subsequent nozzles occurring in a random order. Similarly, the center nozzle tended to be the last nozzle to reattach. The blowoff process of any individual nozzle was similar to that for a single bluff-body stabilized flame, though with cross-flame interactions providing additional means of re-stabilizing a partially extinguished flame. Subsequent to blowoff of the first nozzle, the other nozzles underwent similar blowoff processes. Flame reattachment was initiated by entrainment of a burning pocket into a recirculation zone, followed by transport to the bluff-body; the other nozzles subsequently underwent similar reattachment processes. Several forms of cross-nozzle interaction that can promote or prevent transition are identified. Furthermore, the velocity measurements indicated that blowoff or reattachment of the first nozzle during a multi-nozzle transition causes significant changes to the flow fields of the other nozzles. It is proposed that a single nozzle transition redistributes the flow to the other nozzles in a manner that promotes their transition.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score0.321

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 head0.010
GPT teacher head0.240
Teacher spread0.230 · 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

Citations7
Published2018
Admission routes1
Has abstractyes

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