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Record W4232264958 · doi:10.1115/gt2008-51209

Improving the Performance of a Bent Ejector With Inlet Swirl

2008· article· en· W4232264958 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor Technologies Research
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInjectorNozzleBent molecular geometryInletTube (container)MechanicsMaterials scienceWork (physics)Gas turbinesBack pressureFlow (mathematics)Overall pressure ratioMechanical engineeringPhysicsEngineeringGas compressorComposite material

Abstract

fetched live from OpenAlex

Ejectors are commonly employed in gas turbine exhaust systems for reasons such as space ventilation and IR suppression. Ejectors may incorporate bends in the geometry for various reasons. Studies have shown that the bend has a deteriorating effect on the performance of an ejector. This work was aimed to investigate the effect of exhaust gas swirl on improving the performance of a bent ejector. Four short oblong ejectors with different degrees of bend in the mixing tube and four swirl conditions were tested in this study. The primary nozzle, in all the cases, was composed of a circular to oblong transition. Testing was performed at ambient and hot primary flow with 0, 10, 20 and 30° swirl angles. It was observed that the swirl had a strong affect on the performance of a bent ejector. Improvement of up to 55, 96 and 180% was obtained in the pumping ratio, pressure rise and total efficiency respectively with a 20° swirl in the exhaust gas.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.160

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 head0.013
GPT teacher head0.209
Teacher spread0.196 · 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

Quick stats

Citations1
Published2008
Admission routes2
Has abstractyes

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