MétaCan
Menu
Back to cohort
Record W2009388849 · doi:10.1115/gt2007-27851

Effect of a Bend on the Performance of an Oblong Ejector

2007· article· en· W2009388849 on OpenAlexafffund
Asim Maqsood, A. M. Birk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNozzleInjectorMechanicsMixing (physics)Mach numberInletTube (container)Flow (mathematics)Mass flowRADIUSMaterials scienceMass flow rateMechanical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

This paper presents the results of an experimental study on the performance of oblong ejectors with a bend in the mixing tube. In the aerospace industry, space limitations can lead to the design of exhaust ducts of oblong cross section. These ducts can also include ejectors for engine space ventilation or exhaust cooling or infrared signature suppression. In some cases these systems require bends after the primary driving nozzle. Each ejector consisted of a nozzle and a constant area mixing tube. A series of bent mixing tubes with the same radius of curvature was tested and the results were compared with the baseline straight ejector. A hot flow wind tunnel was used to provide the primary air flow at temperatures up to 450°C and mass flow rates up to 2 kg/s. Ambient air from the surroundings was allowed to enter the mixing tubes and mix with the primary air issuing from the primary nozzle. Velocity, pressure and temperature measurements were taken upstream of the nozzle, at the mixing tube inlet and at the exit of the mixing tube. Seven-hole probes were used to resolve the velocity vector at the exit of the mixing tube to identify large-scale flow structures. Mass flow ratio, temperature distribution and the losses in the different ejectors were compared to estimate the degradation of ejector performance with the degree of bend. Significant reduction in the performance was observed with the degree of bend in the ejector.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.091

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 head0.005
GPT teacher head0.218
Teacher spread0.213 · 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

Citations7
Published2007
Admission routes2
Has abstractyes

Explore more

Same topicRefrigeration and Air Conditioning TechnologiesFrench-language works237,207