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Record W2312692450 · doi:10.2514/6.2004-2621

Air Ejector Pumping Enhancement Through Pulsing Primary Flow

2004· article· en· W2312692450 on OpenAlexaff
P. J. Vermeulen, Venkataramanayya Ramesh, Guang Yao Meng, Daniel Miller, Niel Domel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInjectorMaterials scienceFlow (mathematics)Primary (astronomy)Automotive engineeringMechanicsMechanical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

Improving the performance of an ejector is a flow control problem. Passive methods such as changing the geometry of the mixing tube showed that, for a simple mixing tube geometry of a concentric cone-tube combination, the diameter of the tube had to be at least 4 times the diameter of the primary nozzle. Thus for a 5.13 mm dia. primary jet, a 22.7 mm dia. tube was 27% better than a 17.41 mm dia. tube. A standard Venturi mixing tube with 17.41 mm dia. throat was 100% better. Also the shape of the entrance cone had only a little effect and could be substituted by other shapes. A tube without an entrance shape was found to be still reasonably efficient. Both experiments and Computer Fluid Dynamics (CFD) analysis show that pulsing the primary jet flow, an active method of flow control, improved ejector performance. The physics of this improvement has been discussed. Pumping effectiveness of the ejector was found to be proportional to the square of the pulsation strength. The details of the many pulsators tested are discussed. The majority of the improvement appears to be due to the initial toroidal vortex the pulsation produces. The improvement was strongest at 127-131 Hz, less than half the fundamental frequency of 746 Hz of the system. The pumping effectiveness increased by up to 4.5 times that for a steady jet. Different types of pulse shapes tested indicate that a sinusoidal pulse superimposed on a steady flow is very efficient. For pulses which have only positive pulse velocities, a narrow pulse was more efficient. The data also showed that a strong synthetic jet actuator gave ejector performance as good as a pulsed jet with primary flow.

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: none
Teacher disagreement score0.721
Threshold uncertainty score0.621

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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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

Citations9
Published2004
Admission routes1
Has abstractyes

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