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Record W2331265932 · doi:10.2514/6.2006-8089

A Nozzle Concept to Entrain Atmospheric Air for Ejector Operation

2006· article· en· W2331265932 on OpenAlexafffund
D. J. Cerantola, Jason Etele

Bibliographic record

Venue14th AIAA/AHI Space Planes and Hypersonic Systems and Technologies Conference · 2006
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNozzleInjectorEnvironmental scienceAerospace engineeringComputer scienceMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

The purpose of this paper is to describe a design methodology for a converging-diverging nozzle concept that takes advantage of the ejector effect. Incorporating the ejector effect into the nozzle design may be able to provide a more economical means for space transport as thrust increases so fuel quantity can be reduced. Methodology for the proposed nozzle requires three cross sections to be constrained in the diverging portion of the nozzle. The throat maintains axisymmetry with a choked flow condition. A gate is placed between the throat and outlet on the outer perimeter of the nozzle through which the nozzle geometry must pass; however, the shape is given freedom so that it does not have to remain axisymmetric. In doing so, a cutout can be created for air entrainment as the exhaust flow is restricted to flowing through the gate. Finally, the outlet is set to obtain desired rocket exhaust conditions. Viscous effects are accounted for by implementing Edenfield’s experimental displacement thickness correlation for turbulent boundary layers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.219
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2006
Admission routes2
Has abstractyes

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