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Record W2316681235 · doi:10.2514/6.2011-5826

Exchange Inlet Design for Enhanced RBCC Rocket-Air Mixing

2011· article· en· W2316681235 on OpenAlexaff
Tommy Yuen, Jason Etele

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsCarleton University
Fundersnot available
KeywordsRocket (weapon)Mixing (physics)InletAerospace engineeringEnvironmental scienceEngineeringPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

Rocket Based Combined Cycle [RBCC] engines have the potential to improve the specific impulse of conventional rockets through the use of atmospheric air. Much of the improvement depends on the ability of the rocket and air streams to mix. This paper examines the ability of a novel inlet design called the exchange inlet to promote mixing within an axisymmetric RBCC engine. Rocket exhaust is injected in an annular pattern starting from a circular throat while drawing air towards the centreline. Numerical simulations are performed focusing on the rocket and air interaction within the engine. The entrained air conditions produced by the exchange inlet are shown to be uniform and avoid significant regions of separated flow around the rocket flowpath. Despite a large variation of flow properties across the entrance of the mixing duct due to the difference between the rocket and air streams, five diameters downstream the flow is shown to be well mixed. The variation in temperature at this distance is reduced by 65% while the rocket exhaust is shown to have spread across the entire exit area (as indicated by species massfraction).

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.105
GPT teacher head0.280
Teacher spread0.175 · 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 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

Citations2
Published2011
Admission routes1
Has abstractyes

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