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Record W2001755233 · doi:10.2514/1.12630

Hypervelocity Fuel/Air Mixing in Mixed-Compression Inlets of Shcramjets

2006· article· en· W2001755233 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

VenueAIAA Journal · 2006
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMechanicsRamjetMixing (physics)Duct (anatomy)Ignition systemFuel injectionCombustionInletMaterials scienceInjectorBackflowTurbulenceCombustorEnvironmental scienceAerospace engineeringThermodynamicsMechanical engineeringPhysicsChemistryEngineering

Abstract

fetched live from OpenAlex

This paper investigates the mixing of hydrogen fuel with air in the mixing duct of a mixed-compression shock-induced combustion ramjet (shcramjet) inlet. Mixing augmentation through the use of cantilevered ramp injector arrays on opposite shcramjet inlet walls is studied and the influence of relative array locations is quantified. Studies were undertaken numerically using the WARP code that solves the Favre-averaged Navier-Stokes equations closed by the Wilcox k-w turbulence model. Air-based mixing efficiencies of up to 0.58-0.68 were achieved with thrust potential losses less than that gained from high-speed fuel injection. Shocks created from the fuel injector structures play a major role in the mixing behavior of the fuel jets on the opposing side of the mixing duct. Chemically reacting studies verified for the correct selection of spanwise displacement of the fuel injectors, an air buffer created between the fuel and walls suppresses premature ignition while still allowing for a mixing efficiency of up to 0.46-0.54.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.429

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 head0.004
GPT teacher head0.188
Teacher spread0.184 · 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