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Record W4286716166 · doi:10.2514/1.a35228

Experimental Investigation of Flow Interaction Dynamics in Supersonic Retropropulsion

2022· article· en· W4286716166 on OpenAlexaboutno aff
Nicholas Mejia, Bryan E. Schmidt

Bibliographic record

VenueJournal of Spacecraft and Rockets · 2022
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsnot available
Fundersnot available
KeywordsFreestreamSupersonic speedSchlierenMach numberJet (fluid)MechanicsPhysicsSchlieren imagingThrustNozzleOpticsChoked flowMaterials scienceTurbulenceReynolds number

Abstract

fetched live from OpenAlex

Supersonic retropropulsion experiments were performed using a 12.7-cm-diameter 70 deg sphere–cone body with a single jet in the center of the model with a 4:1-area-ratio Laval nozzle directed into a Mach 4 freestream. Data were acquired using high-speed schlieren imaging and direct axial force measurements. Spectral analyses of the total axial force, jet total pressure, and bow shock standoff distance were performed, resulting in the observation of three characteristic modes. For all tests, a dominant frequency in the axial force, independent of the jet and tunnel flow, of 1.9 kHz was observed, which was determined to be a structural vibration mode. A mode at 4.2 kHz in the axial force is observed to correspond to the motion of flow structures, suggesting a coupling between the jet flow and the freestream. A dependency on the presence of the jet and the selection of jet gas is shown for a 13.7 kHz mode, indicating it is acoustic in nature. Proper orthogonal decomposition on the schlieren image data is used to show that the flowfield structures in which dominant modes manifest are dependent on the thrust coefficient.

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)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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