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Record W2519583914 · doi:10.2514/1.j055220

Reynolds and Mach Number Dependence of Hypersonic Blunt Body Laminar Near Wakes

2016· article· en· W2519583914 on OpenAlexafffund
W. Schuyler Hinman, Craig T. Johansen

Bibliographic record

VenueAIAA Journal · 2016
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCompute Canada
KeywordsMach numberReynolds numberLaminar flowMechanicsHypersonic speedFreestreamBoundary layerAdiabatic wallShock (circulatory)PhysicsAdiabatic processExpansion tunnelClassical mechanicsThermodynamicsTurbulence

Abstract

fetched live from OpenAlex

Laminar separation on the aftbody of an adiabatic circular cylinder was numerically investigated over a range of freestream Mach and Reynolds numbers using the free open-source program OpenFOAM. Simulations were performed assuming laminar, continuum, thermally perfect flow of nitrogen gas. Simulation predictions have been compared to various empirical correlations in the literature. Empirical formulations were presented for the pressure minimum location, separation location, and separation length on the cylinder aftbody. The effects of both Mach and Reynolds numbers on the separation location were examined by correcting for the change in viscosity across the shock wave. This was accounted for explicitly in the presented empirical formulations by deriving an expression for the viscosity change across the shock. A free-interaction theory was used to examine the wall-pressure distribution due to lip-shock formation on the aftbody. Over a range of Mach and Reynolds numbers, it was found that the profile of a free-interaction parameter was predictable and nearly Reynolds number and Mach number independent. This free-interaction parameter was a correlation between the properties at the onset of the interaction and the ensuing pressure rise. This provided a means to predict the lip-shock formation, provided the boundary-layer properties at the pressure minimum were known.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.015
GPT teacher head0.272
Teacher spread0.258 · 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 designTheoretical or conceptual
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

Citations22
Published2016
Admission routes2
Has abstractyes

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