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Record W2381359814

Computation of axisymmetric jet flow with Spalart-Allmaras turbulence model

2001· article· en· W2381359814 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.

Bibliographic record

VenueJournal of Propulsion Technology · 2001
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsTurbulenceJet (fluid)NozzleMechanicsRotational symmetryK-epsilon turbulence modelPhysicsFlow (mathematics)ComputationBoundary value problemExternal flowInternal flowFinite volume methodTurbulence modelingClassical mechanicsAerospace engineeringEngineeringMathematics
DOInot available

Abstract

fetched live from OpenAlex

A computational study for axisymmetric jet flow with Spalart Allmaras turbulence model was carried out.The second order finite volume method,fine unstructured grids and non reflecting boundary condition were used in solving the compressible N S equations.The numerical results are in good agreement with experimental data.It is demonstrated that the Spalart Allmaras turbulence model is suitable for numerical simulation of the axisymmetric jet flow and the sufficiently fine unstructured grids are helpful in obtaining the flow field details.In addition,it is found that,for under expanded jet flow,computation should be started from the internal upstream of the nozzle exit and its exit boundary conditioned should not be prescribed as sonic profile in this case.It is useful in understanding nozzle internal and external flow field and impinging jet parameter distribution.It is also helpful for optimal design of nozzle internal structure.

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 score0.355
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.006
GPT teacher head0.205
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