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Record W4382048075 · doi:10.32920/23581587

Aerodynamic Analyses of Variable Geometry Asymmetric Supersonic Nozzles

2023· preprint· en· W4382048075 on OpenAlexaff
Bakisanani Sibanda

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsNozzleInviscid flowSupersonic speedMach numberAerodynamicsGeometryMechanicsSupersonic wind tunnelRange (aeronautics)Aerospace engineeringPhysicsEngineeringMathematics

Abstract

fetched live from OpenAlex

<p>The objective of the research is to develop a two dimensional supersonic nozzle with adaptable geometry that will allow a range of exit supersonic speeds ranging from Mach 1.29 to 4. The uniformity of the exiting air stream was the primary performance indicator. The asymmetric geometry is intended to be used in supersonic wind tunnels were uniform exit flow and a range of usable Mach numbers increases the utility of the tunnel. Numerical tools using the method of characteristics were developed using MATLAB to create an initial inviscid nozzle profile. Geometric constraints lead to the development of a two nozzle approach. It was found that an inviscid asymmetric nozzle geometry derived through the method of characteristics could be successfully adapted to create asymmetric nozzle profiles to include viscous effects. Numerical methods employing RANS solvers were required to adapt the asymmetric nozzle geometry. The uniformity of the exiting air stream was highly dependent on the downstream nozzle geometry. With effective geometry adaptation, the average variation of exiting nozzle velocity for a viscous flow was reduced to 1% and no less. </p>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.093
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.113
GPT teacher head0.370
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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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