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Record W2112521470 · doi:10.1051/epjconf/20122501056

An experimental setup for visualizations and measurements on free hypersonic jets

2012· article· en· W2112521470 on OpenAlexaboutno aff
M. Belan, Mohsen Mirzaei, S. De Ponte, Daniela Tordella

Bibliographic record

VenueEPJ Web of Conferences · 2012
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsnot available
Fundersnot available
KeywordsMach numberHypersonic speedJet (fluid)PhysicsNozzlePiston (optics)Aerospace engineeringRange (aeronautics)MechanicsSupersonic speedIonizationOpticsComputational physicsEngineering

Abstract

fetched live from OpenAlex

The free hypersonic jets can be found in several technological applications and even in astrophysical observations. This article is mainly devoted to explain an experiment about visualizations and measurements on free hypersonic jets extending on length scales in the order of hundreds of initial diameters and traveling in a medium not necessarily made of the same gas of the jets. The experiments are performed by means of special facilities where the jet Mach numbers and the jetto-ambient density ratios can be set independently of each other, what permits the investigation of a wide parameters range in the relevant physics. The Mach number of the jets ranges from 5 to 20 and the jet-to ambient density ratio, which plays an important role in the jets morphology, can be set from 0.1 up to values exceeding 100. The present setup produces the jets by means of a fast piston system (for high Mach numbers) or injection valves (for low Mach numbers), both coupled with de Laval nozzles. The visualizations and measurements are based on the electron beam technique: the jets are weakly ionized, then a fast CMOS camera captures images that are analyzed by image processing techniques. A sample of the results obtained by this experimental system is included at the end of this work.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.327

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 head0.046
GPT teacher head0.285
Teacher spread0.240 · 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 designSimulation or modeling
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

Citations3
Published2012
Admission routes1
Has abstractyes

Explore more

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