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Record W2335350218 · doi:10.2514/6.2012-3197

Hypersonic PIV in a Ludwieg Tube Wind Tunnel at Mach 5.9

2012· article· en· W2335350218 on OpenAlexaboutno aff
Marcus Casper, Peter Scholz, Jan Windte, Rolf Radespiel, Sven Scharnowski, Christian J. Kähler

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsnot available
Fundersnot available
KeywordsWind tunnelMach numberHypersonic speedAerospace engineeringHypersonic wind tunnelTube (container)Shock tubeAerodynamicsGeologyEngineeringMechanical engineeringShock wave

Abstract

fetched live from OpenAlex

The present work describes particle image velocimetry at M = 5.9 in the Hypersonic Ludwieg Tube Braunschweig on a generic space launcher model. The wind tunnel allows high quality flows as well as high repetition rates and, thus, it is suited for PIV-measurements. The PIV-measurements were performed with oil based tracer particles. Two different aerosol facilities, which differ basically in the position of the aerosol inlet, are described and compared. The first aerosol facility is close to the Laval nozzle whereas the second one is at the begin of the storage tube. The influences of both aerosol facilities to the quality of the PIV-measurements as well as to the safety of the wind tunnel are discussed. The results show that oil based PIV-measurements in a hypersonic blow down facility with a heated and pressurized storage tube are possible. The first aerosol facility close to the Laval nozzle results in an inhomogeneous tracer particle distribution with a low repeatability from run to run. The second aerosol facility at the begin of the storage tube enhances the distribution of the tracer particles inside the storage tube. The resulting tracer particle distribution is homogeneous as well as reproducible but the number of the tracer particles is reduced.

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 categoriesInsufficient payload (model declined to judge)
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 score0.753
Threshold uncertainty score1.000

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)0.0010.001

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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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 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

Citations5
Published2012
Admission routes1
Has abstractyes

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