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High-Turbulent Gas Screen in a Supersonic Nozzle

2000· article· en· W2063018937 on OpenAlexaboutno aff
В. П. Лебедев, В. В. Леманов, В. И. Терехов

Bibliographic record

VenueHeat Transfer Research · 2000
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleTurbulenceMechanicsCompressibilityAdiabatic processDischarge coefficientSupersonic speedMaterials scienceFlow (mathematics)PhysicsPressure gradientThermodynamicsAccelerationClassical mechanics

Abstract

fetched live from OpenAlex

An effect of initial turbulence of the flow on characteristics of a gas screen in the Laval nozzle is studied experimentally. The effect of flow acceleration on turbulence behavior is considered, the distribution of turbulence is compared with the theory of rapid transformation. The distribution of static pressure, adiabatic temperature of a wall, coefficient of recovery, and the parameter of gas screen efficiency along the nozzle length is measured. An integral method is suggested for calculation of the efficiency of screen cooling on the calculated flow modes in the nozzle. The method allows for a longitudinal pressure gradient, compressibility, nonisothermicity and degree of flow turbulence.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.059
GPT teacher head0.317
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; both teacher heads agree on what is shown here.

Study designOther design
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
Published2000
Admission routes1
Has abstractyes

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