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Record W2125952329 · doi:10.1115/imece2004-60125

Rapid Distortion of Homogeneous Turbulence Between Cylinders

2004· article· en· W2125952329 on OpenAlexaff
Babak Emami, Rui Liu, David S.‐K. Ting, M. David Checkel

Bibliographic record

VenueFluids Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of AlbertaUniversity of Windsor
Fundersnot available
KeywordsTurbulenceTurbulence kinetic energyPhysicsMechanicsWind tunnelDissipationKinetic energyK-epsilon turbulence modelDistortion (music)Classical mechanicsThermodynamics

Abstract

fetched live from OpenAlex

The effects of ‘half-full-half’ cylinders on the distortion of a turbulent flow are experimentally investigated. A single hot-wire anemometry unit is used to measure the stream-wise parameters of the flow. The cylinders are 15.2 cm (6 in) in diameter and 76.2 cm (30 in) in height installed in a closed loop wind tunnel with a 76.2 cm by 76.2 cm (30 in by 30 in) cross section. Turbulent flow with a nominal mean velocity of 7.6 m/s was generated by means of a perforated plate situated at the entrance of the wind tunnel. It was found that the mean velocity increases significantly as the flow passes through the contracting passage created by the cylinders, whereas the rms turbulence intensity decreases about 12% but shows an increase of up to 14% very close to the full cylinder. As the flow was distorted, the Kolmogorov length scales were elongated in the stream-wise direction, resulting in a decrease in the rate of turbulence decay which appears as a decrease in energy dissipation rate. The stream-wise integral length scales also increased due to the elongation of eddies in the stream-wise direction. Also, analysis of the turbulence fluctuating velocity in the frequency domain showed a redistribution of stream-wise turbulence kinetic energy from large to small scales during the distortion.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.176
Teacher spread0.169 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2004
Admission routes1
Has abstractyes

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