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Record W2593459729 · doi:10.1615/tsfp5.1000

THE TURBULENT STATISTICS IN THE WAKE OF A SHORT STACK

2007· article· en· W2593459729 on OpenAlexaff
Muyiwa S. Adaramola, Donald J. Bergstrom, David S. Sumner

Bibliographic record

VenueProceeding of Fifth International Symposium on Turbulence and Shear Flow Phenomena · 2007
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsWakeTurbulencePhysicsBoundary layerMechanicsReynolds stressReynolds numberSkewnessWind tunnelBoundary layer thicknessStack (abstract data type)StatisticsMathematics

Abstract

fetched live from OpenAlex

The characteristics of the turbulent statistics along the wake centreline of a stack was experimentally studied in a low-speed wind tunnel using thermal anemometry. The cross-flow Reynolds number was ReD = 2.3×104, and the jetto- cross-flow velocity ratio was varied from R = 0 to 3. The stack was partially immersed in a flat-plate turbulent boundary layer, with a boundary layer thickness-to-stackheight ratio of δ/H = 0.5 at the location of the stack. The turbulent statistics are found to be strongly influenced by the value of R. The Reynolds shear stress and the triple correlation were strongly influenced by the local velocity gradient, especially for lower values of R within the stack wake and within the jet wake for higher values of R within the jet wake. The skewness and flatness factors indicated a strong deviation from a Gaussian distribution, which is evidence of the complexity of the flow.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.009
GPT teacher head0.233
Teacher spread0.223 · 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
Published2007
Admission routes1
Has abstractyes

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