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Record W2595424503 · doi:10.1615/tsfp8.2100

SQUARE-FRACTAL-ELEMENT GRID-GENERATED TURBULENCE

2013· article· en· W2595424503 on OpenAlexaff
R. Jason Hearst, Philippe Lavoie

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSquare (algebra)FractalTurbulenceGridSquare tilingComputer sciencePhysicsMathematicsGeometryMechanicsMathematical analysis

Abstract

fetched live from OpenAlex

A new square-fractal-element grid was designed to investigate the decay of turbulent kinetic energy far downstream of a fractal geometry. The grid is composed of several square fractal elements mounted to a background mesh. Measurements of the decay of turbulent kinetic energy at ReL0 = 57,000 in the region 23 ≤ x/L0 ≤ 45, where LO is the size of the largest element in the grid, yield a power-law decay of the form 〈q2〉 ~ (x − x0)m with m = −1.39. This result agrees with values of m previously reported for regular grids, while it contrasts with m ~ −2.5 previously reported for space-filling square fractals (Valente & Vassilicos, 2011). It is also observed that Richardson-Kolmogorov scaling, both for the spectra and for Cε, approximately describes the turbulence produced by this new grid. This is also in agreement with previous regular grid experiments, but contrasts with previous fractal grid experiments. Previous fractal studies have been conducted in the region x/L0 < 20, and thus the contrasting results are attributed primarily to the difference in measurement region relative to L0 of the present and previous studies.

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)0.001
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
Metaresearch0.0000.001
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)0.0010.000

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 head0.006
GPT teacher head0.185
Teacher spread0.179 · 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
Published2013
Admission routes1
Has abstractyes

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