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Preston Tube Measurements in Low Reynolds Number Turbulent Pipe Flow

2000· article· en· W2113630611 on OpenAlexaff
David G. Rhodes, A. P. New

Bibliographic record

VenueJournal of Hydraulic Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsRoyal Military College of Canada
FundersEngineering and Physical Sciences Research Council
KeywordsReynolds numberTurbulenceReynolds stress equation modelMathematicsPipe flowCalibrationRange (aeronautics)Reynolds-averaged Navier–Stokes equationsMechanicsFlow (mathematics)K-epsilon turbulence modelStatistical physicsPhysicsStatisticsGeometryK-omega turbulence modelMaterials science

Abstract

fetched live from OpenAlex

Preston tube measurements were carried out in low Reynolds number, fully developed, turbulent pipe flows to examine the applicability of Patel's calibration equations derived at higher Reynolds numbers and to account for other variables that might be relevant at lower Reynolds numbers. There was a large degree of scatter when the data were plotted in terms of the variables adopted by Preston and Patel in their calibration equations. An investigation was carried out into the influence of other variables of likely relevance, but no systematic dependence could be identified. The scatter was therefore treated as a random error, and a third-order polynomial was fitted for the range of the experimental parameters. It deviates somewhat from Patel's calibration.

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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.197
Teacher spread0.190 · 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

Citations2
Published2000
Admission routes1
Has abstractyes

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