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Record W2683665492 · doi:10.1115/1.4037044

Measurements of the Effects of Streamwise Riblets on Boundary Layer Turbulence

2017· article· en· W2683665492 on OpenAlexaff
Derek B. Ancrum, M. I. Yaras

Bibliographic record

VenueJournal of Fluids Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsCarleton University
Fundersnot available
KeywordsStreakTurbulenceVortexBoundary layerPhysicsWave packetEddyMechanicsNetwork packetOpticsComputer science

Abstract

fetched live from OpenAlex

This study presents experimental results on the effects of riblets on the coherent structures of turbulence within a turbulent spot. The riblet spacings of the study correspond to 0.5 and 1.5 times the natural spacing of the low-speed streak. The cross-sectional dimensions of the riblets were chosen to control the spatial distribution of wave packets consisting of streamwise-aligned hairpin vortices. Both riblet spacings demonstrated effective control on the spanwise positioning of the wave packets. The wider-spaced riblets reduced spanwise mutual interaction between wave packets. The closer-spaced riblets promoted this interaction via spanwise-oriented vortical structures which produced stronger turbulent fluctuations.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.211
Teacher spread0.201 · 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 designBench or experimental
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

Citations6
Published2017
Admission routes1
Has abstractyes

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