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Record W3200642319 · doi:10.22215/etd/2016-11663

Measurements of the Effects of Streamwise Riblets on the Turbulence Structures in Boundary Layers

2016· dissertation· en· W3200642319 on OpenAlexaff
Derek B. Ancrum

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsCarleton University
Fundersnot available
KeywordsTurbulenceVortexPhysicsWave packetNetwork packetMechanicsOpticsComputer science

Abstract

fetched live from OpenAlex

This study presents experimental results on the effects of streamwise-oriented riblets on the coherent structures of turbulence.Hotwire measurements were performed in artificially created turbulent spots.The riblet spacings of the study correspond to 0.5 and 1.5 times the natural spacing of the low-speed streaks and fall into the category identified as wider-spaced in published literature.The cross-sectional dimensions of the riblets were chosen to promote more effective control on the development and spatial distribution of wave packets consisting of streamwise-aligned hairpin vortices.The riblets proved to be highly effective in controlling the spatial positioning of wave packets.Of the two riblet spacings considered, the wider spacing increased the spanwise spacing of the low-speed streaks beyond their natural spacing and stabilized the wave packets over the riblet tips, enabling a reduction in their mutual interaction and realizing a reduction in their spanwise density compared to the conditions on a smooth surface.This effect may be optimized to achieve skin-friction drag and aerodynamic noise reduction.The closerspaced riblets were observed to have even more control on the spanwise positioning of the wave packets, and produced notably stronger sweep and ejection events by reducing the spanwise spacing between wave packets and promoting mutual interaction of hairpin vortices via spanwise-oriented vortical structures created by a Kelvin-Helmholtz instability mechanism.This effect may be used to achieve increased convection heat transfer in various applications without significant penalties in pressure loss.

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: Observational · 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 studies0.0000.001
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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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 designObservational
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
Published2016
Admission routes1
Has abstractyes

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