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Record W2546424466 · doi:10.1139/tcsme-2015-0012

CONTROLLING BOUNDARY LAYER TRANSITION OVER A SEPARATION BUBBLE: A COMPLEX-LAMELLAR APPROACH

2015· article· en· W2546424466 on OpenAlexaffvenue
Maureen L. Kolla, Jeffrey W. Yokota

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsFreestreamBoundary layerLaminar flowIntermittencyBubbleTurbulenceFlow separationMechanicsSeparation (statistics)Lamellar structureMaterials scienceCompressibilityPhysicsReynolds numberMathematics

Abstract

fetched live from OpenAlex

In this paper, we develop a complex-lamellar description of the incompressible flow that exists as a boundary layer transitions from a fully developed laminar to fully developed turbulent flow. This complex-lamellar description is coupled to the shape of the universal intermittency distribution and experimental correlations to obtain a boundary layer model of transition. This transition model is used to analyze the effects of several different freestream turbulence levels on the reattachment location and the length of the resulting separation bubbles. Furthermore, we show that at the separation bubble reattachment location, the resulting boundary layer flow is both turbulent and fully developed. Results obtained from this transition model are compared with, and verified by several different DNS simulations.

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 score0.005

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 communication0.0010.001
Open science0.0010.001
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 head0.019
GPT teacher head0.215
Teacher spread0.196 · 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
Published2015
Admission routes2
Has abstractyes

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