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Record W2049951765 · doi:10.1115/1.1860570

Modeling Transition in Separated and Attached Boundary Layers

2004· article· en· W2049951765 on OpenAlex
S. K. Roberts, M. I. Yaras

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Turbomachinery · 2004
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsCarleton University
FundersPratt and Whitney Canada
KeywordsBoundary layerTurbulenceBoundary (topology)Transition (genetics)Surface roughnessMechanicsProduction rateSurface finishStatistical physicsTransition layerFlow (mathematics)Separation (statistics)Production (economics)Biological systemComputer scienceSimulationLayer (electronics)Materials scienceMathematicsPhysicsChemistryThermodynamicsEngineeringMathematical analysisNanotechnologyIndustrial engineeringMachine learningComposite material

Abstract

fetched live from OpenAlex

Abstract This paper presents a mathematical model for predicting the rate of turbulent spot production. In this model, attached- and separated-flow transition are treated in a unified manner, and the boundary layer shape factor is identified as the parameter with which the spot production rate correlates. The model is supplemented by several correlations to allow for its practical use in the prediction of the length of the transition zone. Second, the paper presents a model for the prediction of the location of transition inception in separation bubbles. The model improves on the accuracy of existing alternatives, and is the first to account for the effects of surface roughness.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.214
Teacher spread0.208 · 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