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Record W2025812132 · doi:10.1002/2015gl063147

Evaluation of the inertial dissipation method within boundary layers using numerical simulations

2015· article· en· W2025812132 on OpenAlexaff
Aidin Jabbari, Leon Boegman, Ugo Piomelli

Bibliographic record

VenueGeophysical Research Letters · 2015
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsQueen's University
Fundersnot available
KeywordsDissipationTurbulenceMechanicsPhysicsTurbulence kinetic energyBoundary layerInertial frame of referenceComputationSpectral lineKinetic energyConvectionLogarithmComputational physicsClassical mechanicsMathematical analysisMathematicsThermodynamicsAlgorithm

Abstract

fetched live from OpenAlex

Abstract We evaluated the accuracy of the inertial dissipation method to estimate the rate of dissipation of turbulent kinetic energy within boundary layers by performing well‐resolved numerical simulations of turbulent channel flows and comparing the dissipation calculated directly from the data, with that deduced from the frequency spectra. The convection velocity, commonly used to convert frequency spectra into wave number spectra is found to be larger than the local mean velocity by approximately a factor of 2 near the bed and about 10% in the logarithmic layer and beyond. Usage of the standard Kolmogorov constants (particularly in the vertical and spanwise directions) also leads to significant errors (50% or more) in computation of dissipation. Usage of the optimal Kolmogorov constants and the convection velocity, obtained from the simulation results could result in improved accuracy in dissipation calculation with the inertial method.

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 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)0.002
metaresearch head score (Gemma)0.001
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 score0.077
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.097
GPT teacher head0.382
Teacher spread0.285 · 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 teacher head, 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

Citations13
Published2015
Admission routes1
Has abstractyes

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