MétaCan
Menu
Back to cohort
Record W2017702606 · doi:10.1080/10407780902720841

Validation of DES-SST Based Turbulence Model for a Fully Developed Turbulent Channel Flow Problem

2009· article· en· W2017702606 on OpenAlexaff
D. Home, M.F. Lightstone, M. Hamed

Bibliographic record

VenueNumerical Heat Transfer Part A Applications · 2009
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTurbulenceMechanicsLarge eddy simulationK-epsilon turbulence modelK-omega turbulence modelAdvectionTurbulence modelingPhysicsDirect numerical simulationOpen-channel flowReynolds numberReynolds stress equation modelStatistical physicsThermodynamics

Abstract

fetched live from OpenAlex

This work discusses simulations using the detached eddy simulation based (DES) turbulence model to investigate turbulent channel flows. Applicability of Strelets' (2001) version of the DES model was tested for a fully developed turbulent channel flow problem in a rectangular duct. The unsteady Navier-Stokes equations were solved numerically at Reynolds number, Re τ , of 180, 590, and 2000, respectively, and compared to results obtained using direct numerical simulation (DNS) and previously published DES data. Effects of grid density and advection scheme were investigated. Overall, the model predicted the correct trends in the variation of turbulence quantities and compared reasonably well.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.022
GPT teacher head0.237
Teacher spread0.215 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueNumerical Heat Transfer Part A ApplicationsSame topicFluid Dynamics and Turbulent FlowsFrench-language works237,207