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Record W2113191422 · doi:10.2514/1.44356

Turbulence Modeling Applied to Flow Through a Staggered Tube Bundle

2010· article· en· W2113191422 on OpenAlexafffund
You Qin Wang, Peter L. Jackson

Bibliographic record

VenueJournal of Thermophysics and Heat Transfer · 2010
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Northern British Columbia
FundersBritish Columbia Knowledge Development Fund
KeywordsTurbulenceBundleMechanicsTube (container)Flow (mathematics)Computational fluid dynamicsMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Both two-dimensional and three-dimensional numerical simulations of the turbulent flow through a staggered tube bundle are presented. The primary aim of the present study is to search for a turbulent model that could serve as an engineering design tool at a relatively low computational cost. In the present study, the performances of the Spalart-Allmaras model, the k-e model, and large eddy simulation are evaluated by comparing their simulation results against experimental measurements. The turbulence models are assessed mainly based on their ability to resolve time-dependent features of the flow related to vortex shedding. Simulations are performed at a Reynolds number of 9300. Overall, the predicted streamwise mean velocity and transverse mean velocity in the present study are in good agreement with measurements, and the results show that the simple one-equation Spalart-Allmaras model could be a very promising tool for numerical simulation of complex turbulent flows, since the Strouhal number obtained by it agrees well with measurements available in the literature for similar tube geometries.

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)0.000
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 score0.299
Threshold uncertainty score0.581

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 head0.008
GPT teacher head0.198
Teacher spread0.190 · 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

Citations18
Published2010
Admission routes2
Has abstractyes

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