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Record W1982798420 · doi:10.2514/1.18973

Turbulent Flow Through a Staggered Tube Bank

2006· article· en· W1982798420 on OpenAlexafffund
You Qin Wang, Peter L. Jackson, Timothy J. Phaneuf

Bibliographic record

VenueJournal of Thermophysics and Heat Transfer · 2006
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Northern British Columbia
FundersUniversity of British ColumbiaBritish Columbia Knowledge Development FundUniversity of Northern British Columbia
KeywordsTurbulenceMechanicsFlow (mathematics)Tube (container)Materials scienceEnvironmental sciencePhysics

Abstract

fetched live from OpenAlex

Reynolds stress model simulations of turbulent flow through a staggered tube bank were carried out using the computational fluid dynamics code FLUENT. Both wall functions and near-wall treatment approaches were used. In addition, simulations using a near-wall turbulence model, the Spalart-Allmaras turbulence model, were also carried out for comparison. Simulations were performed at a Reynolds number of 10 6 with longitudinal pitch-to-diameter ratio of 1.414 and transverse pitch-to-diameter ratio of 2.0. The primary aim was to numerically investigate the crossflow in a tube bank at a very high Reynolds number using a two-dimensional model. Reynolds stress model with both standard wall function approach and nonequilibrium wall function approach predicted the position of boundary layer separation well. The heat transfer prediction was found to be in reasonable agreement with the experimental data and the empirical correlation. Flow visualization provided a clear picture of the vortex shedding which can help us better understand the flow character. The existence of two Strouhal numbers was consistent with some experimental studies.

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 score0.178
Threshold uncertainty score0.554

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 head0.186
Teacher spread0.180 · 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

Citations28
Published2006
Admission routes2
Has abstractyes

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