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Record W2208184699 · doi:10.1063/1.4935112

Large-eddy simulation of turbulent flow and dispersion over a matrix of wall-mounted cubes

2015· article· en· W2208184699 on OpenAlexaff
Mohammad Saeedi, Bing-Chen Wang

Bibliographic record

VenuePhysics of Fluids · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTurbulencePhysicsLarge eddy simulationMechanicsScalar (mathematics)Turbulence kinetic energyPlumeK-epsilon turbulence modelContext (archaeology)Direct numerical simulationFlow (mathematics)Boundary layerMeteorologyReynolds numberGeometryGeology

Abstract

fetched live from OpenAlex

Turbulent flow over a matrix of wall-mounted cubic obstacles along with continuous release of a passive scalar from a ground-level point source has been investigated using wall-modeled large-eddy simulation (LES). The cubes are fully submerged in a modeled urban atmospheric boundary layer with high turbulence intensities. An inlet boundary condition has been proposed to reproduce the high turbulence level of the approaching flow based on generation of grid turbulence. Coherent flow structures induced by the cubes and their influences on dispersion of the concentration plume in the context of the highly disturbed flow are also investigated. The spatial evolution and temporal cascades of the kinetic and scalar energies have been examined in terms of their transport equations and resolved spectra. In order to validate the LES approach, numerical predictions of turbulence statistics for both velocity and concentration fields have been thoroughly validated against a set of comprehensive water-channel measurement data.

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 score0.482
Threshold uncertainty score0.247

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 head0.014
GPT teacher head0.269
Teacher spread0.255 · 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

Citations22
Published2015
Admission routes1
Has abstractyes

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