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Record W4390235983 · doi:10.3390/w16010085

Numerical Simulation of Confluence Flow in a Degraded Bed

2023· article· en· W4390235983 on OpenAlexafffund
Ehsan Behzad, Abdolmajid Mohammadian, Colin D. Rennie, Qingcheng Yu

Bibliographic record

VenueWater · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConfluenceReynolds-averaged Navier–Stokes equationsVolume of fluid methodMechanicsLarge eddy simulationTurbulenceOpen-channel flowFlow (mathematics)Computer simulationVortexGeologyReynolds numberFlumeDead zoneChannel (broadcasting)GeometryMathematicsPhysicsEngineeringComputer science

Abstract

fetched live from OpenAlex

The fluid dynamics of channel confluences are highly complex due to flow separation and secondary currents. Although numerous studies in the past few decades have focused on the numerical simulation of confluence flow, deformed beds were rarely used. This study attempts to address this issue through numerical simulation of the flow behavior in an open-channel confluence flume with an equilibrium degraded bed in OpenFOAM (version 6.0) to compare the results with a flatbed. In the present study, different turbulence models, including Reynolds-Averaged Navier–Stokes (RANS), large-eddy simulation (LES), and detached eddy simulation (DES) models were performed using rigid-lid and volume-of-fluid (VoF) methods. The accuracy of the models was statistically analyzed by comparing them with observation data. The results demonstrated that the LES model had the best performance, with a minimum average normalized root-mean-square error (NRMSE) of 3% under the VoF assumption. The investigation also further illuminated the intricate interplay of vortical structures within the confluence zone. Notably, the number and behavior of vortices were found to be influenced by channel geometry and size, as well as interactions between separated shear layers. Circulation within the separation zone near the inner bank differed in rotation between the degraded and flatbed cases.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.999

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)0.0020.001

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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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.

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

Citations10
Published2023
Admission routes2
Has abstractyes

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