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Record W2150376718 · doi:10.1139/l05-079

Prediction of flow patterns in scoured beds caused by submerged horizontal jets

2006· article· en· W2150376718 on OpenAlexvenueno aff
Mustafa Günal, Aytaç Güven

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMechanicsTurbulenceJet (fluid)ComputationFinite volume methodGeologyBoundary layerFlow (mathematics)GeometryShear stressGeotechnical engineeringMathematicsPhysics

Abstract

fetched live from OpenAlex

The basic goal of this study is to present a numerical simulation model for turbulent water flow issued on frozen scoured beds. The model uses a finite volume method to solve the equations of motion and transport equations for two dimensions on a transformed rectangular domain using boundary-fitted coordinates. The internal characteristics of the mean flow of submerged horizontal jets including surface profiles on frozen scoured beds are computed by a two-dimensional k–ε turbulence model. Computations are carried out at different frozen-scoured bed profiles. A staggered grid system is adapted for variable arrangements to avoid the well-known checkerboard oscillations in pressure and velocity. The SIMPLE algorithm is adapted for the computation. No experimental studies were performed during this investigation. The diffusion characteristics of the submerged jet, growth of boundary layer thickness, velocity distribution within the boundary layer, and shear stress at the scour are investigated and compared with the results of others. Key words: boundary-fitted coordinates, local scour, k–ε model, finite volume method, horizontal jets, submerged jets.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
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)0.0000.000

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 head0.005
GPT teacher head0.154
Teacher spread0.149 · 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 designObservational
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

Citations5
Published2006
Admission routes1
Has abstractyes

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