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Record W2066060799 · doi:10.1080/00221680509500110

Two-dimensional depth-averaged modeling of flow in curved open channels

2005· article· en· W2066060799 on OpenAlexafffund
Haitham Ghamry, P. M. Steffler

Bibliographic record

VenueJournal of Hydraulic Research · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of AlbertaFisheries and Oceans Canada
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsCurvatureOpen-channel flowMechanicsGeometryFinite element methodTransverse planeChannel (broadcasting)Flow (mathematics)Galerkin methodGeologyStreamlines, streaklines, and pathlinesHydrostatic equilibriumShallow water equationsMathematicsPhysicsComputer science

Abstract

fetched live from OpenAlex

The application of the depth-averaged De St. Venant equations for open channel numerical models dictate the adoption of hydrostatic pressure distribution. They are thus applicable to cases where vertical details are not significant. The alternative two-dimensional vertically averaged and moment equations model, in which more vertical details are accounted for, is used to analyze problems involved in curved channels of various curvature. The distribution of horizontal velocity components is assumed to be linear, while the vertical velocity and pressure is quadratic. The implicit Petrov-Galerkin finite element scheme is used in these simulations. Computed values for water surface profile, depth-averaged longitudinal and transverse velocities across the channel width and vertical profiles of longitudinal and transverse velocities are compared with experimental data. The comparison shows a good agreement between the simulated results and experimental data. In addition, this study recommends the supplement of the standard conventional De St. Venant model by the proposed model on simulating strongly curved flows. Finally, the use of refined finite element meshes is recommended only when some of the details near the channel edges are sought.

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)0.006
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.081
GPT teacher head0.365
Teacher spread0.284 · 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

Citations43
Published2005
Admission routes2
Has abstractyes

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