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Record W1981909110 · doi:10.1139/l06-170

Two-dimensional finite element river morphology model

2007· article· en· W1981909110 on OpenAlexaffvenue
Jose A. Vasquez, Robert G. Millar, P. M. Steffler

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSupercritical flowAggradationHydraulic jumpGeologySediment transportFlow (mathematics)Geotechnical engineeringSedimentFinite element methodHydraulicsSedimentationHydrology (agriculture)ErosionOpen-channel flowBedformMechanicsGeomorphologyEngineeringFluvial

Abstract

fetched live from OpenAlex

We report the development and application of a river morphology model based on the two-dimensional depth-averaged hydrodynamic model River2D. This new movable bed version of River2D was applied to simulate the bed elevation changes in four experiments: bed aggradation due to sediment overload, bed degradation by sediment supply shut-off, knickpoint migration, and bar formation in a variable-width channel. Some conditions in these experiments involved quick changes in the upstream boundary conditions, rapidly varied flow, supercritical flow, hydraulic jumps, and secondary flows. The results of the model agreed well with measured data. Notable features of the model are the use of a flexible unstructured mesh based on triangular finite elements to provide higher spatial resolution in areas of interest and transcritical flow capabilities to simulate supercritical flow and hydraulic jumps over movable beds. Key words: numerical modeling, rivers, scour, sedimentation, two-dimensional, finite elements.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.998

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)0.0030.000

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 head0.007
GPT teacher head0.188
Teacher spread0.181 · 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

Citations22
Published2007
Admission routes2
Has abstractyes

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