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Mathematical Modeling of Meandering Channels with a Generalized Depth Averaged Model

2005· article· en· W2045844429 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Hydraulic Engineering · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Regina
FundersMatsumae International Foundation
KeywordsCurvilinear coordinatesSkewnessChannel (broadcasting)GeometrySurface (topology)GridGeologyOpen-channel flowSimple (philosophy)MechanicsMathematicsFlow (mathematics)Computer sciencePhysicsStatisticsTelecommunications

Abstract

fetched live from OpenAlex

A two-dimensional depth averaged model is developed in a nonorthogonal curvilinear coordinate system. The ability of the model in handling complex mesh arrangements with high aspect ratios and skewness is investigated. It is shown that model formulation makes it able to handle large skewness in the grid lines. It is also shown that in predicting the water surface profile with a very distorted mesh, most of the errors arise from the large aspect ratio rather than the skewness of the grid lines. The model is then applied to three meandering channels (two simple and one compound), with specifications similar to those found in nature and the results are compared with experimental data. The comparison shows that the model predicted the water surface profile and velocity distribution well in simple channels. Predictions of the model in the main channel of the compound meandering channel were also in general agreement with the experimental results.

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.

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 score0.379
Threshold uncertainty score0.394

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 head0.012
GPT teacher head0.207
Teacher spread0.195 · 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