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Record W2041699194 · doi:10.1139/l01-078

Model testing of submerged vanes in strongly curved narrow channel bends

2002· article· en· W2041699194 on OpenAlexfundvenueno aff
Adam Francis. Voisin, R. D. Townsend

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsThalwegBank erosionTransverse planeChannel (broadcasting)ErosionCurrent (fluid)Flow (mathematics)GeologyGeotechnical engineeringMechanicsSedimentGeometryEngineeringStructural engineeringPhysicsElectrical engineeringGeomorphology

Abstract

fetched live from OpenAlex

This paper reports on a laboratory study that examines the effectiveness of submerged vanes for the control of erosion in strongly curved narrow channel bends. All previous researches on submerged vanes were performed in either straight or weakly curved channels that were hydraulically "wide". Submerged vanes are thin rectangular-shaped low-profile foils, typically set at small angles to the main current and arranged in either single or multiple parallel arrays in the longitudinal direction. When installed in a channel bend they induce a helicoidal vortex that interacts with and weakens the centrifugally induced secondary current. The latter effect leads to reduced local erosion near the bend's outer bank. Physical model testing was performed to determine the effects of several parameters affecting submerged vane performance, including submerged vane height H, length L, angle to main flow direction α, vane streamwise spacing δ s , vane transverse spacing from outer bank δ n , and bend angle φ. Submerged vanes effectively stabilize channel bend erosion by reducing the scour depth at the outer bank, generating positive transverse bed slope at the outer bank, and by reducing the net sediment loss through the channel. In general, an increase in vane height tends to shift the thalweg away from the outer bank; an increase in vane length tends to reduce the general erosion through the channel.Key words: submerged vanes, riverbank stabilization, bottom vanes, narrow channels, bank protection, bank stabilization, channel bends.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.924

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)0.0010.000

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 head0.021
GPT teacher head0.176
Teacher spread0.156 · 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 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

Citations28
Published2002
Admission routes2
Has abstractyes

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