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Record W2092600309 · doi:10.1139/l01-012

Effect of grain size on local channel scour below a sluice gate

2001· article· en· W2092600309 on OpenAlexfundvenueno aff
James A. Kells, Ram Balachandar, Kristin Hagel

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Saskatchewan
KeywordsTailwaterGrain sizeGeotechnical engineeringSluiceGeologyChannel (broadcasting)EngineeringGeomorphology

Abstract

fetched live from OpenAlex

In this study, the effect of grain size on the dynamics of local scour processes is discussed in the context of the erosion that takes place downstream from a submerged sluice gate. Four gradations of non-cohesive bed material were used to study the scour process for various tailwater depth and flow rate conditions. The sand gradations included three sizes of uniformly graded sand and a fourth size, which was obtained by mixing the three uniform sands in equal proportions by weight. A total of 36 tests was carried out, each for a period of 24 h. An equilibrium scour condition was not attained over this time period for any of the tests, although a sense of similarity in the bed profiles is observed in the region close to the sluice gate. The present results indicate that the depth and the area of scour are highly dependent on the bed grain size, both increasing as the grain size is reduced. As well, it was found that the tests with a mixed (i.e., graded) sand bed resulted in less scour relative to those in which a uniformly graded sand of similar grain size was used. Moreover, the maximum scour depth increases with increases in the discharge and the tailwater depth. Finally, it was found that the location of the point of maximum scour depth, as measured from the upstream end of the erodible sand bed, moved downstream with an increase in either the discharge or tailwater depth and upstream with an increase in the grain size.Key words: grain size, grain size distribution, local scour, scour dynamics, sluice gate, tailwater depth, video image data acquisition.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score1.000

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 head0.003
GPT teacher head0.177
Teacher spread0.173 · 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

Citations66
Published2001
Admission routes2
Has abstractyes

Explore more

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