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Clear Water Local Scour by Submerged Three-Dimensional Wall Jets: Effect of Tailwater Depth

2006· article· en· W2143471499 on OpenAlexaff
Md Abdullah Al Faruque, Partha Sarathi, Ram Balachandar

Bibliographic record

VenueJournal of Hydraulic Engineering · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsTailwaterFroude numberNozzleGeotechnical engineeringHydraulicsScalingGeologyJet (fluid)Hydrology (agriculture)Flow (mathematics)MechanicsGeometryMathematicsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

The present study deals with scour caused by three-dimensional jets issuing from a square cross-section nozzle onto a noncohesive sand bed. Experiments were conducted using two different nozzles and three tailwater depths. The densimetric Froude number was maintained below ten, while the jet expansion ratio was held greater than ten. The results indicate that the densimetric Froude number, tailwater depth, and grain size-to-nozzle width ratio, all have an influence on the extent of scour. However, each parameter has a dominant influence at different flow conditions. For example, at values of densimetric Froude numbers less than five, nondimensional tailwater depth and grain size-to-nozzle width ratio have no effect on the maximum depth of scour. At higher densimetric Froude numbers, the effect of tailwater depth appears to be important at larger values of grain size-to-nozzle width ratio. A set of scaling parameters based on nozzle hydraulic radius, grain size, and densimetric Froude number provides for a better scaling of the time variation of the scour parameters.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
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 head0.002
GPT teacher head0.173
Teacher spread0.170 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations38
Published2006
Admission routes1
Has abstractyes

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