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Two-Dimensional Scour Hole Problem: Role of Fluid Structures

2007· article· en· W1982941558 on OpenAlexaff
Alex Bey, Md Abdullah Al Faruque, Ram Balachandar

Bibliographic record

VenueJournal of Hydraulic Engineering · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsGeologyTurbulenceVortexJet (fluid)MechanicsAnemometerFlow (mathematics)Geotechnical engineeringPhysics

Abstract

fetched live from OpenAlex

An experimental program was carried out to understand scour caused by a plane wall jet. A two-dimensional laser Doppler anemometer was used to characterize the velocity field at various locations in the scour hole region. Observations indicate that different types of flow structures influence scour at different time periods. Based on the present tests, the entire test duration is divided into five time zones. Following vigorous scour caused principally by jet shear forces and impingement at the start of the test and during early time periods, the flow was characterized by the presence of longitudinal axial vortices, turbulent bursts, and movement of the jet impingement point during the later stages. Attempts were made to distinguish the fluid structures at asymptotic conditions. The scour hole region was characterized by the presence of randomly forming and disappearing streaks, laterally located concave shaped depressions, rolling and ejection of the bed material. Through analysis of higher order moments and quadrant decomposition, sweep and ejection type events were observed, which can potentially contribute to scour.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.004
GPT teacher head0.204
Teacher spread0.200 · 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 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

Citations58
Published2007
Admission routes1
Has abstractyes

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