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Record W4390729624 · doi:10.1139/cjce-2023-0360

Effect of hemispherical roughness spacing on double-averaged turbulence characteristics for different flow submergence

2024· article· en· W4390729624 on OpenAlexvenueno aff
Jayanta Shounda, Krishnendu Barman, Koustuv Debnath

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
Fundersnot available
KeywordsTurbulenceFlow (mathematics)MechanicsSurface finishHydraulic roughnessTurbulence kinetic energyEnvironmental scienceGeologyMeteorologyMaterials sciencePhysicsEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

The double-averaged (DA) turbulence characteristics over rough bed comprising of hemispherical elements with different spacing ( p/ r = 2, 4, 6, and 8; p = pitch distance; r = height of hemisphere) is quantified for three flow-submergences ( h/ r = 7.14, 5.35, 3.57; mean flow-depth ( h) = 20 cm, 15 cm, and 10 cm). The production and dissipation rates of turbulent kinetic energy are maximum at and below the crest level. Within interfacial sublayer, the degree of anisotropy is observed to be maximum for p/ r = 4 and the tendency for the return to isotropy is strongest for p/ r = 8 in the outer layer. The turbulence generated in the bottom region is still present in the outer region for low flow-submergences. The turbulence strength is maintained in the roughness order (descending) as p/ r = 4 > 2 > 6 > 8 > plane bed; wherein the change in flow-submergence does not change this order.

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)0.000
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
Metaresearch0.0000.000
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 head0.005
GPT teacher head0.196
Teacher spread0.191 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicHydrology and Sediment Transport ProcessesFrench-language works237,207