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Record W2137738642 · doi:10.1139/cjce-2014-0157

Flow simulation over oblique cylindrical weirs

2015· article· en· W2137738642 on OpenAlexvenueno aff
Mehmet İshak Yüce, Aemad A.H. Al-Babely, Mohammad A. Al-Dabbagh

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsnot available
Fundersnot available
KeywordsWeirMechanicsOblique caseTurbulenceFlow (mathematics)CrestGeologyComputational fluid dynamicsReynolds numberGeotechnical engineeringReynolds stressMaterials scienceGeometryMathematicsPhysicsOpticsGeography

Abstract

fetched live from OpenAlex

This paper presents a computational fluid dynamics (CFD) simulation to investigate the effects of the obliqueness of cylindrical weirs on the flow velocity distribution, the pressure distribution and the distribution of water depth over the weir crest. Three different cylindrical weirs with diameters of 0.114 m, 0.09 m, and 0.0635 m, with three dissimilar inclination angles of 90°, 135°, and 150° were used. The SSG Reynolds stress turbulence closure model was utilized in the analyses. The results show that the flow patterns are affected by the inclination angle with respect to the flow direction. It was noticed that inclination angle increment increases the velocity of flow at the downstream surface of the weir, thus increases the absolute value of the negative pressure, at the inward-moved end of the weir. The outward-moved end of the weir was observed not to be covered with water and extending with the increase of the inclination angle.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

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 head0.010
GPT teacher head0.198
Teacher spread0.188 · 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

Citations16
Published2015
Admission routes1
Has abstractyes

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