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Water Surface Characteristics of Submerged Rectangular Sharp-Crested Weirs

2016· article· en· W2232538945 on OpenAlexaff
Amir H. Azimi, N. Rajaratnam, David Z. Zhu

Bibliographic record

VenueJournal of Hydraulic Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWeirHydraulic jumpJet (fluid)MechanicsFree surfaceSurface waveFlow (mathematics)Surface (topology)JumpGeologySupercritical flowGeometryPhysicsMathematicsOpticsGeography

Abstract

fetched live from OpenAlex

Laboratory experiments were carried out to investigate the water surface characteristics of submerged flow over sharp-crested weirs. Interesting observations were made on the water surface profiles near the weir as weir submergence sets in as well as for various stages of submergence. Submerged flow was divided into four regimes: (I) impinging jet, (II) surface jump, (III) surface wave, and (IV) surface jet. It was found that a surface jump turned into a surface wave when the wave trough became level with the tip of the weir. The surface jet regime began as the surface waves faded out. A condition was set to quantify the boundary between the surface wave and surface jet regimes. Based on flow observations, the surface jet regime sets in as the amplitude of the surface wave becomes small (i.e., less than 0.1h, where h is the head). An empirical equation was developed based on the literature data to predict the discharge reduction factor in the generally used discharge equation. This formulation was compared with other formulations in the literature. It was found that the proposed formulation provides a slightly better estimation of flow discharge.

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: Observational · Consensus signal: none
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)0.0000.000

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 head0.174
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 designObservational
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
Published2016
Admission routes1
Has abstractyes

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