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Record W2112777157 · doi:10.1115/1.4029164

Experimental Study of the Type VI Stilling Basin Performance

2014· article· en· W2112777157 on OpenAlex
Seyed Sobhan Aleyasin, Nima Fathi, Peter Vorobieff

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Fluids Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFroude numberTurbulenceBaffleDissipationFlow (mathematics)Turbulence kinetic energyOpen-channel flowGeologyHydraulic jumpChannel (broadcasting)Structural basinHydrology (agriculture)Geotechnical engineeringMechanicsMeteorologyGeomorphologyEngineeringGeographyPhysicsTelecommunications

Abstract

fetched live from OpenAlex

Understanding the estuarine turbulent flow from dams, channels, and pipes, as well as the river flow are very important due to the potential to cause damage to the bed of the river or channel and cause scouring of structures such as the saddles of bridges, because of the huge amount of the kinetic energy carried by the flow. One of the most efficient yet simple ways to dissipate this energy is to install a stilling basin at the discharge point to calm the flow. Turbulence data were recorded using acoustic Doppler velocimetry (ADV) for type VI2 of stilling basins for pipe outlets. During the study, various splitters and a cellular baffle were placed in the stilling basin, and the baffle locations were changed to assess the effect on the energy dissipation. Velocity at several locations in the basin was measured for different Froude numbers to investigate the effect of flow rate. Based on the findings of the experiments, several suggestions regarding the efficiency and geometry of stilling basins were made.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.233
Threshold uncertainty score0.320

Codex and Gemma teacher scores by category

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 head0.006
GPT teacher head0.200
Teacher spread0.193 · 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