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Record W2074177130 · doi:10.1088/1755-1315/22/3/032010

Experimental investigation of the draft tube inlet flow of a bulb turbine

2014· article· en· W2074177130 on OpenAlexaff
Jean-Christophe Vuillemard, V Aeschlimann, R Fraser, S. Lemay, Claire Deschênes

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2014
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsDraft tubeInletMechanicsWakeTurbineParticle image velocimetryFlow (mathematics)Laser Doppler velocimetryFlow separationVelocimetryTube (container)VortexMaterials sciencePhysicsTurbulenceEngineeringAerospace engineeringMechanical engineering

Abstract

fetched live from OpenAlex

In the BulbT project framework, a bulb turbine model was studied with a strongly diverging draft tube. At high discharge, flow separation occurs in the draft tube correlated to significant efficiency and power drops. In this context, a focus was put on the draft tube inlet flow conditions. Actually, a precise inlet flow velocity field is required for comparison and validation purposes with CFD simulation. This paper presents different laser Doppler velocimetry (LDV) measurements at the draft tube inlet and their analysis. The LDV was setup to measure the axial and circumferential velocity on a radius under the runner and a diameter under the hub. A method was developed to perform indirect measurement of the mean radial velocity component. Five operating conditions were studied to correlate the inlet flow to the separation in the draft tube. Mean velocities, fluctuations and frequencies allowed characterizing the flow. Using this experimental database, the flow structure was characterized. Phase averaged velocities based on the runner position allowed detecting the runner blade wakes. The velocity gradients induced by the blade tip vortices were captured. The guide vane wakes was also detected at the draft tube inlet. The recirculation in the hub wake was observed.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.499

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 studies0.0000.001
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 head0.008
GPT teacher head0.178
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 teacher head, 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

Citations20
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueIOP Conference Series Earth and Environmental ScienceSame topicCavitation Phenomena in PumpsFrench-language works237,207