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Record W4400499983 · doi:10.55037/lxlaser.21st.25

Endoscopic Stereoscopic PIV Measurements Within An Enclosed And Tight Area Of A Hydraulic Turbine

2024· article· en· W4400499983 on OpenAlexafffund
Araz Rezavand Hesari, Anthony Munoz, Maxime Coulaud, Sébastien Houde, Yvan Maciel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaHydro-QuébecUniversité LavalVattenfall
KeywordsStereoscopyHydraulic turbinesTurbineGeologyAerospace engineeringComputer scienceMarine engineeringMechanical engineeringEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The increasingly common utilization of hydraulic turbines in off design operating conditions in recent years have affected their lifetime due to damaging fluid-structure interactions. To decrease the downtime associated to more frequent maintenance of these turbines, a thorough understanding of the damaging flow phenomena is required. This may eventually lead to the development of mitigation strategies. However, measuring velocity at the entrance of the rotor of Francis turbines is difficult because of the confined spaces and limited optical access. This paper presents a stereoscopic PIV methodology enabling measurements at the inlet of a reduced-scale Francis turbine, along with multiple novelties developed to make accurate measurements possible. It elaborates on the solutions devised to address the challenges of performing optical measurements in highly confined spaces. The measured velocity fields cover the vaneless space and a large section of the interblade channels. In the phase-averaged velocity fields, three circulation zones are detected at the speed-no load operating point, representing the combined effect of numerous vortices and flow structures observed in the instantaneous velocity fields. The flow is characterized by a significant backflow within the runner, extending to the leading edge of the runner blades and overflowing into the vaneless space.

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 score0.287
Threshold uncertainty score0.511

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 head0.034
GPT teacher head0.244
Teacher spread0.210 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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