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Geometric parameters of influence on rotor stator interaction in radial hydraulic turbines

2021· article· en· W3166203582 on OpenAlexaff
B Nennemann, S Afara, Christine Monette, O Braun

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsAndritz (Canada)
Fundersnot available
KeywordsStatorTorqueRotor (electric)Blade (archaeology)Forcing (mathematics)Trailing edgeMechanicsFlow (mathematics)EngineeringMarine engineeringMechanical engineeringStructural engineeringGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract Numerical methods for the prediction of the hydraulic forcing from rotor stator interaction (RSI) in hydraulic turbines as well as the corresponding methods to calculate mechanical dynamic stresses are mature and well-established in the industry. The geometric factors influencing RSI are generally known, but little information is available on the quantification of these factors with respect to RSI forcing. We present relative quantifications of four geometric factors on RSI forcing expressed as dynamic blade torque. The factors are the blade leading edge lean, the radial distance between guide vane trailing and runner leading edges, the phase between adjacent runner channels as a function of number of guide vanes and blades, and finally the number of guide vanes independently of their effect on the phase. RSI pressure pulsations on the stator in the vane-less space between guide vanes and runner show a different tendency with the variation of the blade number compared to the dynamic blade torque. This indicates that dynamic pressure measurements in the vane-less space are not a good indicator for dynamic forcing on the runner blades.

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 score0.424
Threshold uncertainty score0.456

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 communication0.0000.001
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 head0.010
GPT teacher head0.202
Teacher spread0.192 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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