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Record W2756465913 · doi:10.1080/00221686.2017.1356758

New insight in Francis turbine cavitation vortex rope: role of the runner outlet flow swirl number

2017· article· en· W2756465913 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Hydraulic Research · 2017
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsnot available
FundersSeventh Framework ProgrammeBC HydroÉcole Polytechnique Fédérale de LausanneEuropean Commission
KeywordsFrancis turbineDraft tubeCavitationTurbineMechanicsRopePrecessionTorqueVortexFlow (mathematics)Resonance (particle physics)Control theory (sociology)Computer scienceAcousticsPhysicsEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

At part load operation, Francis turbines experience the development of a cavitation vortex rope in the draft tube, whose precession acts as a pressure excitation source. In case of resonance, the resulting pressure pulsations lead to unacceptable torque and power fluctuations on the prototype machine, putting at risk the system stability. However, the accurate prediction of resonance conditions at the prototype scale remains challenging since it requires a proper hydro-acoustic modelling of the draft tube cavitation flow. Furthermore, both the head and discharge values have an impact on the precession frequency of the vortex and the natural frequency of the system. The present paper demonstrates for the first time that the influence of both parameters on the frequencies of interest can be represented by a single parameter, the swirl number. Its analytical expression is derived as a function of the operating parameters of the machine. It is used to establish empirical laws enabling the determination of both frequencies and finally the operating parameters in resonance conditions on the complete part load operating range at the model scale. The methodology presented in this paper represents a decisive step towards the prediction of resonances on the complete part load operating range of the prototype.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.718
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.317
Teacher spread0.291 · 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