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Record W2507762946 · doi:10.1115/1.4034422

A Numerical Study of Francis Turbine Operation at No-Load Condition

2016· article· en· W2507762946 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.

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

Bibliographic record

VenueJournal of Fluids Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsTransCanada (Canada)Polytechnique Montréal
Fundersnot available
KeywordsReynolds-averaged Navier–Stokes equationsTurbineFrancis turbineRotor (electric)StatorMechanicsTorqueDraft tubeFlow (mathematics)Turbine bladeTurbomachineryTurbulenceMechanical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

This paper presents a numerical methodology to study Francis turbines at no-load condition, an important operating condition regarding static and dynamic stresses. The proposed methodology uses unsteady Reynolds-averaged Navier–Stokes (RANS) simulations that have been integrated with a user subroutine to compute and return the value of runner speed, time step, and friction torque. The modeling tool is the commercial software ansys-cfx 14. The research compares the simulations that were performed using transient rotor–stator (TRS) and stage interface models and validate the results through experiments over the full range of admissible guide vane angles (GVAs). Both TRS and stage interface models yielded similar trends for all turbine runner parameters during the no-load process. Results show sizable differences in the average and maximum pressure on the blades between TRS and stage simulations. Analysis of the flow behavior in TRS simulation demonstrates complex flow phenomena involving a vortex breakdown within the draft tube, and strong vortices blocking the runner inlet, which dissipate the input energy into the turbine and yield a near zero-torque at no-load condition.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.434

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 head0.214
Teacher spread0.208 · 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