A Numerical Study of Francis Turbine Operation at No-Load Condition
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".