Classification of the Hydraulic Behavior Along the No-Load Curve of Francis Turbines
Bibliographic record
Abstract
Abstract For hydraulic turbines, no-load (NL) is considered a homogeneous family of operating conditions, although the literature exposes a wide variety of flow structures depending on many factors. A better understanding of the flow structures developed during NL operation is necessary, since they generate pressure fluctuations in the turbine causing significant fatigue damage and reducing the life expectancy of the machines. Hydraulic turbines at model scale show that behavioral trends can be identified for NL conditions. This paper presents a classification of NL operating conditions following the swirl level at the runner outlet. The main tendencies linking the cavitation level to the runner speed and the discharge for operating points along NL curves of different turbines are also detailed. To study the NL conditions, data from 26 Francis turbines, measured between 2007 and 2020 at the laboratory of Andritz Hydro Canada Inc., are analyzed. This study demonstrates that NL operating conditions exhibit flow features very similar to those at regular operation with similar runner outlet swirl. The runner acceleration or deceleration with cavitation is related to the flow topology at the runner outlet.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".