Time-resolved PIV measurement at the exit of a Francis turbine runner during a homologous start-up sequence
Bibliographic record
Abstract
Because of the growing integration of intermittent energy sources into the power grid, hydraulic turbines undergo more frequent transient operations such as startup. Different field studies have highlighted that startups are some of the most damaging events for hydraulic turbines. They can induce high stress levels in the runner, potentially leading to structural damage. The complex transient fluid-structure interactions associated with start-ups make them one of the hydraulic turbines' most critical and challenging operating conditions. Key parameters such as rotational speed, guide vanes opening speed, inertia of rotating components, and startup duration influence stress levels in the runner. To investigate the startup behaviour of a 140 MW Francis turbine at the Jean-Lesage generating station (Manic-2), a homologous startup scenario was implemented on a reduced-scale model of a medium-head Francis turbine installed on the Heki test stand at Université Laval.As a part of the Tr-Francis project, stereoscopic Time-Resolved Particle Image Velocimetry (TR-PIV) measurements at the runner outlet, along with strain measurements on the runner, were conducted to analyze fluid-structure interactions during startup. The runner was explicitly designed to achieve a scaled structural response homologous with the prototype turbine. This presentation introduces the methodology for performing stereoscopic TR-PIV measurement at the runner outlet during homologous startup sequences. It presents the endoscopic camera configuration and the laser sheet location. The measurement plane extends from the trailing edge of the runner to a region crossing the rotation axis within the conical diffuser. Preliminary measurements reveal that flow dynamics exhibit considerable temporal and spatial variation. Consequently, four different “time between frames” for each image pair were empirically determined to ensure the reliability and accuracy of PIV velocity fields. Results of different velocity field analyses are presented, including the procedure developed to evaluate windowed average velocity fields using sixty repetitions of the homologous startup sequence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.013 |
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; both teacher heads agree on what is shown here.
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".