Preliminary investigation of flow dynamics during the start-up of a bulb turbine model
Bibliographic record
Abstract
Nowadays, the electricity network undergoes more perturbations due to the market demand. Additionally, an increase of the production from alternative resources such as wind or solar also induces important variations on the grid. Hydraulic power plants are used to respond quickly to these variations to stabilize the network. Hydraulic turbines have to face more frequent start-up and stop sequences that might shorten significantly their life time. In this context, an experimental analysis of start-up sequences has been conducted on the bulb turbine model of the BulbT project at the Hydraulic Machines Laboratory (LAMH) of Laval University. Maintaining a constant head, guide vanes are opened from 0 ° to 30 °. Three guide vanes opening speed have been chosen from 5 °/s to 20 °/s. Several repetitions were done for each guide vanes opening speed. During these sequences, synchronous time resolved measurements have been performed. Pressure signals were recorded at the runner inlet and outlet and along the draft tube. Also, 25 pressure measurements and strain measurements were obtained on the runner blades. Time resolved particle image velocimetry were used to evaluate flowrate during start-up for some repetitions. Torque fluctuations at shaft were also monitored. This paper presents the experimental set-up and start-up conditions chosen to simulate a prototype start-up. Transient flowrate methodology is explained and validation measurements are detailed. The preliminary results of global performances and runner pressure measurements are presented.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".