Power break off in a bulb turbine: wall pressure sensor investigation
Bibliographic record
Abstract
A measurement campaign using unsteady wall pressure sensors on a bulb turbine draft tube was performed over the power and efficiency break off range of a N 11 curve. This study is part of the BulbT project, undertaken by the Consortium on hydraulic machines and the LAMH (Hydraulic Machine Laboratory of Laval University). The chosen operating points include the best efficiency point for a high runner blade angle and a high N 11 . Three other points, with the same N 11 , have been selected in the break off zone of the efficiency curve. Flow conditions have been set using the guide vanes while the runner blade angle remained constant. The pressure sensors were developed from small piezoresistive chips with high frequency response. The calibration gave an instrumental error lower than 0.3% of the measurement range. The unsteady wall pressure was measured simultaneously at 13 locations inside the first part of the draft tube, which is conical, and at 16 locations in the circular to rectangular transition part just downstream. It was also measured at 11 locations along a streamwise line path at the bottom left part of the draft tube, where flow separation occurs, covering the whole streamwise extent of the draft tube. For seven radial-azimuthal planes, four sensors were distributed azimuthally. As confirmed by tuft visualizations, the break off phenomenon is correlated to the presence of flow separation inside the diffuser at the wall. The break off is linked to the appearance of a large recirculation in the draft tube. The efficiency drop increases with the size of the separated region. Analysis of the draft tube pressure coefficients confirms that the break off is related to diffuser losses. The streamwise evolution of the mean pressure coefficient is analyzed for the different operating conditions. An azimuthal dissymmetry of the mean pressure produced by the separation is detected. The pressure signals have been analyzed and used to track the separation zone depending on the operating conditions. Spectral analysis of these signals reveals a low frequency unsteadiness generated by the flow separation.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".