Experimental investigation of the draft tube inlet flow of a bulb turbine
Bibliographic record
Abstract
In the BulbT project framework, a bulb turbine model was studied with a strongly diverging draft tube. At high discharge, flow separation occurs in the draft tube correlated to significant efficiency and power drops. In this context, a focus was put on the draft tube inlet flow conditions. Actually, a precise inlet flow velocity field is required for comparison and validation purposes with CFD simulation. This paper presents different laser Doppler velocimetry (LDV) measurements at the draft tube inlet and their analysis. The LDV was setup to measure the axial and circumferential velocity on a radius under the runner and a diameter under the hub. A method was developed to perform indirect measurement of the mean radial velocity component. Five operating conditions were studied to correlate the inlet flow to the separation in the draft tube. Mean velocities, fluctuations and frequencies allowed characterizing the flow. Using this experimental database, the flow structure was characterized. Phase averaged velocities based on the runner position allowed detecting the runner blade wakes. The velocity gradients induced by the blade tip vortices were captured. The guide vane wakes was also detected at the draft tube inlet. The recirculation in the hub wake was observed.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".