Experience with location of cavitation emission measurement
Bibliographic record
Abstract
Abstract The OSC Hydro Power Group has carried out many performance tests on various types of hydraulic machines. Scan of ultrasonic cavitation emission has been often part of these tests. In addition to the principle used (in our case, modulation of the ultrasonic emission of flowing water by imploded bubbles), also the ultrasonic sensor placement on the turbine body has an influence on the cavitation sensing success and reliability of measurement results. This paper presents our experience with cavitation measurements at various locations in the turbine body. Our effort was always to install the contact microphone as close as possible to the point where the cavitation had a typical manifestation (surface greying, material loss). These positions are often located in concreted parts (e.g. runner chamber) usually inaccessible for sensors. Due to the fact, it is necessary to place the sensors at the locations where at least part of the cavitation implosion occurs. We present recommendations, supported by many real tests, where optimal results can be expected. The results of the determination of cavitation zones are supported by examples from measurements mainly on Kaplan but also Francis turbines, which helped to protect them from cavitation damage by excluding operation in hazardous areas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".