Acoustic-structure interaction in disk-disk configurations in water for high head pump-turbines
Bibliographic record
Abstract
Abstract Francis high-head pumps or pump-turbine runners often have speed and dimension ratios that make acoustic and structural natural frequencies, as well as rotor-stator excitation frequencies, approach each other. When compressibility effect becomes significant, it is not sufficient to only consider the incompressible added mass, which shifts the natural frequencies of the structure. The strong vibroacoustic coupling makes it difficult to distinguish the nature of each mode and the associated effect of the forced response amplification. The project’s main aim is to study a disk-disk system behavior in an acoustic cavity filled with water when the acoustic and structural frequencies are close, as a simplified model of a pump-turbine runner in its casing. It is demonstrated here that the compressibility significantly affects vibration modes of the system, particularly when individual acoustic and structural modes have similar frequencies and spatial coherence, resulting in an increase in energy transmission and a decrease in total natural frequency. Additionally, the system’s rigidity is affected by the cover’s stiffness; when the vibration frequencies of the cover and runner are similar, excitation transmission is divided between them.
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 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 | 0.000 |
| 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) | 0.002 | 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".