Energy performance and flow characteristics of a slanted axial-flow pump under cavitation conditions
Bibliographic record
Abstract
Cavitation is a complex flow phenomenon that hinders the efficient, safe, and stable operation of hydraulic machinery. To investigate the effect of cavitation on energy performance and flow characteristics of hydraulic machinery, cavitating flow in a slanted axial-flow pump based on entropy production theory and vortex dynamics is studied. The results show that the impeller chamber is a primary region of cavitation and energy loss generation under different cavitation conditions, including the incipient, growing, and wedge-shaped cavitation stages. In the incipient cavitation stage, as degree of cavitation strengthens, the flow at the impeller blade is smooth with little cavitation, and the variation in entropy production is constant, resulting in a stable energy performance. As it evolves into the wedge-shaped stage, the cavitation grows from the tip region near the impeller blade to the hub. At this time, the entropy production increases in the impeller chamber, resulting in a drop in energy performance. Meanwhile, flow separation appears at the impeller blade, and a secondary tip leakage vortex is promoted. The region with high vorticity basically matches the region with the high local entropy production rate. According to the relative vorticity transport equation, compressibility of cavitation strongly affects the relative vorticity in the impeller chamber, indicating that cavitation indirectly increases entropy production and energy loss by affecting the vorticity distribution, resulting in the drop in energy performance.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".