Experimental Comparison of Hydrodynamic Behavior Under Partial Flowrates and Cavitation in Three Configurations of a Centrifugal Pump With Inducer and Impeller
Bibliographic record
Abstract
Abstract This study aims at experimentally investigating the hydrodynamic behavior of a centrifugal pump, both with and without cavitation. The pump consists of an axial inducer, a centrifugal impeller, and a volute. Three assembly configurations are examined: the inducer alone, the impeller alone, and the combined inducer and impeller. Particular attention is given to cavitating conditions—low suction pressure—at four partial flowrates (4% ϕref, 16% ϕref, 39% ϕref, and 78% ϕref), where ϕref is defined as the flow coefficient for which the inducer has been designed. The hydromechanical performance is analyzed and compared across these configurations, with cavitation formation captured using high-speed digital imaging. A spectral analysis of pressure signals is also conducted in operational regimes where instabilities were observed. The results indicate that the inducer mitigates the impact of cavitation on hydromechanical performance as the flowrate approaches the design point ϕref. However, at partial flowrates, the inducer negatively impacts pump performance by increasing the critical cavitation number threshold beyond which a head drop occurs. Cavitation-induced instabilities were observed in partial flow regimes and under low suction pressure conditions in configurations involving the inducer. These instabilities, characterized by a very low-frequency signature, result in significant pressure and flow fluctuations, leading to vibrations within the system. Furthermore, these instabilities exhibit a clear dependency on flowrate.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".