Cavitation performance testing of podded propellers with different hub taper angle
Bibliographic record
Abstract
This study presents the experimental study of some podded propellers with different hub geometry. The experiments were conducted in the cavitation tunnel at Institute for Ocean Technology (IOT), NRC Canada. Four model propellers having the same blade sections but different hub geometry were designed and manufactured and tested at different cavitating conditions. The objective was to investigate the variations of propulsive performance and cavitation characteristics of the propellers because of different hub geometry. Tests were done in various combinations of flow velocity, propeller rotational speed and tunnel pressure. All of the propellers were tested in a wide range of advance coefficients and cavitation numbers to measure propeller thrust and torque. Reynolds Number effects on performance at design cavitation number, effect of hub taper angle on cavitation inception and comparison of performance under various cavitation conditions were investigated. The study gives a suitable basis for comparison of pusher and puller propellers' performance (propeller only case) under cavitating conditions. It is concluded that the puller configuration propellers had better performance than the pusher configuration propellers under majority of test conditions. Results also show that hub taper angle does not have noticeable effect on visual cavitation inception and desinence.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".