Performance aspects of podded propulsor in dynamic operating conditions
Bibliographic record
Abstract
This paper presents various aspects of propulsive performance of a dynamic azimuthing puller podded propulsor in open water condition derived from an experimental research. A model podded propulsor was instrumented to measure thrust, torque and rotational speed of the propeller, three orthogonal forces and moments, azimuthing angle and azimuthing rate of the unit. Experiments were carried out in which the azimuthing angle was varied dynamically at multiple azimuthing rates and propeller rotational speeds for different advance speeds. The model podded propulsor was capable of azimuthing or yawing continuously in the range of −180° to +180°, 0° (straight-ahead) being the design operating condition and positive azimuthing means a counter-clockwise rotation. The performance coefficients of the propeller and the pod unit showed a strong dependence on the propeller loading and azimuthing angle. The open water characteristics were mostly irregular for the astern thrust conditions in the azimuthing angle beyond the normal inflow condition and the fluctuation of the magnitude of the performance coefficients showed a considerable range. The azimuthing rate showed little or no effect on the performance coefficients in the range of azimuthing angles examined. Both at high and moderate propeller loading conditions, an increase in the shaft speed resulted in slight change in the performance coefficients and the change was more obvious as the azimuthing angle was increased. The increase in the performance coefficients due to the increase of propeller shaft speed was not noticeably affected by the change of azimuthing rate.
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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".