Hydrodynamic performance of marine propellers in steady and unsteady wake flows
Bibliographic record
Abstract
A marine propeller in unsteady wake flow is analyzed by using a potential-based boundary element method. Constant strength dipole and source distributions are used on each quadrilateral panel representing the propeller blades and their trailing vortex wakes. An analytical modification of Morino's method is adopted to determine the influence coefficients of source and dipole using hyperboloidal quadrilateral panels. This is very important to the accuracy of the solutions. An iterative pressure Kutta (IPK) condition is applied to ensure pressure equality at the trailing edge of the blade. First, calculations were conducted for a steady flow to confirm the accuracy and the capability of the present method. Next, the calculations of the unsteady flow due to the ship's wake were performed to calculate the fluctuating pressure acting on the propeller and consequently the thrust and torque. The thrust fluctuation for one blade and the whole propeller are presented. The method is demonstrated for two propellers, one corresponding to the conventional propeller and one for a highly skewed. The unsteady pressure distributions on the propeller blades determined by the method are in good agreement with experimental data from full-scale propellers.
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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 | 0.001 |
| 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".