Generating Pre-swirl Using Mesh Deformation
Bibliographic record
Abstract
The Orca-class vessels of the Royal Canadian Navy are equipped with an open shaft arrangement that consists of three foil-shaped brackets: two that extend from the hull to support the propeller and shaft and a third that extends downwards from the hub. All brackets are located slightly forward of the propeller disc and therefore affect the propeller inflow. By manipulating the radial pitch distribution of these brackets, pre-swirl can be generated to counteract propeller induction and potentially reduce the energy lost to flow rotation. Rather than manually rotating the brackets using a computer-aided-design tool, mesh deformation is employed to twist the brackets using a single baseline geometry and mesh. The pitch distributions of the brackets are parameterized to facilitate a simplified design space exploration to determine if performance benefits can be realized in terms of power delivered and cavitation generation. Coupled viscous and potential flow calculations are used to consider the influence of the rotating propeller on the aft-ship region. Furthermore, a simplified one-way alternative is shown to provide similar results with a reduced computational requirement when compared to the typical iterative approach. In the preliminary design space exploration, it was found that applying twist to the outboard bracket permits a slight power reduction over the baseline case but comes with an associated penalty in cavitation behaviour.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".