AUTOMATED MARINE PROPELLER GEOMETRY GENERATION OF ARBITRARY CONFIGURATIONS AND A WAKE MODEL FOR FAR FIELD MOMENTUM PREDICTION
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Bibliographic record
Abstract
This paper first describes procedures and methodologies to automatically producemarine propeller geometry with optional auxiliary bodies such as nozzles, blockagesand rudders. This process is designed and implemented for a general boundaryelement method (the panel method) to deal with both lifting body and non-lifting bodyflows.The generated geometry is represented by quadrilateral and triangular panels thatcan be used by other mesh generation codes to produce 3D volumetric mesh for CFDwork. The vertices of these generated panels are set so that the normal of the surfacespoints inside the body. The order of the panels and their side indices are aligned fornumerical procedures such as differentiation of the perturbation doublet potential forsurface tangential velocities and Kutta condition at the trailing edge. A DXF fileformat was also implemented as one of the output files that can be used for propellermanufacturing via CNC and for commercial CFD codes that use geometry datainput.Based on the near field wake modeling studies performed by the authors and previousexperimental investigations on far wake turbulent jet measurements, a far wakemodel for a propeller panel method is implemented to enhance the capability ofpredicting the velocities and momentum impact on the risers under a floatingproduction storage off-loading (FPSO) system during operation. This far wake modelconsists of contraction wake (within one propeller diameter downstream), transitionwake (one to two diameters downstream), and inflation wake (two diameters beyond).Near field velocity prediction of this far wake model is validated using previous LDVmeasurement. Further experimental studies are scheduled for LDV/PIV measurementup to 20-diameter downstream.
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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 it