An End-to-End Methodology for CFD-based Parametric Optimisation of Propeller Boss Cap Fins
Bibliographic record
Abstract
This research investigates the reduction in fuel consumption in the marine industry by reducing hub-vortex-related losses downstream of propellers using strategically placed fins.This study focuses on the parametric optimization of Propeller Boss Cap Fins (PBCFs) to establish the relationship between key design parameters and overall propeller efficiency.An ANSYS CFX-based CFD model was used to evaluate the impact of the various parameters on the overall efficiency.The variation in different parameters and their effects on efficiency are recorded and detailed in this paper.Furthermore, we present an end-to-end methodology that enables users to optimise their PBCF design for maximum efficiency.Our results show that the radius ratio has a dominant influence on efficiency due to eddyinduced losses, with the optimal configuration corresponding to the lowest feasible r/R, while phase angle variations have a marginal effect.This research contributes to the ongoing efforts to enhance marine propulsion efficiency, reduce fuel consumption, and mitigate environmental impact.
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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".