Hydrodynamic performance evaluations of domestic fishing vessels for cleaner and quieter operations
Bibliographic record
Abstract
This research aims to systematically evaluate the impacts of hull forms, propellers, rudders, and other appendages on domestic vessels' hydrodynamic and URN performance. The study also seeks to improve understanding of the hydrodynamic interactions between the hull, propeller, rudder and appendages and the resulting impacts on performance efficiencies, GHG and URN emissions of Canadian domestic boats. As a crucial first step, the research team selected and physically modelled two representative Atlantic Canadian fishing vessels at suitable scales. The team utilized comprehensive suites of physical modelling facilities and techniques to conduct the investigations on the hydrodynamic performance evaluations of the fishing vessels at realistic operating conditions in terms of bare and appended hull resistance, powering predictions using self-propulsion tests, free running maneuvering and seakeeping performance. This paper presents selected outcomes of the measurements we acquired through the physical modelling campaign on the powering and manoeuvring performance variations due to changes in commonly used hull appendages and propeller-rudder configurations. The hull appendages and rudder types are found to have significant impact on the overall powering and maneuvering performance of the fishing vessel. This work is expected to generate knowledge and improve understanding to investigate the interactions of the vessel, propeller, rudder, and other appendages regarding hydrodynamic performance. The study will also provide support and solutions for the communities regarding the (optimized) design and construction of domestic vessels and provide insights into how professional and technical improvements can benefit vessel operations.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".