Development of small-scale unmanned hydrofoil boats
Bibliographic record
Abstract
Unmanned boats have gained a lot of interest in the maritime community during the last decade. Most hydrodynamic platforms employed for unmanned boats are based on traditional relatively simple hulls. In the present study, small-scale hydrofoil-assisted unmanned boats (0.6–0.7 m in length and 3.5–5.5 kg in mass) have been developed and tested. Design calculations using a hydrodynamic transverse-strip engineering method with semi-empirical correlations were applied to determine suitable dimensions for hydrofoil systems. The boat hulls and hydrofoils were fabricated by laying up carbon-fiber cloth sheets on foam cores or 3-D printed profiles. The boats were instrumented with outboard propulsors and electronic equipment for operations in both remote control and autopilot modes. In addition, an in-situ thrust-measuring module was designed and installed at the hull sterns to gather thrust data at GPS-measured speeds in the range between 0 and 11 m/s. The developed boats proved to be robust platforms capable of going over 600 m distances at high speeds while autonomously following preset paths. The presented methods and results can assist engineers developing unmanned surface vehicles that utilize advanced hydrodynamic concepts.
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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 | 0.000 |
| 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) | 0.001 | 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".