Risk analysis of an Autonomous Surface Craft for operation in harsh ocean environments
Bibliographic record
Abstract
Risk analysis of an Autonomous Surface Craft (ASC) is a very important subject since it is closely related to the safety of an ASC operating in harsh ocean environments. In this study, we provide a detailed analysis of the primary disturbance of ocean waves and its influence on an ASC's roll motion. A conventional decoupled nonlinear roll motion model has been chosen and through experiments the roll motion model parameters are successfully identified. Using this model, we perform extensive simulations under different assumed wave conditions. Our analysis is based on the well-known erosion basin technique in phase plane. The safe region proportion has been defined to serve as a safety criterion. Through analysis, we find out that the safety of an ASC operating in the ocean is related to the wave amplitude and wave encounter frequency. This relationship provides a useful reference for risk analysis of an ASC. The results provided can be regarded as guidelines for an ASC's safety determination, and thus they are planned to be integrated into an ASC for its self safety awareness. The presented method can also be extended to other medium-size or large marine vessels for their operational safety analysis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".