Dependability of the Explorer Autonomous Underwater Vehicle in Oil Plume Response Mission; Case Study of the Vehicle Roll Control
Bibliographic record
Abstract
Oil plume dispersion in water depth is an applied topic to study, and a practical way to respond to such a catastrophic event is to deploy an autonomous underwater vehicle (AUV) in the area. With notice that the underwater oil flows upward to the surface and in the meantime disperses into larger radii, a conical helix can be a suitable candidate for maneuvering about the oil spill.A helix maneuver requires steady control of the roll angle of the vehicle. Therefore, roll control adverse yaw, which originated in aviation, would be a concern for underwater navigation too. The correcting actuator signal that can adjust the vehicle's yaw angle, and therefore maintain its heading angle, shall be provided by the rudders or stern planes of the vehicle. Then the methodology of this research is to analyze the dependability of the rudder’s subsystem as a network of components in series. The dependability analysis that is performed here is in a series block diagram that is based on a minimal cut series. The results of this study show that the dependability of the engineering subsystems in an unmanned underwater vehicle can directly influence the outcome of a sensitive marine environmental protection project. Results show that the stern planes by more than a 90 percent chance can manage to control the maneuvering goals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".