Simulation of Submerged Slack Tethers and Their Interaction With the Environment
Bibliographic record
Abstract
Tethered systems, underwater or otherwise, are nowadays used for very diverse tasks. Due to the complexity of such systems, it is necessary to simulate them for design, operation and training purposes. This paper deals with an approach to simulation of tethered systems, in particular underwater remotely operated vehicles (ROVs), by incorporating contact forces acting between the tether and the environment into the dynamic model of the tether. This will ensure model fidelity when the tethered system is operated in a dense environment. In this paper, methods used to compute contact forces are described. In the calculation of contact dynamics, the distance between the tethered system and the environment is of utmost interest. Algorithms to determine the separation distance between the tether and the environment are discussed in the scope of this work. These algorithms are then incorporated into an existing dynamics model of the ROV tether. Finally, this paper concludes with a simple numerical example where a tether is moved in a concave environment. The distance between the tether and the environment is computed as the tether’s location and three-dimensional profile change with time.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".