Modelling and Simulating Unsteady Six Degrees-of-Freedom Submarine Rising Maneuvers
Bibliographic record
Abstract
Abstract : DRDC Atlantic is collaborating with ANSYS Canada and the University of New Brunswick to develop an unsteady, six degrees-of-freedom, Reynolds Averaged Navier-Stokes (RANS) submarine maneuvering simulation capability. Initially, this is being used to evaluate emergency rising maneuvers. During these maneuvers, high negative angles of attack can occur which result in a roll instability not previously predicted by quasi-steady modelling. The objective of the RANS simulation is to reproduce the instability and investigate mitigation strategies. Models for weight and buoyancy when blowing, high incidence propulsion, and appendage and propulsion activation are presented and tested. A high incidence, quasi-steady, coefficient based hydrodynamic model used in previous stability analyses is also presented. These models are used for evaluating stability, testing the system models, and investigating different maneuvering scenarios in preparation for carrying out the computationally intensive RANS simulations. These preliminary investigations suggest the initial roll angle prior to blowing ballast, coupled with the roll instability and low pitch angles, plays an important role in the emergence roll angle.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".