A VPM/CFD Coupling Methodology to Study Rotor/Ship Aerodynamic Interaction
Bibliographic record
Abstract
The air disturbance (or airwake) resulting from the interaction of ship motion and air flow, has a significant effect on shipboard rotorcraft operations. It is essential to develop capabilities to accurately model the rotor/ship aerodynamic interactions which can subsequently be used to implement an efficient and accurate virtual dynamic interface (VDI) simulation. The aerodynamic interaction of the rotorcraft and ship involves the mutual interference between the rotors, fuselage and ship structure. The ship airwake produces unsteady loads on the helicopter as a result of shear layers and turbulence. Therefore modeling rotor/ship aerodynamic interaction requires a high fidelity approach due to complex physical mechanisms that drive the flow phenomena. The interactions between rotor and ship have known to be highly non-linear, therefore the airwake due to an isolated ship has different flow characteristics compared to the ship airwake in presence of a rotorcraft. Moreover the coupled airwake has a feedback effect on the rotor wake geometry and vorticity strength which creates a two-way coupling scenario. In this study, a methodology was developed to couple a CFD ship airwake solver with a viscous Vortex Particle Method (VPM) for rotor wake solution to study rotor/ship aerodynamic interaction. The CFD and VPM solvers were used to compute the time accurate ship airwake and rotor wake, respectively, from first principles. This coupling methodology is demonstrated for a helicopter ground effect study. The coupling simulations were subsequently run for helicopter performing shipboard operations. The simulations showed the complex interactions of ship airwake with rotor wake including the ground effect that rotor experiences in the vicinity of the deck.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".