Dragonfly Preparation for Powered Flight Wind Tunnel and CFD Modeling
Bibliographic record
Abstract
Preparation for Powered Flight (PPF) is a critical phase for Dragonfly, the National Aeronautics and Space Administration (NASA) mission to Saturn’s moon Titan. During PPF the descending Lander is lowered below the Backshell and uses its rotors to remove or “despin” any residual yaw motion of the vehicle. A 1/2-scale model of the Dragonfly PPF configuration was tested in the National Full-Scale Aerodynamics Complex (NFAC) 80 by 120-foot wind tunnel to measure aerodynamic loads and surface pressures on the Lander and Backshell. The results were used to improve understanding of the complex aerodynamic interactions and provide validation data for the Computational Fluid Dynamics (CFD) simulations used to develop the aerodynamic databases for full-scale, Titan conditions. Configurations tested in the wind tunnel included Lander-alone-no-rotors (L), Lander-alone-with-rotors (LR), and Lander-with-Rotors-and-Backshell (LRB). Both LR and LRB configurations were tested at multiple descent velocities and pitch and roll attitudes. The eight powered rotors were operated in nine combinations of active and inactive rotors, using steps of increasing RPM from idle to maximum. The results were used to identify conditions that generated the desired yaw moment for despin as well as those that generated reduced or opposite sign moment. In parallel, CFD simulations applied the STAR-CCM+ toolset to the experimental geometry. Time-averaged virtual disks represented the rotors by adding spatially varying axial and rotational momentum to the flow. There was generally good agreement between experiment and CFD, but conditions having strong interactions between the rotors, Lander, and Backshell were found to be improved by use of more sophisticated time accurate and discrete blade models. The lessons from the experiment are being applied to the CFD for the full-scale Lander under Titan conditions.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
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".