Flying Qualities Prediction Tool for Aerial Refuelling Operational Compatibility Assessment
Bibliographic record
Abstract
Air-to-air refuelling is a common operational practise in military aviation, and is used both to extend mission length and reduce total fuel consumption for long-haul missions. Clearing tanker and receiver aircraft pairs for aerial refuelling is an extensive process that requires a combination of analysis and flight testing. In order to develop further tools with which to analyse aerial refuelling, this paper presents the continued development of a fully coupled vortex lattice method representation of two aircraft in close formation flight which is used to calculate the frequency and damping of a receiver aircraft's long period, short period, and Dutch Roll during aerial refuelling. These flight dynamics quantities are then used to predict the flying qualities during air-to-air refuelling. This paper examines the case of a F/A-18 being refuelled by both a C-150 Polaris and C-130 Hercules tanker aircraft. At the refuelling point of both tankers, the results predict a reduction in long period natural frequency, an increase in long period damping, an increase in short period natural frequency and damping, a decrease in Dutch Roll natural frequency, and an increase in Dutch Roll damping. This is predicted to result in Level 2 flying qualities during refuelling.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".