Analysis of flying qualities for an F/A-18 aircraft
Bibliographic record
Abstract
The stability and control derivatives were calculated at NASA Dryden Flight Research Center DFRC laboratories for a number of 52 flight test conditions characterized by combinations of Mach numbers, altitudes and angles of attack for the longitudinal and lateral F/A-18 aircraft motion. More precisely, these different flight tests were considered at Mach numbers situated between 0.3 and 1.3, at altitudes between 1,000 ft and 40,000 ft and at angles of attack between 1° and 10°. Following two methods were used to calculate the characteristic system eigenvalues: the approximate method and the exact method. From these eigenvalues, by use of the classic vibration equation, the natural frequencies and damping were determined for the longitudinal and for the lateral aircraft motion. In case of the longitudinal aircraft motion, the flying qualities were evaluated for the long and short period of motion, while for the lateral aircraft motion, the flying qualities were evaluated for the roll, Dutch roll and spiral motions. From the values of frequencies and damping, based on aircraft class and phase, the flying qualities for the F/A-18 aircraft were determined. In this paper, is shown, for the first time in the literature, that relationships exist between flying qualities levels 1, 2 and 3 and flight conditions expressed in terms of Mach numbers, altitudes and angles of attack for the F/A-18 SRA (System Research Aircraft). These relationships are extremely helpful in detecting if intermediate stability and control derivatives are well calculated for flight tests intermediate 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".