Piloted Simulation Evaluation of Tracking MTEs for the Assessment of High-Speed Handling Qualities
Bibliographic record
Abstract
Updates to the military rotorcraft handling qualities specification are currently being considered that address the high-speed flight regime envisioned for the Future Vertical Lift platform of the US Army. A team that features industry and academia have developed and evaluated a set of Mission Task Elements (MTEs) that are defined to address VTOL high-speed handling qualities. Following the mission-oriented approach upon which ADS-33E-PRF is based, the MTEs were designed to meet different levels of precision and aggressiveness. Tracking MTEs based on a sum-of-sinewaves (SOS) command signal were defined for precision, aggressive and precision, non-aggressive applications. The command signals are derived from fixed wing analogs that have long been used to evaluate aircraft handling qualities. While the precision, aggressive SOS tracking tasks, the primary subject of this paper, are surrogates for air-to-air tracking and nap-of-the-earth tracking, the known forcing function allows for complete open- and closed-loop pilot-vehicle system identification. The MTE objectives, descriptions, and performance criteria were assessed and refined via several checkout piloted simulation sessions. Formal evaluations were then conducted by Army test pilots at four simulator facilities, each featuring a unique high-speed platform including a generic winged compound helicopter, two tiltrotor configurations, and a compound helicopter with coaxial rotors. To aid in the MTE evaluation process, baseline VTOL configurations were varied to achieve different handling qualities levels. Quantitative measures based on task performance and qualitative measures based on pilot ratings, comments and debrief questionnaires were used to assess MTE effectiveness. The piloted simulation results demonstrated that the sum-of-sines tracking MTEs provided an effective means to discern precision, aggressive handling qualities in high speed flight.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".