Further Development and Piloted Simulation Evaluation of the Break Turn ADS-33 Mission Task Element
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 (FVL) platform of the US Army. The US Army's National Rotorcraft Technology Center (NRTC) project "Rotorcraft Handling Qualities Requirements for Future Configurations and Missions" is a U.S. Government and Industry co-funded three year research project. A Sikorsky-led project team that features industry and academia have developed and evaluated a set of Mission Task Elements (MTEs) that are defined to address rotorcraft 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. Break Turn MTE was defined for non precision, aggressive applications in order to provide a suitable coverage of aggressive air combat maneuvers in future ADS-33. The MTE objectives, descriptions, and performance criteria were systemically developed via a series of piloted simulation sessions at each team's simulation facility. Formal evaluations were then conducted by US Army test pilots at four simulator facilities, each featuring a unique high-speed platform including an X2 Technology™ compound helicopter, two tiltrotor configurations, and a generic winged compound helicopter. To enhance the MTE evaluation process, baseline control law (CLAW) 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 Break Turn MTE provided an effective means to discern non-precision, aggressive handling qualities in high speed flight.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".