Ground Based Simulation of Airplane Upset Recovery Using an Enhanced Aircraft Model
Why this work is in the frame
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Bibliographic record
Abstract
Loss-of-control has become the dominating cause of worldwide commercial airplane accidents in recent years. Airplane upset, which could result in loss-of-control, is a situation where the aircraft goes beyond the normal ight envelope. In response to the increasing number of loss-of-control accidents resulting from airplane upsets, various preventative and recovery strategies have been proposed in the industry. One strategy considered is using ground-based ight simulators for upset recovery training. However, for the training to be meaningful, improvements must be made to the ight model aerodynamic database and the motion cues produced at upset conditions. The on-going research at the University of Toronto intends to address both of these areas with the ultimate goal to develop simulator requirements to support meaningful upset recovery training. As the rst step in the research, the aerodynamic database of an existing large transport aircraft model was extended to cover a much larger ight envelope using the wind-tunnel data from NASA Langley Research Center. This enhanced aircraft model was then used to run a set of representative upset recovery maneuvers in the simulator without motion. The time histories recorded from these upset recovery maneuvers will be used to outline areas of improvements required to the simulator motion drive algorithm (MDA) for supporting upset motions. This paper will focus on the development of the aircraft model and the simulator upset recovery experiments.
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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 | 0.000 | 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 it