Semi-Analytical and Empirical Approaches to Aircraft Configuration Effects on Post-Stall Aerodynamics - Invited
Why this work is in the frame
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Bibliographic record
Abstract
Loss-of-control due to aerodynamic stall continues to be the largest contributor to fatal civil aviation accidents. Improved ground-based simulator training for post-stall recovery training would therefore be of great benefit. Post-stall aerodynamic models of aircraft will be required to carry out meaningful post-stall traning. This study offers a way to develop a representative aerodynamic model that will capture the effect of aircraft configuration changes relative to a baseline model. In this document, first a literature review on the effects of aircraft configuration changes on stall aerodynamics is presented. Next, an overview of the basic methodology in carrying out the configuration changes is shown, followed by details on how some of the coefficients are generated. Lastly, a full scale example of the application of the method is provided. Results from the application of the proposed method shows good match with wind tunnel data.
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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