Flow Fields Around The Tails Of Aircraft With Outboard Horizontal Stabilizers
Bibliographic record
Abstract
An application is studied of the outboard horizontal stabilizer (OHS) aircraft design concept to a high-altitude, long endurance (HALE) mission, uninhabited air vehicle (UAV). It was found that the OHS concept appears to be very well suited for the suggested mission because of the relative advantage, compared with a conventional UAV design, due to an improved lift/drag ratio over a wide range of lift coefficients implying that the benefits of improved performance, in lift/drag terms, would be available during both cruise to and from the surveillance site and during the loiter phase of the mission. A simplified, approximate, design process is presented that allows the expected lift/drag ratio of the aerodynamic surfaces to be estimated in an elementary manner. The all-important flow fields around the tail surfaces of a wind-tunnel model of the suggested OHS vehicle were explored using twodimensional PIV equipment. It was shown by this means, that the flows around the horizontal stabilizer surfaces generated by the wing-tip vortices, made it possible for the horizontal stabilizers to generate lift and, due to the upwash approaching these surfaces, this lift was obtained efficiently with offset of both the fictional and induced drags of the horizontal tails. In-flows about the vertical stabilizer surfaces generated, in a horizontal plane, lift forces acting primarily towards the vehicle vertical plane of symmetry but also inclined upwind. As a direct consequence of this a thrust component of the horizontally directed lift force also served to counteract the drag forces associated with the vertical tails.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".