Numerical analysis of the performance and drag reduction mechanisms of outboard horizontal stabilizers
Bibliographic record
Abstract
The Outboard Horizontal Stabilizer (OHS) configuration is a unique fixed-wing design that is often used when a traditional tail is impractical and has been proposed in the past as a means to achieve enhanced range and endurance. This study utilized a mixture of numerical approaches to quantify and critically examine the potential performance gains of the OHS concept. A modified non-linear lifting-line approach incorporating wing interactions was used for a fast low-fidelity model and Reynolds Averaged Navier Stokes simulations were completed using OpenFOAM®. A representative small-scale wing-tail combination was arranged into traditional, outboard, split, and extended span configurations and was used as a case study. The results obtained in this work demonstrate a substantial increase in lift-to-drag ratios for the OHS when compared to configurations with a similar main wing span. However, it was observed that simply extending the main wing to the overall span of the OHS configuration yielded higher performance. The lifting line approach was also utilized to explore the lift and drag performance of the chosen OHS case study when considering static stability and trim. The results show that the potential performance advantages of the OHS configuration are closely tied to static margin. Without careful consideration of the center of gravity location and neutral point, an OHS configuration may perform worse than a conventional configuration. Furthermore, the specific conditions that can lead to increased overall lift, and reduced induced drag on the stabilizers are highlighted and discussed. • Outboard stabilizers can yield improved lift to drag ratio compared to traditional. • Modified lifting line method produced similar results to RANS. • Increased wingspan is preferred over outboard stabilizers. • Primary mechanism of drag reduction is reduced induced drag due to wake superposition. • Stabilizer drag reduction inherently linked to static margin and trim.
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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 | 0.001 |
| 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 | 0.001 | 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".