Effect of Size and Mission Requirements on the Design Optimization of Non-Planar Aircraft Configurations
Bibliographic record
Abstract
Significant performance improvements can be achieved by aircraft configurations which make use of non–planar lifting surface arrangements to improved aerodynamic efficiency, reduced structural weight, and tailored flight dynamics and control characteristics. Potential improvements come at the price of a larger degree of inter–disciplinary couplings where non–aerodynamic considerations such as structural strength and weight characteristics need to be included in the overall design process. Furthermore, the effect that aircraft size, its mission, and its operational requirements have in these type of configurations need to be assessed. In this paper, we explore the multidisciplinary design and optimization of non–planar configurations, taking into account the coupling between aerodynamics and structures for different aircraft sizes and mission requirements. A very flexible representation of non–planar configurations is allowed and geometric, volumetric, aerodynamic, and structural characteristics are considered. Results show the performace effects and inter– disciplinary trade–offs that size and mission requirements impose on the design of these types of aircraft configurations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".