Design of a Variable Camber Morphing Winglet with Composite Lamination Structural Analysis and Failure Analysis – Application to the UAS-S45
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-1584.vid The purpose of this study is to design a variable camber morphing winglet with a composite laminate structure for the UAS-S45. The camber morphing winglet will be designed using a honeybee-inspired abdomen structure for the deformation mechanism. It was found that the morphing winglet could improve wing aerodynamic efficiency compared to its reference geometry. The leading edge and trailing edge deflections of the proposed morphing winglet design were generated by the bending and flexing motion mechanism represented by a honeybee abdomen and a flexible wing skin. The controlled winglet deformation was achieved by linear servos that stretched and retracted the flexible mechanism. The morphing winglet was controlled by three servos. The kinematic working mechanism will be presented in the study. The stress analysis is also performed on composite laminates winglet under various loads, used as pre-analysis data. A laminate with a stacking sequence of [0/90/±45/90/0] s was calculated in detail using the Classical Lamination Theory (CLT). The analysis consisted in the comparison of two materials, carbon epoxy and Glass Fibre Reinforced Plastics (GFRP). Ansys ACP was used to model the geometry, while Ansys Mechanical was utilized to model the loading cases and to perform the stress analysis to confirm the results. A demonstrative mechanism for morphing winglet was manufactured of thermoplastic polylactic acid (PLA), and its deformations were measured. The structural optimization analysis results will be presented, and investigated, therefore the optimization will result in a better orientation of composite lay-up and will minimize the morphing winglet weight.
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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 | 0.000 | 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) | 0.001 | 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".