Design and Manufacturing of Biologically Inspired Micro Aerial Vehicle Wings Using Rapid Prototyping
Bibliographic record
Abstract
Micro Aerial Vehicles (MAVs) are an emerging class of uninhabited aerial vehicle (UAV). Their reduced scale (maximum dimension of approximately 150 mm) provides advantages in terms of advanced mission capabilities, such as wildlife monitoring and urban search and rescue. This introduces the design challenge of flying efficiently at very low Reynolds numbers (e.g. Re<10000). To date, three basic MAV design concepts have been developed: fixed, rotary and flapping wings. Each approach has been met with limited success due to gust stability, flight control and propulsive efficiency. The design of both fixed and rotary wing aircraft is relatively mature, whereas flapping wing design is in its infancy and therefore its viability cannot yet be assessed. Nonetheless flapping wing MAVs have the potential to offer advantages such as stealth, manoeuvrability, and improved propulsive efficiencies. This paper focuses on the challenging problem of the manufacture and testing of flapping wings for MAVs. A review of the current state of flapping wing aerodynamics, manufacturing, and wing structures is provided. A detailed assessment of the aerodynamic performance of flexible MAV-scale wings was carried out. Aerodynamic force measurements were collected using a spin rig to assess the effect of design details on lift generation. It was found that a simple three-vein wing structure manufactured using a fused filament fabrication 3D printer could produce lift forces close to those of natural insect wings. The lift and stall performance was found to be sensitive to chordwise stiffness by testing wings without veins. These results demonstrate that it is possible to produce low cost biologically inspired wings with aerodynamic performance equal to or better than natural wings – a critical step on the path to a functional and practical flapping wing MAV.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".