Abstract
The Flying-V aircraft concept promises better fuel-burn performance over conventional tube-and-wing configurations, integrating the passenger cabin and cargo volume into the lifting surface. However, the wing-fuselage and cockpit windows of the Flying-V are exposed to the flight direction, posing a new challenge to the design and certification of structures in terms of bird strikes. This study is a first step towards understanding the dynamic load path and contribution of each structural element on the bird strike resistance of the Flying-V leading-edge structures. The objective is to propose a building block approach to design the Flying-V's leading edge bird strike crashworthiness that complies with the EASA's certification CS25.631 using a 4lb bird impacted at a sea level cruising speed of 70 m/s. An additional requirement by the authors is to keep the structure within the elastic deformation during the impact of a 4lb bird to avoid the need for repairs in the Flying-V fuselage. Plasticity generated in the structure is regarded as damage and is used as a comparative parameter. At the highest building block level, a sensitivity analysis is performed to identify the effect of the thickness of each structural element on the plasticity and weight of the leading-edge structures. The trends are used to modify the baseline design and achieve a reduction of 80% of the plastic energy. The critical case of a 133 m/s impact of a 4lb bird at the cruise altitude of 37000 ft is also evaluated, and the results show penetration.
Original language | English |
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Article number | e14723 |
Number of pages | 41 |
Journal | Heliyon |
Volume | 9 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2023 |
Keywords
- Aircraft design
- Bird strike
- Blended wing-body
- Crashworthiness
- Design
- Flying wing
- Flying-V
- Metallic
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Data set for design for bird strike crashworthiness using a building block approach applied to the Flying-V aircraft
Chen, S. (Creator), van de Waerdt, W. (Contributor) & Giovani Pereira Castro, S. (Contributor), Zenodo, 1 Nov 2022
Dataset/Software: Dataset