Abstract
Designing lighter airframes is one of the crucial pursuits of aviation for structural and operational efficiency. Owing to the expansion of the boundaries for manufacturing technologies, the utilization of exotic structures inspired by nature in aviation has gained popularity in recent years. In this study, a bio-inspired structural stiffening concept employing Voronoi cells is proposed to reinforce a fuselage panel subjected to compression loads. In this regard, a genetic optimization algorithm based on artificial neural networks (ANNs) is used to establish the optimized design of Voronoi cell reinforced fuselage panels with minimum weight. Since stiffening with Voronoi cells causes serious nonlinearity in the estimation of buckling strength, a layer/neuron count optimization scheme consisting of nested loops and condition blocks is developed for each panel with different local Voronoi cell densities. Comparisons with conventional panel stiffeners such as isogrid, orthogrid and stringer structures demonstrate that Voronoi-type stiffeners provide much lighter design solutions at the same critical buckling load levels. Additionally, it is also presented that the advantage of Voronoi cell reinforcements significantly increases as the critical buckling load level increases. Therefore, the results provided in this study signify a great potential for the usage of Voronoi cells as bio-inspired stiffener members for lightweight structural designs.
Original language | English |
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Article number | 107923 |
Journal | International Journal of Mechanical Sciences |
Volume | 240 |
DOIs | |
Publication status | Published - 15 Feb 2023 |
Bibliographical note
Publisher Copyright:© 2022 Elsevier Ltd
Keywords
- Artificial neural networks
- Buckling
- Fuselage panels
- Optimization
- Voronoi cells