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首页> 外文期刊>Journal of aerospace engineering >Two-Scale Topology Optimization of the 3D Plant-Inspired Adaptive Cellular Structures for Morphing Applications
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Two-Scale Topology Optimization of the 3D Plant-Inspired Adaptive Cellular Structures for Morphing Applications

机译：用于变形应用的三维植物启发自适应蜂窝结构的双模拓扑优化

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摘要

A novel two-scale topology optimization method is developed in this work to optimize three-dimensional (3D) plant-inspired fluidic adaptive cellular structures for morphing applications. In this method, the coupled mechanical behaviors of the 3D smart structures with fluidic cells are simulated by extended multiscale finite-element method. Multiscale base functions are constructed through the microscale computation to create the relationship between information of the single cells in the microscale and structural deformation in the macroscale. Furthermore, the 3D structural topology algorithm based on the power-low interpolation approach is combined with the multiscale method to improve the mechanical behaviors of the plant-inspired cellular structures. Consequently, the plant-inspired cellular structures can be designed by the proposed optimization method, in which the distribution of the motor cells is optimized to maximize the structural performance. Then, the smart structures based on fluid actuation of the cells can be optimized to create biomimetic compliant mechanisms, where self-actuated output displacements are set as the design objective. Moreover, the proposed two-scale optimization algorithm is investigated to optimize the number of liquid motor cells in order to minimize the weight of the cellular structure. Numerical examples including the design problems of morphing wings indicated that the two-scale topology optimization method can be effectively used to design the 3D plant-inspired cellular structures.
机译：在这项工作中开发了一种新颖的双模拓扑优化方法，以优化用于变形应用的三维（3D）植物鼓励流体自适应蜂窝结构。在该方法中，通过扩展的多尺度有限元方法模拟了利用流体电池的3D智能结构的耦合机械行为。多尺度基础功能通过微观计算构建，以创建单个小区信息之间的关系与Macroscale中的结构变形中的单个小区之间的关系。此外，基于功率低插值方法的3D结构拓扑算法与多尺度方法相结合，以改善植物鼓励蜂窝结构的机械行为。因此，可以通过所提出的优化方法来设计植物启发的蜂窝结构，其中优化电动机电池的分布以最大化结构性能。然后，可以优化基于细胞的流体致动的智能结构以产生仿生兼容机制，其中自致致动输出位移被设定为设计目标。此外，研究了所提出的双规模优化算法以优化液体电机单元的数量，以最小化蜂窝结构的重量。包括变形翼的设计问题的数值例表明，可以有效地用于设计三维拓扑优化方法来设计3D植物启发的蜂窝结构。

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