论文标题
机械超材料执行器的自动设计
Automatic Design of Mechanical Metamaterial Actuators
论文作者
论文摘要
机械超材料执行器实现了预定的输入 - 输出操作利用了在单个3D打印元件中编码的架构特征，从而消除了组装不同结构组件的需求。尽管该领域取得了迅速的进展，但仍然需要有效的策略来优化各种功能的超材料设计。我们提出了一种用于自动设计机械超材料执行器的计算方法，该方法将增强的蒙特卡洛方法与离散元件模拟相结合。所选机械超材料致动器的3D打印表明机器生成的结构可以达到高效率，超过了人工设计的结构。我们还表明，可以通过训练深层神经网络来设计有效的执行器，从而消除了对冗长的机械模拟的需求。可以将这里设计的基本致动器合并，以生成无数工程应用的任意复杂性的超材料机器。
Mechanical metamaterials actuators achieve pre-determined input--output operations exploiting architectural features encoded within a single 3D printed element, thus removing the need of assembling different structural components. Despite the rapid progress in the field, there is still a need for efficient strategies to optimize metamaterial design for a variety of functions. We present a computational method for the automatic design of mechanical metamaterial actuators that combines a reinforced Monte Carlo method with discrete element simulations. 3D printing of selected mechanical metamaterial actuators shows that the machine-generated structures can reach high efficiency, exceeding human-designed structures. We also show that it is possible to design efficient actuators by training a deep neural network, eliminating the need for lengthy mechanical simulations. The elementary actuators devised here can be combined to produce metamaterial machines of arbitrary complexity for countless engineering applications.
