机械超材料驱动器的自动设计
Automatic Design of Mechanical Metamaterial Actuators
摘要：
机械超材料致动器利用单个3D打印元件中编码的建筑特征实现预定的输入-输出操作，从而消除了组装不同结构部件的需要。尽管该领域取得了快速进展，但仍然需要有效的策略来优化用于各种功能的超材料设计。我们提出了一种计算方法的机械超材料致动器的自动设计相结合的增强蒙特卡罗方法与离散元模拟。选定的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，超过人类设计的结构。我们还表明，通过训练深度神经网络来设计高效的执行器是可能的，无需进行冗长的机械模拟。这里设计的基本致动器可以结合起来，为无数的工程应用生产任意复杂的超材料机器。
英文摘要：
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.
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