基于数据驱动的非周期性超材料设计的机械隐身
Mechanical Cloak via Data-Driven Aperiodic Metamaterial Design
摘要：
机械斗篷是一种材料，可以操纵物体周围的弹性反应，使它们与均匀的环境无法区分。通常，基于材料参数变换的方法用于设计光学、热和电斗篷。然而，它们不适用于设计机械斗篷，因为连续力学方程在一般坐标变换下不是形式不变的。因此，现有的机械斗篷设计方法迄今为止仅限于形状简单的狭窄空隙。为了应对这一挑战，我们提出了一个系统的，数据驱动的设计方法来创建由非周期性超材料组成的机械斗篷，使用一个大型的预先计算的单元格数据库。我们的方法是灵活的，允许设计各种边界条件，多种载荷，不同形状和数量的空隙，以及不同的均匀环境的斗篷。该方法可以同时优化隐身衣的拓扑结构和性能分布。与传统的固定形状解决方案相比，这导致整体更好的隐身性能，并提供无与伦比的多功能性。对3D打印结构的实验测量进一步证实了所提出方法的有效性。我们的研究说明了数据驱动方法在快速响应新的设计方案和解决与功能结构的多尺度设计相关的计算挑战方面的优势。它可以推广到其他需要异质属性分布的应用，如软机器人和植入物设计。
英文摘要：
Mechanical cloaks are materials engineered to manipulate the elastic response around objects to make them indistinguishable from their homogeneous surroundings. Typically, methods based on material-parameter transformations are used to design optical, thermal and electric cloaks. However, they are not applicable in designing mechanical cloaks, since continuum-mechanics equations are not form-invariant under general coordinate transformations. As a result, existing design methods for mechanical cloaks have so far been limited to a narrow selection of voids with simple shapes. To address this challenge, we present a systematic, data-driven design approach to create mechanical cloaks composed of aperiodic metamaterials using a large pre-computed unit cell database. Our method is flexible to allow the design of cloaks with various boundary conditions, multiple loadings, different shapes and numbers of voids, and different homogeneous surroundings. It enables a concurrent optimization of both topology and properties distribution of the cloak. Compared to conventional fixed-shape solutions, this results in an overall better cloaking performance, and offers unparalleled versatility. Experimental measurements on 3D-printed structures further confirm the validity of the proposed approach. Our research illustrates the benefits of data-driven approaches in quickly responding to new design scenarios and resolving the computational challenge associated with multiscale designs of functional structures. It could be generalized to accommodate other applications that require heterogeneous property distribution, such as soft robots and implants design.
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