Mechanical cloak via data-driven aperiodic metamaterial design

Abstract

Significance An invisibility cloak to conceal objects from an outside observer has long been a subject of interest in metamaterial design. While cloaks have been manufactured for optical, thermal, and electric fields, limited progress has been made for mechanical cloaks. Most existing designs rely on mapping-based methods, which have so far been limited to special base cells and a narrow selection of voids with simple shapes. In this study, we develop a fundamentally different approach by exploiting data-driven designs to offer timely, customized solutions to mechanical cloaking that were previously difficult to obtain. Through simulations and experimental validations, we show that excellent cloaking performance can be achieved for various boundary conditions, shapes of voids, base cells, and even multiple voids.

Mechanical Cloaking of Cutouts in Laminated Plates

“…However, the concept of altogether cloaking, masking or concealing the mechanical effects of cutouts on laminated plates by the fiber steering concept has received little attention. The idea of mechanical cloaking has received investigation from the field of metamaterials by material design to directly influence the elastic response of loaded structures, which has been investigated by Wang et al [21]. Wang et al's method concurrently optimized the topology and properties to produce aperodic structural cloaking configurations for several boundary conditions [21].…”

“…The idea of mechanical cloaking has received investigation from the field of metamaterials by material design to directly influence the elastic response of loaded structures, which has been investigated by Wang et al [21]. Wang et al's method concurrently optimized the topology and properties to produce aperodic structural cloaking configurations for several boundary conditions [21]. Wang et al's design configuration, for a plate with central circular hole under displacement loading, achieved a 4% difference in directional spatial displacement fields when cloaked, compared to 17.2% when uncloaked [21].…”

Growth rules for irregular architected materials with programmable properties

“…Irregular microstructures can be designed to present heterogeneous distributions of local elastic properties ( 40 ). For nonperiodic architected materials that are designed from a database of unit cells ( 24 ), tessellating different structures and constituent materials while ensuring connectedness and compatibility is challenging ( 25 , 40 , 41 ). By using the virtual growth program, designing materials with inhomogeneous properties is possible with a single, continuous process by assigning different frequency hints to different regions of the sample.…”

t-METASET: Tailoring Property Bias of Large-Scale Metamaterial Datasets through Active Learning

“…The framework handles data bias reduction (for generic use) and design quality (for particular use) simultaneously, by leveraging diversity and quality as the sampling criteria, respectively. We advocate that (i) building a good dataset should be an iterative procedure; (ii) diversity-driven sampling [18] can efficiently suppress the property imbalance of multi-dimensional regression that most DDMD is involved with [11]; (iii) property diversity significantly improves fully aperiodic metamaterial designs, as have been shown by recent reports [15,19,20,21]. Distinct from existing work, however, we primarily seek a solution to an commonplace -yet frequently overlooked -scenario that designers face during data preparation: we wish to collect or generate a large-scale shape dataset without any property evaluated at the start, while also aiming to acquire a uniform or a controlled task-aware property/shape distributions.…”