A design framework for gradually stiffer mechanical metamaterial induced by negative Poisson's ratio property

Gradually stiffer (GS) mechanical metamaterial is a novel kind of adaptive structures under nonlinear varying loads for cushioning and vibration damping in engineering. These man-made metamaterials in applications are usually tailored by trial-and-error. This study develops a design framework that integrates the topology optimization, parametric design and compression experiment for the GS mechanical metamaterials induced by the negative Poisson's ratio (NPR) property. Firstly, a parametric level set method is incorporated with the numerical homogenization method to topologically optimize a series of microstructural unit cells with different NPRs. Then, the nonlinear static analysis is respectively applied to different unit cells to check their GS behavior. Secondly, typical microstructures with GS property are selected and simplified to perform the subsequent parametric design to analyze the expected property. Thirdly, the obtained mechanical metamaterials are fabricated by using the additive manufacturing (AM). GS properties of the obtained designs are analyzed and verified by both the simulation and compression experiments. Results show that we could obtain the GS mechanical metamaterial based on NPR properties for their similar characteristics. This study demonstrates that the proposed design framework is effective to tailor innovative layouts of the GS mechanical metamaterials. (C) 2020 The Author(s). Published by Elsevier Ltd.