<p style="text-align: justify">Soft materials have emerged as promising candidates in various applications such as soft robotics, sensors, and actuators.&nbsp;Topology optimization is a powerful computational method for finding optimal structural topologies and material microstructures, making it a promising tool that explores the design space of topology and material heterogeneity.&nbsp;To enable a systematic paradigm to design soft metamaterials and metastructures with programmable behaviors,&nbsp;this talk will first introduce a general multi-material topology optimization framework considering both&nbsp;material nonlinearity and&nbsp;finite deformations.&nbsp;The inverse design framework simultaneously optimizes both the topology&nbsp;and material composition of a structure&nbsp;to achieve the target performance.&nbsp;&nbsp;The proposed formulation can handle an arbitrary number of candidate hyperelastic materials with isotropic and anisotropic behaviors. This capability is achieved by novel design parametrization and general stored-energy interpolation schemes, which account for candidate material phases with distinct properties (such as hardening, softening, isotropic, and anisotropic behaviors). We explore various objective functions and generalized settings of local and global constraints to enable more design freedom and functionalities. To&nbsp;effectively&nbsp;solve optimization problems with an arbitrary constraint setting, we derive novel design update schemes that handle design variables associated with each constraint independently in parallel.&nbsp;We also employ&nbsp;several techniques to solve&nbsp;the&nbsp;highly nonlinear state equations&nbsp;efficiently and robustly. The generality and effectiveness of the proposed framework are demonstrated through illustrative benchmark examples, which verify the robustness of the framework to handle soft composite materials under large deformations as well as the capability to find the optimal topology and select the proper type of materials.</p><p style="text-align: justify">Next, we tailor the proposed multi-material topology optimization framework to systematically design metastructures with programmable nonlinear elastic responses under finite deformations. The design procedure is formulated as an inverse problem where the errors between the actual and the prescribed force-displacement curves are minimized. The framework harnesses multiple hyperelastic materials with distinct constitutive relations, which enlarge the design space of programmable behaviors compared to the single-material setting. We present several numerical design scenarios in which we discover metastructures that achieve a variety of programmed load-displacement curves, some of which are physically unattainable with single materials. The optimized metastructures exhibit unconventional geometries and multi-material distributions, and reveal distinct deformation mechanisms, such as converting deformation modes from flexure-dominated to stretch-dominated. We further manufacture the topology-optimized metastructures and present experimental validations to demonstrate excellent agreement between their actual load-displacement curves and the target ones. &nbsp;Finally, we conclude this presentation with a brief demonstration of the extension of the proposed framework to soft active material design under multi-physics actuation.&nbsp;</p>

Programmable Soft Metastructures via Multi-Material Topology Optimization-Part I

Paper Proceedings: https://asmedigitalcollection.asme.org/IMECE/IMECE2021/volume/85543

ASME 2021 International Mechanical Engineering Congress and Exposition (IMECE2021)

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