Design Optimization for the Active Response of Liquid Crystal Elastomers
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Liquid crystal elastomers (LCEs) are responsive materials that can undergo large reversible deformations upon exposure to external stimuli, such as changes in temperature. These materials have drawn increasing interest in a wide range of applications, including soft robotics and sensors. While experimental measurements can provide valuable insights into their behavior, computational analysis is essential to exploit their full potential. Accurate simulation is not, however, the end goal; rather it is the means to their optimal design. Such design optimization problems are best solved with nonlinear programming algorithms that require gradients, i.e., sensitivities, of functions with respect to the design parameters, to efficiently traverse the design space. In this work, we design and print LCE devices using state-of-the-arts optimization and additive manufacturing techniques. To achieve this, a nonlinear LCE model implemented in a scalable and flexible finite element-based open source framework, namely Serac, performs the analyses. The graph-based Livermore Design Optimization code, LiDO, is used to link the design parameterizations, finite element analysis, and optimization solver, and automate the sensitivity analysis. LCE design problems that optimize both the material orientation and shape to either reach a target deformation or maximize energy absorption are solved. The optimal designs are post-processed into a file that is input to a voxel-by-voxel printer for their fabrication. Finally, the computations are validated via experimental data. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, IM Review Number: LLNL-ABS-857935.
