Evgueni T. Filipov

Yi Zhu, Evgueni T. Filipov

This work harnesses interpretable machine learning methods to address the challenging inverse design problem of origami-inspired systems. We show that a decision tree-random forest method is particularly suitable for fitting origami databases, containing both design features and functional performance, to generate human-understandable decision rules for the inverse design of functional origami. First, the tree method is unique because it can handle complex interactions between categorical features and continuous features, allowing it to compare different origami patterns for a design. Second, this interpretable method can tackle multi-objective problems for designing functional origami with multiple and multi-physical performance targets. Finally, the method can extend existing shape-fitting algorithms for origami to consider non-geometrical performance. The proposed framework enables holistic inverse design of origami, considering both shape and function, to build novel reconfigurable structures for various applications such as metamaterials, deployable structures, soft robots, biomedical devices, and many more.

Yi Zhu, Evgueni T. Filipov

Electro-thermally actuated origami provides a novel method for creating 3-D systems with advanced morphing and functional capabilities. However, it is currently difficult to simulate the multi-physical behavior of such systems because the electro-thermal actuation and large folding deformations are highly interdependent. In this work, we introduce a rapid multi-physics simulation framework for electro-thermally actuated origami systems that can simultaneously capture: thermo-mechancially coupled actuation, inter panel contact, heat transfer, large deformation folding, and other complex loading applied onto the origami. Comparisons with finite element models validate the proposed framework for simulating origami heat transfer with different system geometries, materials, and surrounding environments. Verification of the simulated folding behaviors against physical electro-thermal micro-origami further demonstrates the validity of the proposed model. Simulations of more complex origami patterns and a case study for origami optimization are provided as application examples to show the capability and efficiency of the model. The framework provides a novel simulation tool for analysis, design, control, and optimization of active origami systems, pushing the boundary for feasible shape morphing and functional capability.