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This paper presents a case study of the design, fabrication, and evaluation of an automotive rear-frame model made of variable axial composites (VAC), using a tailored fiber placement (TFP) technique. Conventionally, the design of a three-dimensional complex VAC structure places significant demands on mechanical engineering expertise (for anisotropic structural design) and on man-hours (for fiber-path CAD). The proposed methods facilitate the design of complex VAC structures with significantly reduced manpower requirements. A computational design method, anisotropic topology optimization, was used to create the base design. The fiber paths on the preform surfaces were generated using a Turing pattern algorithm (based on optimized fiber orientation distributions) subsequent to designing developable three-dimensional surfaces to fill the interior of the target structure. The preforms were fabricated using a computer numerical control (CNC) embroidery machine by stitching the raw fiber tow onto the base fabric in accordance with the generated fiber path data. After stacking the preforms in the mold, they were formed using vacuum-assisted resin-transfer molding (VaRTM). The static stiffness of the prototype was evaluated experimentally, and the results were compared with numerical simulations. This study demonstrates the potential for achieving further weight reduction in large-scale 3D structures by combining innovative computational design techniques with advanced fabrication methods.

Locomotive soft robots (SoRos) have gained prominence due to their adaptability. Traditional locomotive SoRo design is based on limb structures inspired by biological organisms and requires human intervention. Evolutionary robotics, designed using evolutionary algorithms (EAs), have shown potential for automatic design. However, EA-based methods face the challenge of high computational cost when considering multiphysics in locomotion, including materials, actuations, and interactions with environments. Here, we present a design approach for pneumatic SoRos that integrates gradient-based topology optimization with multiphysics material point method (MPM) simulations. This approach starts with a simple initial shape (a cube with a central cavity). The topology optimization with MPM then automatically and iteratively designs the SoRo shape. We design two SoRos, one for walking and one for climbing. These SoRos are 3D printed and exhibit the same locomotion features as in the simulations. This study presents an efficient strategy for designing SoRos, demonstrating that a purely mathematical process can produce limb-like structures seen in biological organisms. [ABSTRACT FROM AUTHOR]