Design of 3D and 4D printed continuous fibre composites via an evolutionary algorithm and voxel-based Finite Elements: Application to natural fibre hygromorphs - de Kergariou, Charles; Kim, Byung Chul; Perriman, Adam; Le Duigou, Antoine; Guessasma, Sofiane; Scarpa, Fabrizio (Additive manufacturing, 2022)
This paper describes a novel voxel-based technique to accurately model 3D printed continuous yarns of fibre composites at printed filament scale. To cater for the constraints of continuous filament printing, the design strategy here makes use of a set of variables that fully define the printing path as input in the model. A voxel-based algorithm is developed to obtain the local orientations of the filaments and local quantities of yarns and matrix from a pixelated flat layout of the printed composite. This voxel-based representation is then translated into a Finite Element model to obtain the required structural properties. This approach simplifies and potentially shortens the design of the part, compared to other analytical techniques. The design space of the part is defined by the variables of the gcode used to print the composite. The voxel model is coupled with an evolutionary algorithm to explore the part of the design space related to the use of continuous yarns. The hygro expansion of the material was measured to determine the coefficients of moisture expansion serving as input in the model. Promising results are obtained from a test case related to a continuous flax fibres-reinforced polylactic acid (PLA) printed structure, mimicking the shape of a leaf. The proposed modelling strategy has the potential to characterise geometric, material, mechanical and actuation properties of general 3D printed structures with negligible out-of-plane (i.e., through thickness) printing. [Display omitted] •FEA voxel-based strategy can be used to model continuous fibre 3D printed composite.•Leaf shaped hygromorph printed with continuous flax fibre polylactic acid composite.•4D printed continuous fibre hygromorphs can be designed via evolutionary algorithm.