Optimizing Beam Stiffness and Beam Modal Response with Variable Spacing and Extrusion (VaSE)

This paper presents a novel algorithm, Variable Spacing and Extrusion (VaSE), designed to optimize the infill pattern of material extrusion (ME) 3D-printed parts for specified mechanical performance while ensuring manufacturability. The algorithm adjusts deposition spacing and width across layers to achieve functionally graded infill distributions derived from input density maps. First, the variable line spacing algorithm is implemented by normalizing the weighted density distribution. Errors in between the desired density and the density from the line spacing are corrected with a varying extrusion width algorithm. Two application scenarios are demonstrated with the proposed VaSE algorithm. First, beam samples are optimized for flexural stiffness and tested under three-point bending, showing a 10.8–19.2% stiffness increase compared to homogeneous infill, except at low (25%) volume fractions, where local buckling dominated failure. The second scenario involves maximizing the frequency of the first three modes of beams under an induced vibration. The optimized beams, taken straight from a topology optimization algorithm performed in the ANSYS 2023 finite element software, were compared to the beams that were instead put through the VaSE algorithm after the topology optimization. While all manufactured beams underperform relative to simulation, the VaSE-optimized beams show substantial frequency gains (34–63% for the first mode, 0.82–65% for the second mode) over purely geometry-based designs, with the exception of high-mass-fraction beams. These findings highlight the significance of the VaSE algorithm in enhancing mechanical performance and extending the design space of ME additive manufacturing beyond conventional homogeneous infill strategies.