Stochastic modeling of the void shape in 3D-printed thermoplastics

Abstract The 3D-printed composites manufactured by the fused filament fabrication technique contain a substantial amount of voids as a result of the layerwise deposition process. The voids obtain convex or concave shapes which influence the macrostructural response and must be captured by homogenization approaches. However, the majority of approaches that consider the real shape of voids are based on computationally intensive numerical models that are time-consuming. This article presents a novel methodology to convert the real shape of voids to ideal supercylindrical one, which can be defined using only one parameter, the concavity parameter, thus drastically reducing the computational effort. The methodology is stochastically implemented using a non-intrusive uncertainty quantification technique for analytical, semi-analytical, and numerical homogenization approaches to describe the effects of voids on the effective elastic properties of 3D-printed thermoplastics. The stochastic modeling is applied for acrylonitrile butadiene styrene (ABS) and the results are compared to previous experiments and computationally intensive models and illustrate a good overall prediction of the effective elastic properties.