Image-Based Geometrical Characterization of Nodes in Additively Manufactured Lattice Structures.

Additive manufacturing (AM) enables the fabrication of lattice structures with optimal mechanical, fluid, and thermal properties. However, during the AM fabrication process, defects are produced in the strut and node elements, which comprise the lattice structure. This leads to discrepancies between the AM fabricated lattice and its idealized computer-aided design (CAD) model, negatively affecting the ability to predict the mechanical behavior of the fabricated lattice via numerical models. Current research is focused on quantification of geometric uncertainties in the strut elements of the lattice; as-manufactured node geometries remain relatively unexplored on an individual scale, despite their criticality to the mechanical response of the structure. Understanding the geometrical properties of as-manufactured nodes relative to CAD idealizations can be used to improve lattice designs and numerical models. In this research, X-ray microcomputed tomography (μCT) is used to analyze and quantify the as-manufactured nodal geometry, found in face-centered cubic and face-centered cubic with axial struts lattices fabricated via selective laser melting. A custom tool is developed that enables auto-isolation and classification of nodal joints from μCT-derived cross-sectional slices. Geometrical properties are extracted from the isolated nodal cross sections and compared with their idealized CAD model counterpart. Quantification of geometrical defects provides insight into how nodes within an AM lattice structure differ from each other and their idealized design. Overall, this research is an initial step toward developing accurate and efficient numerical models, as well as better node design for AM.