| Abstract Scope |
The characterization of defects in additive manufacturing (AM) is key in determining the performance indicators used for validation of a material or component. However, due to the thermal nature of AM, traditional methods of validation may fail to capture geometric effects on the resulting thermal history of a build. Thus, a new methodology of validation must be considered to build on the effect of not only the feedstock material, but also the final geometry intended for use. Through the use of computed tomography scanning, porosity and surface roughness of AlSi10Mg specimens, designed to incorporate various geometric features, are analyzed. These features, such as fillet radii, thickness, and overhang angle, are then tied to their defect characteristics to create a model of the effect of geometry. Subsequent optimization of these modeled correlations is employed in finite element modeling using Altair Optistruct to maximize the performance of the final component geometry. |