Characterization of defects in additively manufactured materials from mechanical properties

Minimization of defects in additively manufactured components is essential for material development and the determination of fabrication process windows. Here, a purely mechanical means of quantifying porosity in a material is developed based on the Mori–Tanaka mean field theory. The micromechanics based defect quantification approach developed here links the elastic properties of a material with the specific defect structures that must exist within it to obtain those properties. Laser powder bed fusion is used to fabricate aluminum 6061 with three different processing conditions to produce nominally identical samples with unique defect microstructures. Test samples are imaged with microcomputed X-ray tomography (μCT) and the images are classified with a machine learning method to identify the volume fraction of pores, solidification cracks, and the orientation distribution function of the solidification cracks. Tensile tests are then conducted in the z-axis and within the xy-plane to measure the respective elastic moduli and the Poisson's ratio. These three commonly measured material properties are the only inputs to the new micromechanics based approach used to infer the same defect descriptors that were extracted from μCT. Excellent agreement is found between defect descriptors obtained with both methods, and quantities derived from the mechanical properties are found to carry substantially lower uncertainty. Full error propagation maps for the micromechanics based technique are calculated. Notably, defect descriptors from the micromechanics based approach are calculated from strain and load measurements, which are measured on much larger length scales than the defect size. This enables simple quantification of defects for materials containing small defects that are challenging to image.