appinternalicon-talk

Additive Technologies

3D Printing, Porosity, Synchrotron Experiments and Machine Learning

8:10 AM–8:40 AM Feb 24, 2020 (US - Pacific)

San Diego Convention Ctr - 8

Description

Anthony D. Rollett1; 1Carnegie Mellon University

3D printing of metals has advanced rapidly in the past decade and is used across a wide range of industry. At the microscopic scale much work is required to quantify, understand and predict defect- and micro-structures, which affect properties such as fatigue resistance. Dynamic x-ray radiography (DXR) provides ultra-high speed imaging of laser melting of metals and their powders. This has, e.g., enabled the keyhole and hot cracking phenomena to be quantified. Computer vision (CV) has successfully classified different microstructures, including powders. The power of CV is further demonstrated by its ability to detect and classify defects in the spreading of powder. High speed synchrotron x-ray diffraction is beginning to provide new information on solidification and phase transformation in, e.g., IN718, Ti-6Al-4V and stainless steel. High Energy (x-ray) Diffraction Microscopy (HEDM) experiments also is also providing data on 3D microstructure and elastic strain in 3D printed materials.
Tags