Probability of Detection and Validation for Computed Tomography Processes for Additive Manufacturing (20-RD-231)

X-ray computed tomography (CT) is a widely used nondestructive evaluation (NDE) method for quality control and post-build inspection in additively manufactured (AM) components. The limitations of such NDE methods and the need to validate the capability of these methods on an ongoing basis are increasingly recognized. Automated, metallography-based serial sectioning offers a reliable method to establish ground truth data on the flaw populations as well as microstructural variations of AM components. Such data can be used to validate, and subsequently improve the reliability of NDE methods. UES proposes a project aimed at establishing comparison methods and workflows for validating CT (and potentially other NDE data) with ground truth from serial sectioning, and developing probability of detection (POD) curves. The knowledge gained from these efforts will inform CT scan strategies for improved flaw detection in AM components, evaluate flaw detectability in CT using serial sectioning as a ground truth comparison, and quantify the risk of the flaws absent from the CT data sets. Phase II extends the work of validation into the area of in situ detection and validation of in situ sensing methodologies using thermal and visual data.