Lawrence Livermore National Laboratory

MED’s Rosa Morales is developing algorithms for Robert Panas’ (PI) Precision Computed Tomography (PCT) project, which is focused on advancing the state-of-the-art in computed tomography (CT) measurements. This work provides new and better information via CT for measuring additively manufactured parts. The algorithms she writes for the PCT project are destined for eventual integration with the Livermore Tomography Tools software package.

“Additive manufacturing (AM) currently lacks dimensional metrology because there is not a standard to obtain accurate measurements, or error bars, of AM parts with internal features,” said Morales. “Error bars are typically found using optical or tactile methods that are limited to external measurements and tend to be destructive. X-ray CT systems can nondestructively measure AM parts, including any internal features. CT provides the dimensional metrology that is missing, but we must first have a clear understanding of measurements made with these systems.”

The theory developed by the PCT project team provides a detailed understanding of the multi-physics uncertainties generated during X-ray imaging and the effect of these uncertainties on measurements conducted with X-rays, a first for the CT field. Based on rigorous mathematics, five error models were generated to provide an understanding of the uncertainty. “A majority of my work consists of developing the algorithms for these abstract error models,” said Morales. “I am creating MATLAB code that can automatically determine the machine performance and limitations based on the quantified uncertainty. The Precision CT LDRD project will allow us to (1) determine the uncertainties in measurements, which is needed to improve the LLNL AM equipment, (2) optimize those measurements, and (3) determine how to build better CT systems.”