Ut-battelle, Inc.

Derek H Siddel

Amelia M Elliott

David C Anderson

Anibal J Ramirez-Cuesta

Matthew B Stone

Vincent C Paquit

Derek C Rose

Desarae J Goldsby

William H Halsey

Chase B Joslin

Michael D Richardson

Luke R Scime

Collimators and other components for use in neutron scattering experiments or to provide neutron shielding in nuclear reactors or accelerator based neutron sources are produced by additive manufacturing from neutron absorbing material, such as boron carbide (BC) or isotopically enriched boron carbide (B).

Method for producing neutron collimators using additive manufacturing

Detection and classification of anomalies for powder bed metal additive manufacturing. Anomalies, such as recoater blade impacts, binder deposition issues, spatter generation, and some porosities, are surface-visible at each layer of the building process. A multi-scaled parallel dynamic segmentation convolutional neural network architecture provides additive manufacturing machine and imaging system agnostic pixel-wise semantic segmentation of layer-wise powder bed image data. Learned knowledge is easily transferrable between different additive manufacturing machines. The anomaly detection can be conducted in real-time and provides accurate and generalizable results.

Systems and methods for powder bed additive manufacturing anomaly detection

Method for producing collimators and other components from neutron absorbing materials using additive manufacturing

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Knoxville, TN, United States of America

Derek H Siddel