Patents by Inventor Derek H. Siddel

Derek H. Siddel has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 12062464
    Abstract: 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 (B4C) or isotopically enriched boron carbide (10B).
    Type: Grant
    Filed: August 1, 2022
    Date of Patent: August 13, 2024
    Assignee: UT-Battelle, LLC
    Inventors: David C. Anderson, Anibal J. Ramirez-Cuesta, Matthew B. Stone, Amelia M. Elliott, Derek H. Siddel
  • Publication number: 20230139949
    Abstract: 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.
    Type: Application
    Filed: October 3, 2022
    Publication date: May 4, 2023
    Inventors: Luke R. Scime, Vincent C. Paquit, Desarae J. Goldsby, William H. Halsey, Chase B. Joslin, Michael D. Richardson, Derek C. Rose, Derek H. Siddel
  • Publication number: 20230041882
    Abstract: 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 (B4C) or isotopically enriched boron carbide (10B).
    Type: Application
    Filed: August 1, 2022
    Publication date: February 9, 2023
    Inventors: David C. Anderson, Anibal J. Ramirez-Cuesta, Matthew B. Stone, Amelia M. Elliott, Derek H. Siddel
  • Patent number: 11458542
    Abstract: 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.
    Type: Grant
    Filed: November 17, 2020
    Date of Patent: October 4, 2022
    Assignee: UT-Battelle, LLC
    Inventors: Luke R. Scime, Vincent C. Paquit, Desarae J. Goldsby, William H. Halsey, Chase B. Joslin, Michael D. Richardson, Derek C. Rose, Derek H. Siddel
  • Patent number: 11404180
    Abstract: 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 (B4C) or isotopically enriched boron carbide (10B).
    Type: Grant
    Filed: October 9, 2018
    Date of Patent: August 2, 2022
    Assignee: UT-Battelle, LLC
    Inventors: David C. Anderson, Anibal J. Ramirez-Cuesta, Matthew B. Stone, Amelia M. Elliott, Derek H. Siddel
  • Publication number: 20220134435
    Abstract: 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.
    Type: Application
    Filed: November 17, 2020
    Publication date: May 5, 2022
    Inventors: Luke R. Scime, Vincent C. Paquit, Desarae J. Goldsby, William H. Halsey, Chase B. Joslin, Michael D. Richardson, Derek C. Rose, Derek H. Siddel
  • Publication number: 20190108923
    Abstract: 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 (B4C) or isotopically enriched boron carbide (10B).
    Type: Application
    Filed: October 9, 2018
    Publication date: April 11, 2019
    Inventors: David C. Anderson, Anibal J. Ramirez-Cuesta, Matthew B. Stone, Amelia M. Elliott, Derek H. Siddel