Patents by Inventor Zachary R. Ulbig

Zachary R. Ulbig 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: 12115581
    Abstract: A rapid material development process for a powder bed fusion additive manufacturing (PBF AM) process generally utilizes a computational fluid dynamics (CFD) simulation to facilitate selection of a simulated parameter set, which can then be used in a design of experiments (DOE) to generate an orthogonal parameter space to predict an ideal parameter set. The orthogonal parameter space defined by the DOE can then be used to generate a multitude of reduced volume build samples using PBF AM with varying laser or electron beam parameters and/or feedstock chemistries. The reduced volume build samples are mechanically characterized using high throughput techniques and analyzed to provide an optimal parameter set for a 3D article or a validation sample, which provides an increased understanding of the parameters and their independent and confounding effects on defects and microstructure.
    Type: Grant
    Filed: September 22, 2023
    Date of Patent: October 15, 2024
    Assignee: The Johns Hopkins University
    Inventors: Steven M. Storck, Joseph J. Sopcisak, Christopher M. Peitsch, Salahudin M. Nimer, Zachary R Ulbig
  • Publication number: 20240017326
    Abstract: A rapid material development process for a powder bed fusion additive manufacturing (PBF AM) process generally utilizes a computational fluid dynamics (CFD) simulation to facilitate selection of a simulated parameter set, which can then be used in a design of experiments (DOE) to generate an orthogonal parameter space to predict an ideal parameter set. The orthogonal parameter space defined by the DOE can then be used to generate a multitude of reduced volume build samples using PBF AM with varying laser or electron beam parameters and/or feedstock chemistries. The reduced volume build samples are mechanically characterized using high throughput techniques and analyzed to provide an optimal parameter set for a 3D article or a validation sample, which provides an increased understanding of the parameters and their independent and confounding effects on defects and microstructure.
    Type: Application
    Filed: September 22, 2023
    Publication date: January 18, 2024
    Inventors: Steven M. Storck, Joseph J. Sopcisak, Christopher M. Peitsch, Salahudin M. Nimer, Zachary R Ulbig
  • Patent number: 11806784
    Abstract: A rapid material development process for a powder bed fusion additive manufacturing (PBF AM) process generally utilizes a computational fluid dynamics (CFD) simulation to facilitate selection of a simulated parameter set, which can then be used in a design of experiments (DOE) to generate an orthogonal parameter space to predict an ideal parameter set. The orthogonal parameter space defined by the DOE can then be used to generate a multitude of reduced volume build samples using PBF AM with varying laser or electron beam parameters and/or feedstock chemistries. The reduced volume build samples are mechanically characterized using high throughput techniques and analyzed to provide an optimal parameter set for a 3D article or a validation sample, which provides an increased understanding of the parameters and their independent and confounding effects on defects and microstructure.
    Type: Grant
    Filed: May 14, 2021
    Date of Patent: November 7, 2023
    Assignee: The Johns Hopkins University
    Inventors: Steven M. Storck, Joseph J. Sopcisak, Christopher M. Peitsch, Salahudin M. Nimer, Zachary R. Ulbig
  • Publication number: 20210362242
    Abstract: A rapid material development process for a powder bed fusion additive manufacturing (PBF AM) process generally utilizes a computational fluid dynamics (CFD) simulation to facilitate selection of a simulated parameter set, which can then be used in a design of experiments (DOE) to generate an orthogonal parameter space to predict an ideal parameter set. The orthogonal parameter space defined by the DOE can then be used to generate a multitude of reduced volume build samples using PBF AM with varying laser or electron beam parameters and/or feedstock chemistries. The reduced volume build samples are mechanically characterized using high throughput techniques and analyzed to provide an optimal parameter set for a 3D article or a validation sample, which provides an increased understanding of the parameters and their independent and confounding effects on defects and microstructure.
    Type: Application
    Filed: May 14, 2021
    Publication date: November 25, 2021
    Inventors: Steven M. Storck, Joseph J. Sopcisak, Christopher M. Peitsch, Salahudin M. Nimer, Zachary R. Ulbig