The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Oct. 15, 2024
Filed:
Sep. 22, 2023
The Johns Hopkins University, Baltimore,, MD (US);
Steven M. Storck, Catonsville, MD (US);
Joseph J. Sopcisak, Derwood, MD (US);
Christopher M. Peitsch, Perry Hall, MD (US);
Salahudin M. Nimer, Fulton, MD (US);
Zachary R Ulbig, Essex, MD (US);
The Johns Hopkins University, Baltimore, MD (US);
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. Additionally, machine learning techniques can be used to optimize for future parameter selection by modeling the relationship between input processing parameters and outputs of material characterization.