Directed energy deposition characterization and modeling

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dc.contributor.advisorKovar, Desiderio
dc.contributor.advisorLienert, T. J. (Thomas J.)
dc.contributor.committeeMemberBourell, David
dc.contributor.committeeMemberLandsberger, Sheldon
dc.contributor.committeeMemberHochanadel, Patrick W
dc.creatorKnapp, Cameron Myron
dc.creator.orcid0000-0001-8775-7660
dc.date.accessioned2018-10-25T15:24:05Z
dc.date.available2018-10-25T15:24:05Z
dc.date.created2018-08
dc.date.issued2018-08-10
dc.date.submittedAugust 2018
dc.date.updated2018-10-25T15:24:05Z
dc.description.abstractAdditive manufacturing has seen a rapid rise in implementation into modern manufacturing schemata. The success or failure of its full adoption into stringent engineering environments hinges on bridging the qualification gap that currently exists. Qualification of high performance components requires the ability to control the deposition and fusion of material to minimize geometric variation and defect introduction. This research focuses on the characterization and instrumentation of an Optomec LENS MR-7 to conduct targeted experiments in support of advancing the fundamental understanding of the DED process. Initial efforts to control the DED process focused on evaluating a theoretical passive feedback mechanism associated with the laser alignment. Preliminary experiments confirmed the theory of a passive deposition stability associated with overfocusing the laser at initial alignment. However, this experimental series revealed how much was truly uncontrolled in the process. Ideally a lightweight model was needed that could predict the effect of changes to deposition parameters. A model of this type could be used to reduce the number of Edisonian experiments needed to develop new material systems or optimize for specific deposition characteristics. A thermodynamically governed model was proposed that included mathematical models that govern physical processes, material properties, and two experimental fits. This model can be executed in seconds on a laptop style computer and can predict deposition characteristics such as height, width, deposition rate, powder capture efficiency, and melting efficiency. A controlled set of experiments was done on 304L stainless steel, Ti-6Al-4V titanium alloy, and A356.1 aluminum alloy to evaluate the accuracy of the model. The model demonstrated a predictive capability within 10% of measured values and the ability to predict when departure from stable conditions would likely occur.
dc.description.departmentMechanical Engineering
dc.format.mimetypeapplication/pdf
dc.identifierdoi:10.15781/T2WW77J95
dc.identifier.urihttp://hdl.handle.net/2152/69177
dc.language.isoen
dc.subjectDirected energy deposition
dc.titleDirected energy deposition characterization and modeling
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentMechanical Engineering
thesis.degree.disciplineMechanical Engineering
thesis.degree.grantorThe University of Texas at Austin
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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