Processing and predictive modeling of thin-walled geometries by directed energy deposition
Author(s)
Kim, Myong Joon
Advisor(s)
Saldana, Christopher
Editor(s)
Collections
Supplementary to:
Permanent Link
Abstract
Blown powder directed energy deposition is a prominent additive manufacturing technique for near-net-shape part production and for repair manufacturing for aerospace, automotive, and defense industry. Thin substrate deposition, wherein the width of the substrate is smaller than that of the laser diameter, is a critical topic of interest for building and repairing complex components in various geometries and has potential to impact the production of delicate parts with minimum post-processing. Despite widespread interest and research on directed energy deposition, a rigorous understanding of process-structure response in deposition and post-processing of thin-walled geometries has yet to be developed. The proposed study will address this gap by focusing on three main objectives: (1) understanding dependent relationships between deposition quality (e.g., defect structure, grain structure, geometry, surface roughness), substrate geometry and process variables, (2) exploring efficacy of post-processing strategies for mitigating internal defects and external surface quality by laser remelting, and (3) develop and validate a multi-fidelity prediction model to relate deposition and post processing parameters to part quality outcomes. Collectively, the proposed framework and fundamental investigations will advance predictive modelling for process optimization efforts, will further the scientific understanding of thin substrate deposition in conjunction with defect removal strategies, and will provide robust tools for further implementation.
Sponsor
Date
Extent
Resource Type
Text
Resource Subtype
Dissertation