Optimization of Process Parameters, Post Processing Treatments, and Phase Diagram Features for Controlling the Microstructure and Performance of Additively Manufactured Metals
Abstract
Additive manufacturing (AM) has gained considerable academic and industrial interest due to its ability to produce parts with complex geometries with the potential for local microstructural control. However, due to the large number of material and process variables associated with AM, optimization of alloying compositions and process parameters is an arduous task. There is a fundamental gap in understanding how changes in process variables and material properties affect additively manufactured parts. An optimization framework to determine process parameter ranges for building porosity-free parts is introduced here and validated for a newly developed ultra-high strength steel alloy. This framework utilizes the computationally inexpensive Eager-Tsai model, calibrated with single track experiments, to predict the melt pool geometry. A geometric criterion for determining maximum allowable hatch spacing is also developed to avoid lack of fusion induced porosity in the as-printed parts. This process optimization framework is then applied to four binary nickel-based alloys, namely, Ni-20at.% Cu, Ni-5at.% Al, Ni-5at.% Zr, and Ni-8.8at.% Zr in order to study the effects of alloying composition and material properties on printability and solidification microstructures in AM. These compositions are selected to represent binary isomorphous, weak solute partitioning, strong solute partitioning, and eutectic alloying conditions respectively. Single track and bulk experiments are conducted to quantify the effects of varying material properties such as solidification temperature ranges, alloy melting temperatures, and other solidification conditions on resultant microstructures across the laser powder bed fusion (L-PBF) parameter space. A second layer is added to the parameter optimization framework to predict microsegregation across the laser power – scan speed parameter space and is validated for each of these alloys to determine how material properties affect printability and microstructure in L-PBF.
Finally, the effect of post processing treatments on additively manufactured ultra-high strength steel are studied to refine and homogenize microstructural features and further improve mechanical properties. This knowledge will be vital in optimizing alloy chemistry, process parameters, and post processing schedules to design alloys specifically for additive manufacturing, as well as to provide a path toward local microstructure control.
Subject
Additive ManufacturingLaser Powder Bed Fusion
Selective Laser Melting
Ultra-High Strength Steel
Martensitic Steel
Nickel Alloys
Process Optimization
Microsegregation
Citation
Seede, Raiyan Ali (2022). Optimization of Process Parameters, Post Processing Treatments, and Phase Diagram Features for Controlling the Microstructure and Performance of Additively Manufactured Metals. Doctoral dissertation, Texas A&M University. Available electronically from https : / /hdl .handle .net /1969 .1 /197158.