Publisher
University of Tennessee at Chattanooga
Place of Publication
Chattanooga (Tenn.)
Abstract
The microstructure of the parts created using Directed Energy Deposition (DED) additive manufacturing method, vary notably due to a change in the processing parameters. Since there is a direct relation between grain morphology and the mechanical properties of a part, understanding the effects of each process parameter on the grain morphology is critical towards optimal fabrication of parts using DED method. In this study, Kinetic Monte Carlo (KMC) method was used to model the DED of parts made of 304L stainless steel. In order to simulate the grain evolution, KMC Potts model, which is a statistical mechanics model, was implemented. Using this model, the fusion zone that comprises the melt pool and Heat Affected Zone (HAZ) are simulated as two concentric ellipsoids. The kinetics provided by the fusion zone results in grain growth. To see each process parameter’s effect on the grain morphology, a parametric study was conducted on the effect of scanning speed and layer thickness on the microstructure of deposited material. The final results were analyzed qualitatively and quantitatively by using an image processing software. It was found that by increasing the scanning speed, the number of fine grains at the centerline of the laser path increases significantly. In addition, we found that in very small layer thicknesses, fine grains cannot grow and mostly disappear. This happens as a result of a too small layer thickness compared to the depth of the melt pool, which results in each layer being melted multiple times due to passage of laser on the subsequent layers.
Document Type
presentations
Language
English
Rights
http://rightsstatements.org/vocab/InC/1.0/
License
http://creativecommons.org/licenses/by/4.0/
Recommended Citation
Ataollahi, Saeed and Mahtabi, Mohammad J., "Computational modeling of the effects of process parameters on the grain morphology of additively manufactured stainless steel". ReSEARCH Dialogues Conference proceedings. https://scholar.utc.edu/research-dialogues/2022/proceedings/3.
Computational modeling of the effects of process parameters on the grain morphology of additively manufactured stainless steel
The microstructure of the parts created using Directed Energy Deposition (DED) additive manufacturing method, vary notably due to a change in the processing parameters. Since there is a direct relation between grain morphology and the mechanical properties of a part, understanding the effects of each process parameter on the grain morphology is critical towards optimal fabrication of parts using DED method. In this study, Kinetic Monte Carlo (KMC) method was used to model the DED of parts made of 304L stainless steel. In order to simulate the grain evolution, KMC Potts model, which is a statistical mechanics model, was implemented. Using this model, the fusion zone that comprises the melt pool and Heat Affected Zone (HAZ) are simulated as two concentric ellipsoids. The kinetics provided by the fusion zone results in grain growth. To see each process parameter’s effect on the grain morphology, a parametric study was conducted on the effect of scanning speed and layer thickness on the microstructure of deposited material. The final results were analyzed qualitatively and quantitatively by using an image processing software. It was found that by increasing the scanning speed, the number of fine grains at the centerline of the laser path increases significantly. In addition, we found that in very small layer thicknesses, fine grains cannot grow and mostly disappear. This happens as a result of a too small layer thickness compared to the depth of the melt pool, which results in each layer being melted multiple times due to passage of laser on the subsequent layers.