1. Melt Pool and Heat Treatment Optimization for the Fabrication of High-Strength and High-Toughness Additively Manufactured 4340 Steel.
- Author
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Ryder, Matthew A., Montgomery, Colt J., Brand, Michael J., Carpenter, John S., Jones, Peggy E., Spangenberger, Anthony G., and Lados, Diana A.
- Subjects
MONTE Carlo method ,STEEL manufacture ,MANGANOUS sulfide ,STRENGTH of materials ,PROCESS optimization - Abstract
Additively manufactured (AM) components offer superior design flexibility compared to their conventionally manufactured counterparts and require process parameter optimization to achieve high-quality depositions with desirable and predictable mechanical properties. This study was focused on 4340 steel fabricated using laser powder bed fusion (LPBF), and 42 laser power and scan speed combinations have been systematically investigated to optimize the melt pool geometry and ensure fully dense parts. The AM material was compared with a wrought 4340 equivalent and studied in both as-fabricated and heat-treated conditions. Two heat treatments were designed and used to optimize the materials for strength and toughness, respectively. Microstructure, tensile, and fractographic studies were conducted to assess build integrity and establish processing–structure–performance relationships. Tensile properties of the AM materials in all studied conditions were equivalent or better than the comparable wrought materials. The high performance of the AM materials was attributed to the absence of both manganese sulfide inclusions and rolling-induced banding, typically found in the wrought materials. The fine cellular substructure is thought to additionally contribute to the high strength of the as-fabricated AM material. Complementary to the knowledge that has emerged from the experimental investigations, the dataset was further leveraged to make recommendations for future design of experiments to optimize AM build parameters in other material systems. A statistical Monte Carlo analysis was used to predict the interpolation error produced when using reduced datasets and to enable informed processing parameters selection. These findings are discussed to make recommendations for the use of AM materials for high-integrity structural applications. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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