Tempering kinetics during multilayer laser additive manufacturing of a ferritic steel

T. Mukherjee, T. DebRoy, T. J. Lienert, S. A. Maloy, C. R. Lear, P. Hosemann

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Grade 91 steel forms martensite during additive manufacturing and the extent of tempering of martensite significantly affects the mechanical properties of parts. Currently, there is a lack of quantitative understanding of the tempering kinetics for Grade 91 steel, and as a result, the effects of repeated thermal cycles on properties for different processing conditions cannot be determined. Here we evaluate the tempering kinetics by determining the constant terms in the Johnson Mehl Avrami kinetic equation from the tempering data available in the literature and the thermal cycles computed using a rigorously-tested heat and fluid flow model of multi-layer additive manufacturing. The raw tempering data are cleaned using a neural network to enhance accuracy. The lower layers experience repeating cycles of heating and cooling when the upper layers are added. As a result, the hardness is reduced owing to the tempering of martensite. In contrast, martensite formed in the upper layers is not tempered to the same extent and the hardness remains high. Therefore, the hardness of the part increases with the distance from the substrate. Variations in the heat input at different laser powers and scanning speeds significantly affect the extent of tempering. Since the method used here can provide a quantitative understanding of the tempering of martensite and the spatial variation of hardness, it can be used to tailor the microstructure and hardness of heat treatable printed metallic parts.

Original languageEnglish
Pages (from-to)105-115
Number of pages11
JournalJournal of Manufacturing Processes
Volume83
DOIs
StatePublished - Nov 2022
Externally publishedYes

Funding

This work was supported by the funding received from the DOE Office of Nuclear Energy 's Nuclear Energy Enabling Technologies Program, as part of project 19–17206 of the Advanced Methods for Manufacturing Program.

Keywords

  • 3D printing
  • Directed energy deposition
  • Grade 91 steel
  • Heat transfer and fluid flow
  • Johnson Mehl Avrami
  • Martensite
  • Neural network

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