Predictive Modeling of Microstructure Evolution within Multi-Phase Steels during Rolling Processes
Abstract
Recently, severe plastic deformation induced microstructure evolution has been studied through extensive experimental investigations for various materials with multiple phases during rolling processes. In this study, a dislocation density-based numerical approach is combined with strain-induced phase transformation kinetics to investigate the gain size change within steels consisting of different phases. The microstructure evolution caused by plastic deformation during rolling processes is modeled by finite element formulation with a dislocation density-based model and strain-induced transformation subroutines. The validity of the numerical solutions is evaluated through simulations of cold rolling processes of steels at different rolling strains and comparison with experimental results. It is shown that the microstructure evolution of different phases during rolling processes is well captured by the proposed approach. The predicted mechanical behavior of the rolled steels exhibits a good agreement with the experimental results under tensile loadings.
Recommended Citation
X. Dong and Y. C. Shin, "Predictive Modeling of Microstructure Evolution within Multi-Phase Steels during Rolling Processes," International Journal of Mechanical Sciences, vol. 150, pp. 576 - 583, Elsevier, Jan 2019.
The definitive version is available at https://doi.org/10.1016/j.ijmecsci.2018.10.061
Department(s)
Mechanical and Aerospace Engineering
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Cold rolling; Plastic 00deformation; Strain; Cold rolling process; Dislocation densities; Experimental investigations; Finite element formulations; Micro-structure evolutions; Severe plastic deformations; Strain induced transformation; Strain-induced phase transformation; Microstructure
International Standard Serial Number (ISSN)
0020-7403
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 Elsevier, All rights reserved.
Publication Date
01 Jan 2019
Comments
The authors wish to gratefully acknowledge that this research was partially funded by MFRC (Grant Number: 208981).