Multi-Phase-Field Simulation of Flow Stress and Microstructural Evolution during Deformation-Induced Ferrite Transformation in a Fe–C Alloy

Abstract

Deformation-induced ferrite transformation (DIFT) is one of the most effective ways of refining ferrite grains in steel. In this study, we employed a multi-phase-field (MPF) model to simulate both variations in macroscopic flow stress and microstructural evolution during DIFT. Using the MPF model, two-dimensional simulations of DIFT in a Fe-C alloy were performed to investigate the effects of strain rate, austenite grain size, and dynamic recrystallization (DRX) of the ferrite phase on flow stress curve and ferrite grain size. The results demonstrated that increasing the rate of ferrite nucleation by increasing the strain rate and reducing the austenite grain size is essential to obtaining fine-grained ferrite. The results of the simulations also indicated that it is important to reduce the interfacial mobility and increase the nucleation rate of the ferrite grains subjected to DRX in order to obtain ultrafine-grained ferrite by DIFT when it is accompanied by DRX of the ferrite phase. Thus, the MPF model is an effective tool for elucidating the correlation between the variation in the flow stress and the evolution of the ferrite grains during DIFT.

Design of advanced steels by integrated computational materials engineering

“…It introduces deformation energy storage between grains into the free energy functional of the phase field and considers work hardening and recovery softening in the relationship between deformation and dislocation density. By comparing with the experimental stress–strain curves, the phase field method can well describe recrystallization behaviors [81–85] [81] GCr15, [84] and Fe‐C alloy, [83] were studied.…”

“…By comparing with the experimental stress–strain curves, the phase field method can well describe recrystallization behaviors [81–85] [81] GCr15, [84] and Fe‐C alloy, [83] were studied. The recrystallization microstructure during hot rolling and the heat treatment process after cold rolling were obtained.…”

“…The recrystallization microstructure during hot rolling and the heat treatment process after cold rolling were obtained. Furthermore, the diffusion of carbon was introduced into the recrystallization phase field model [83] to achieve the influence of the composition field on the recrystallization structure. In addition, the recrystallization structure calculated by the phase field method was introduced into the finite element program to couple the high‐temperature deformation of the work piece with the recrystallization behavior, providing valuable reference for the development of actual hot working processes of steels [85] …”

“…The static recrystallization or dynamic recrystallization behaviors of steels, such as C‐Mn steel, [81] GCr15, [84] and Fe‐C alloy, [83] were studied. The recrystallization microstructure during hot rolling and the heat treatment process after cold rolling were obtained.…”

“…highlighted the potential of ML in shortening R&D cycles and reducing costs in metal additive manufacturing in a review article, advocating interdisciplinary cooperation to accelerate material development by combining physics, chemistry, material science, and computer science. Yu et al [49–128] . explored the role of ML in guiding the design and discovery of metal structural materials, emphasizing the importance of data sharing and physics‐informed modeling.…”