Abstract
Grain size and its distribution is the dominant microstructure feature of austenitic stainless steels. These characteristics considerably affect the mechanical properties of the steels. The distribution of grain size during preheating prior to the hot deformation has the main effect on the uniform distribution of the strain interior of the grains and, consequently, on the homogeneous development of processes such as static, dynamic, and metadynamic recrystallization in the material. The grain size distribution can be expressed using the Jensen–Gundersen point method along with the commonly-cited distribution functions such as the lognormal, gamma, Weibull, Louat, or Hilert relations. In this study, 3D Monte Carlo Potts method was employed for predicting grain growth kinetics and relevant grain size distribution during annealing process to describe which distribution function is dominant. To validate simulation results, the serial sectioning procedure was performed on AISI 316L cylindrical samples annealed at 1200°C for 5, 10, and 15 min. Results show that grain number densities (GND) affect the grain size distribution, in which at the relatively low GNDs, the lognormal function and at the higher ones, the gamma function are realized. Moreover, a new method for the grain size standard deviation statement via the lognormal distribution is introduced.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call