Identification of Microstructural Model Parameters for 3D Finite Element Simulation of Machining Inconel 100 Alloy

Prediction of machining induced surface integrity and microstructural changes using Finite Element modeling is challenging due to difficult to obtain material deformation models as well as models related to microstructure of the material. This study presents investigations on identifying microstructure model parameters by using experimentally measured microhardness and grain sizes and phase fractions in machining of Inconel 100 nickel based alloy with uncoated and coated cutting tools. 3D customized finite element simulations have been performed to predict the average grain size by implementing modified temperature dependent flow softening based material and Johnson-Mehl-Avrami-Kolmogorov (JMAK) crystallization models. A sensitivity analysis on the JMAK model parameters has been performed and by using an optimization scheme the microstructure model parameters have been identified with genetic algorithms. Finally, simulation predictions using identified JMAK model parameter set on the average grain sizes, phase fractions, and resultant microhardness are compared against experimental measurements revealing good agreements.