A new method to determine material parameters from machining simulations using inverse identification

Realistic simulations of machining processes require a correct description of the material behaviour. Due to the large strains and strain rates in the shear zone, the conditions during machining are difficult to reproduce in material testing so that extrapolation from testing data is often necessary. One way to circumvent this problem is to use inverse identification methods and to match machining simulations with experiments by varying the material parameters. The inverse identification process, however, is time-consuming because standard optimisation methods like evolutionary algorithms or Newton methods usually need a large number of finite element simulations. In this contribution, we use a new parameter identification method to identify Johnson-Cook material parameters from machining simulations. Target simulations with known parameters are used instead of experimental results since material parameters can be varied. The method is able to correctly reproduce the target simulations for different target materials with a small number of FEM simulations, identifying five parameters of the Johnson-Cook law. (C) 2015 The Authors. Published by Elsevier B.V.