A new method for identification of cyclic plasticity model parameters

In this study, a new method for determining the material parameters of cyclic plasticity is presented. The method can be applied to evaluate the model parameters from any loading histories measured experimentally. The experimental data require basic processing only to be utilized. The method can be applied to calibrate the parameters of different elastoplastic models such as the Chaboche-Rousselier (Ch-R) constitutive equation or other model formulations which use different rules of isotropic hardening. The developed method was utilized to evaluate the material parameters of copper for a selected group of constitutive models. It is shown that among the considered model formulations a very good description of the mechanical properties of copper is achieved for the Ch-R model with two Voce terms used for simulating the isotropic hardening and two backstress variables utilized for capturing the kinematic hardening behavior. Furthermore, it is demonstrated that a model calibrated using the cyclic tension/compression data is able to properly capture the material response in torsion. Similarly, when the constitutive parameters are determined using the cyclic torsion data the model is able to properly reproduce the material behavior in tension/compression. It is concluded that for the considered type of constitutive equations the material parameters can be identified from a single mechanical test. The proposed methodology was validated using the relations derived analytically

Automated summary

In this study, a new method for determining the material parameters of cyclic plasticity is proposed. The method can be applied to evaluate the model parameters from any experimentally measured loading histories with basic data processing. The results show that the Chaboche-Rousselier (Ch-R) model with two Voce terms for isotropic hardening and two backstress variables for kinematic hardening provides a very good description of the mechanical properties of copper.