Owing to its excellent properties, graphite shows great potential for applications in engineering. However, the removal mechanism of brittle materials results in the formation of randomly distributed craters of varying sizes on the machined surface of graphite during machining. The difficult machining characteristics lead to the importance of studying the cutting mechanism of graphite. In this paper, the cutting process of graphite has been numerically simulated by the finite element method. In numerical simulations, the accuracy of the simulation results depends largely on the accuracy of the selected intrinsic model parameters. To determine the parameters of the Johnson‒Holmquist II (JH-2) constitutive model, this paper presents systematic mechanical testing of graphite materials. The compressive and impact strengths of graphite were found to be 142.17 MPa and 133.6 MPa via quasistatic compression and Hopkinson compression rod experiments, respectively, and the damage patterns of graphite were obtained. The constant HEL of the equation in the Hugoniot state was measured to be 1.056 GPa using plate impact tests. Finally, the experimental data obtained were combined with the theoretical derivation to finalize the parameters of the JH-2 model. To ensure the reliability of the model parameters, the cutting simulation results were compared with the actual experimental results.

Determination of the parameters of the Johnson-Holmquist-II (JH-2) constitutive model for graphite and a simulation of cutting
    Abstract
    1 Introduction
    2 Theoretical basis of the JH-2 constitutive model
    3 Test introduction
        3.1 Quasistatic compression test and dynamic compression test
        3.2 Plate impact experiment
    4 JH‑2 constitutive model parameter determination
        4.1 Basic parameters of graphite
        4.2 Determination of the state equation parameters
        4.3 Determination of strength model parameters
        4.4 Determination of damage model parameters
    5 Numerical simulation
    6 Conclusion
    References

• Zhiyang Zhang(School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou, China)
• Min Liu(School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou, China)
• Shuping Li(School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou, China)
• Dayong Yang(School of Mechanical and Automotive Engineering, Guangxi University of Science and Technology, Liuzhou, China, College of Intelligent Manufacturing, Jingchu University of Technology, Jingmen 448000, China) Corresponding author
• Furui Wei(Shandong Huitong Intelligent Machine Company Limited, Qingdao,, China)
• Hong Li(Chongqing Vocational Institute of Engineering, Chongqing, China)