Effect analysis of residual stress on the machined surface of a titanium alloy (TC4) based on parameter optimization of a finite-element model

Abstract. This paper uses the Jonson–Cook (J–C) constitutive and Coulomb friction models to study the residual stress (RS) finite-element method on the cut surface. A reverse recognition optimization algorithm combining a data-driven algorithm and a genetic algorithm is proposed to optimize the parameters of the J–C constitutive model, thus improving the simulation accuracy. Experiments verify the accuracy of the model. Based on the simulation of RS, the mechanism of cutting parameters' influence on the workpiece surface's RS was deeply analyzed in this study. The results show that increasing the cutting speed can reduce the cutting force and increase the RS. Increasing the tool front angle helps improve the machining quality, but a front angle that is too large will also increase RS. The cutting temperature and force influence the RS of the surface and subsurface, respectively.