Finite element-based inverse identification of Johnson-Cook constitutive parameters for selective laser-melted IN718 superalloy

IN718 superalloy components fabricated by selective laser melting (SLM) generally require subsequent machining and numerical simulation. However, Johnson-Cook (J-C) constitutive parameters specifically applicable to three-dimensional milling of SLM-IN718 and independently validated using milling forces and chip characteristics remain scarce, thereby limiting the predictive accuracy of finite element simulations of the cutting process. In this study, dynamic stress–strain curves over wide ranges of strain rate and temperature were obtained through split Hopkinson pressure bar (SHPB) tests. A second-order regression model correlating the J-C parameters with the resultant milling force was then established based on orthogonal finite element simulation data. Taking the relative error between the experimentally measured and finite element-predicted resultant milling forces in the steady cutting stage as the objective function, a genetic algorithm was employed to inversely identify the J-C constitutive parameters within physically reasonable ranges. In addition, the predictive capability of the model for material flow and chip formation was further evaluated by comparing the experimental and simulated chip morphologies and chip thicknesses at low, medium, and high cutting speeds. Consequently, a set of equivalent J-C parameters with satisfactory predictive performance under the investigated processing conditions and finite element modeling assumptions was obtained. Validation under 16 independent milling conditions showed that the optimized J-C parameters achieved an R ² of 0.973, an RMSE of 9.39 N, an AARE of 3.1%, and a maximum relative error of 6.63%. The model also reproduced the overall chip morphology and thickness variation reasonably well. These results demonstrate that the proposed method provides satisfactory mechanical prediction accuracy and physical consistency within the investigated processing and parameter ranges.