Abstract
Constitutive model plays an important role in finite element (FE) simulation of machining, especially the Johnson-Cook (J-C) model. Although many researches have completed on modifying the J-C model to improve FE simulation of cutting, the systematic determination scheme of the added coefficients is heretofore not available. Inverse identification approach presents a promising advantage on determining constitutive coefficient compared with traditional methods, such as Split Hopkinson Pressure Bar (SHPB). In this work, a new inverse method based on finite element analysis (FEA) is developed for determining added J-C coefficients. A modified J-C constitutive model (MJC) including hyperbolic tangent failure function is introduced for machining titanium alloy Ti-6Al-4V. The determination process of the added coefficients is taken as an optimization problem, where experimental cutting forces and the added J-C coefficients are considered as the optimization objectives and design variables, respectively. An FE model of orthogonal cutting titanium alloy Ti-6Al-4V is established on the Deform-2D simulation platform. The response surface method (RSM) is subsequently used to build the mapping relation of the simulated cutting forces and the added coefficients. Then, orthogonal cutting experiments are conducted to obtain the objective cutting forces. The firefly algorithm (FA) is employed to solve the optimization model for the optimal added J-C coefficients. Verification results show that the identified constitutive model has higher accuracy on predicting cutting forces compared with other models including the origin J-C model and the Calamaz’s model.
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Funding
This work is supported by the National Natural Science Foundation of China (No.51775444), the Doctorate Foundation of Northwestern Polytechnical University (No.CX201514), and the China Scholarship Council (No.201606290165).
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Ren, J., Cai, J., Zhou, J. et al. Inverse determination of improved constitutive equation for cutting titanium alloy Ti-6Al-4V based on finite element analysis. Int J Adv Manuf Technol 97, 3671–3682 (2018). https://doi.org/10.1007/s00170-018-2178-4
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DOI: https://doi.org/10.1007/s00170-018-2178-4