This paper presents a procedure for the identification of Johnson Cook model parameters and Tresca's law friction factor for orthogonal cutting of AISI 304. The process is described by a thermomechanical numerical model. The parameters are identified by minimizing the error in the prediction of cutting force, chip thickness, and chip curvature. Two optimization algorithms where tested: a pure Nelder–Mead method (NMM), and a hybrid procedure, in which the starting simplex for NMM is calculated by means of a genetic algorithm. The results emphasize the importance of the initial guess chosen in the optimization to obtain a reliable set of parameters. By using the optimized parameters in the numerical model, the cutting force, the chip thickness, and the chip curvature can be evaluated with an acceptable accuracy. The identified rheological and tribological coefficients are validated for different orthogonal cutting conditions.
Identification of Johnson–Cook and Tresca's Parameters for Numerical Modeling of AISI-304 Machining Processes
Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received March 28, 2013; final manuscript received August 19, 2013; published online September 23, 2013. Assoc. Editor: Donggang Yao.
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Bosetti, P., Maximiliano Giorgio Bort, C., and Bruschi, S. (September 23, 2013). "Identification of Johnson–Cook and Tresca's Parameters for Numerical Modeling of AISI-304 Machining Processes." ASME. J. Manuf. Sci. Eng. October 2013; 135(5): 051021. https://doi.org/10.1115/1.4025340
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