Inverse Identification of Johnson-Cook Material Parameters from Machining Simulations

Abstract:

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A material model is a prerequisite to the modelling of machining processes. Owing to its versatility, the Johnson-Cook model is commonly used for machining simulations. Determination of the model parameters from experiments is challenging due to the large variations of strains, strain-rates and temperatures which lead to several problems. State-of-the-art experimental methods have to rely on data obtained from much lower strains and strain-rates than those encountered during machining. In this paper, an inverse method of identifying Johnson-Cook parameters from machining experiments is described. A fnite-element model of the machining process was created and a particular Johnson-Cook parameter set was taken from literature for the simulation. The Levenberg-Marquardt Algorithm was used to re-identify the material parameters by looking at the Chip-morphology and the Cutting force evolution. It is shown that the optimisation parameters and error function must be chosen carefully in order to achieve better solutions at lower computational expense.

Info:

Periodical:

Edited by:

J.C. Outeiro

Pages:

277-285

DOI:

10.4028/www.scientific.net/AMR.223.277

Citation:

A. Shrot and M. Bäker, "Inverse Identification of Johnson-Cook Material Parameters from Machining Simulations", Advanced Materials Research, Vol. 223, pp. 277-285, 2011

Online since:

April 2011

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Price:

$35.00

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