Parameter Identification of Thermal Visco-Plastic Model Considering Dynamic Recrystallization

Abstract:

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A hybrid global optimization method combining the Real-coded genetic algorithm and some classical local optimization methods is constructed and applied to develop a special program for parameter identification. Finally, the parameter identification for both 26Cr2Ni4MoV steel and AZ31D magnesium alloy is carried out by using the program. A comparison of deformation test and numerical simulation shows that the parameter identification and the obtained two sets of material parameters are all available.

Info:

Periodical:

Materials Science Forum (Volumes 561-565)

Main Theme:

Edited by:

Young Won Chang, Nack J. Kim and Chong Soo Lee

Pages:

1869-1874

DOI:

10.4028/www.scientific.net/MSF.561-565.1869

Citation:

Q. L. Jin and Y. S. Zhang, "Parameter Identification of Thermal Visco-Plastic Model Considering Dynamic Recrystallization", Materials Science Forum, Vols. 561-565, pp. 1869-1874, 2007

Online since:

October 2007

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Price:

$35.00

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