Prediction of forming limit in hydro-mechanical deep drawing of steel sheets using ductile fracture criterion

2006 ◽  
Vol 12 (2) ◽  
pp. 121-129 ◽  
Author(s):  
S. -T. Oh ◽  
H. -J. Chang ◽  
K. H. Oh ◽  
H. N. Han
2019 ◽  
Vol 55 (16) ◽  
pp. 47 ◽  
Author(s):  
YANG Zhuoyun ◽  
ZHAO Changcai ◽  
DONG Guojiang ◽  
CHEN Guang ◽  
ZHU Liangjin ◽  
...  

2008 ◽  
Vol 49 (572) ◽  
pp. 886-890 ◽  
Author(s):  
Hirohiko TAKUDA ◽  
Keisuke OZAWA ◽  
Takayuki HAMA ◽  
Tohru YOSHIDA ◽  
Jun NITTA

2012 ◽  
Vol 472-475 ◽  
pp. 781-786
Author(s):  
Duc Toan Nguyen ◽  
Young Suk Kim ◽  
Dong Won Jung

The FEM simulation results of deep drawing process are carried out to create training cases for the artificial neural network (ANN), and then the well-trained ANN(s) is used to predict the formability of aluminum alloy A1100-O sheets. The OYANE’ s ductile fracture criterion equation [J. Mech. Work. Technol. 4 (1980), pp. 65-81] was implemented to predict the formability of deep drawing process. This ductile fracture criterion is introduced and evaluated from the histories of stress and strain calculated by means of finite element analysis in order to get the ductile fracture value (I). The resolution of the results of ductile fracture criterion equations is carried out via a VUMAT user material, using ABAQUS/Explicit finite element code. From the calculative results of FEM simulation with the changing of various parameters, the formability predictions using ANN methodology was investigated by comparing with random case studies of FEM results and shown good agreements


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