Material Property Requirements for Laser Windows

2009 ◽  
pp. 144-144-15
Author(s):  
AT Glassman
Keyword(s):  
Material Property ◽  
Laser Windows

scholarly journals Malleable and recyclable imide-imine hybrid thermosets: influence of imide structure on material property

2021 ◽  
Author(s):  
Xiran Shen ◽  
Yunlong Ma ◽  
Shichang Luo ◽  
Rao Tao ◽  
Dan An ◽  
...  
Keyword(s):  
Material Property ◽  
Thermosetting Polyimides

Although thermosetting polyimides have been widely used in many fields, it is still a challenging task to realize their repairability, reprocessibility, and recyclability, which are highly desired features given the...

Prediction of Effective Material Property of Tailor Welded Blanks for Air Bending Process

2012 ◽  
Vol 472-475 ◽  
pp. 761-766
Author(s):  
Yong Chuan Duan ◽  
Ying Ping Guan ◽  
Xing Dong Ma
Keyword(s):  
Finite Element ◽  
Tensile Test ◽  
Finite Element Model ◽  
Material Property ◽  
Statistical Error ◽  
Element Model ◽  
Ann Model ◽  
Process Data ◽  
Tailor Welded Blanks ◽  
Effective Material Property

A method based on artificial neural network (ANN) for predicting the effective material property is put forward in this paper. The finite element model of tensile test specimen is modeled in LS-DYNA code, which has transverse weld at the middle of the specimen and conforms to the ASTM specification. A statistical error analysis model is used to include the random phenomenon in the result of tensile test finite element model and verify the accuracy of finite element model (FEM) simulation. In order to study the effect of the processing parameter with design of experiment is followed, the simulation trail is conducted in all the levels of parameters. It is assumed that Hollomon’s law is followed by tailor welded blanks. The results obtained from fitting the post-process data of FEM by least square method are used to train and develop ANN model, the prediction average error of ANN model is acceptable compared with simulation trail.

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