NEURAL NETWORK APPLICATION FOR STRUCTURE DESIGN OPTIMIZATION OF THIN-WALL STRUCTURES

被引：0

作者：

Kamel, Hesham ^{[1
]}

机构：

[1] Egyptian Armed Forces, Mil Tech Coll, Cairo, Egypt

来源：

PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2011, VOL 9 | 2012年

关键词：

D O I：

暂无

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Neural networks are trained to predict the response of a thin wall tube under dynamic impact loading then they are integrated with an optimization algorithm to improve the crashworthiness design of the thin wall tube. LS-DYNA is used to simulate the tube's response under dynamic impact while MATLAB is used to train the neural networks and the optimization algorithm. The results show that the suggested approach succeeded in improving the thin wall tube design at an affordable computational cost. It is suggested that the approach can be expanded for the design improvement of more complex structures.

引用

页码：41 / 45

页数：5

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