Applications and studies on artificial neural network model for mechanical properties deposited metals

被引：0

作者：

Xue, XH ^{[1
]}

Qian, BN

Yu, SF

Guo, XM

Yang, K

Zi, BT

机构：

[1] Chinese Acad Sci, Inst Met Res, Shenyang 110016, Peoples R China

[2] Tsing Hua Univ, Dept Engn Mech, Beijing 100084, Peoples R China

来源：

ACTA METALLURGICA SINICA | 2001年 / 37卷 / 09期

关键词：

artificial neural network; deposited metal; mechanical property; alloyed element;

D O I：

暂无

中图分类号：

TF [冶金工业];

学科分类号：

0806 ;

摘要：

A mechanical property prediction model for deposited metals was built upon the experimental data with the aid of artificial neural network (ANN). There are good correlations between the predicted results and the experimental data. Using this prediction model, the effects of alloying elements C, Mn, Ti and impurity elements S, P, O, N on the low temperature toughness of deposited metals were studied, and by using orthogonal designed experiment, a good chemical constitution for deposited metal was obtained. The technique proposed can be served as a reliable tool for deposited metals property control and design.

引用

页码：947 / 951

页数：5