期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
APPLICATION OF ARTIFICIAL NEURAL NETWORK TO INVERSE PROBLEMS OF ESTIMATING INNER ETCH OF ELASTOPLASTIC PIPE UNDER PRESSURE
1
作者 Guan, BT Shen, CW +1 位作者 xiao, js Cai, YS 《Acta Mechanica Solida Sinica》 SCIE EI 1996年第1期88-93,共6页
To determine a variation of pipe's inner geometric shape as due to etch, the three-layered feedforward artificial neural network is used in the inverse analysis through observing the elastoplastic strains of the o... To determine a variation of pipe's inner geometric shape as due to etch, the three-layered feedforward artificial neural network is used in the inverse analysis through observing the elastoplastic strains of the outer wall under the working inner pressure. Because of different kinds of inner wail radii and eccentricity. several groups of strains calculated with computational mechanics are used for the network to do learning. Numerical calculation demonstrates that this method is effective and the estimated inner wall geometric parameters have high precision. 展开更多
关键词 artificial neural network inverse problem ELASTOPLASTIC finite element
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部