确定裂纹尖塑性区的神经网络方法  

Neural Network Method for Conforming the Plastic Region Around Carck Tip

作　　者：师俊平[1] 朱文艺[1] 

机构地区：[1]西安理工大学,西安710048

出　　处：《应用力学学报》2003年第4期151-154,共4页Chinese Journal of Applied Mechanics

基　　金：陕西省教育厅专项研究基金资助项目 ( 0 0JK2 0 5 )

摘　　要：通过构造反向传播神经网络 ,对裂纹尖端的应力场进行学习 ,进而实现对裂纹尖端应力场函数的逼近。经过学习的网格具有相当的联想、记忆能力和一定的稳定性 ,并且可以快速、准确地计算实际情况中带裂纹构件的裂纹尖端应力场 ,确定裂纹尖端的塑性区。The constructed Back-Propagation Neural Network (BPNN) can be used to learn the stress field around the crack tip. Then the approximation of the stress field around the crack tip was achieved. The trained neural network has the ability of association and memory. At the same time, it can calculate the stress field of the component with a arack in reality quickly and correctly, confirming to the plastic region. With the trained network, the component can to be analyzed easily and conveniently.

关 键 词：神经网络法 裂纹 应力场 断裂韧度 输入层 隐含层 输出层 激活函数 

分 类 号：O346.1[理学—固体力学] TP183[理学—力学]