Research on creep constitutive model of TC11 titanium alloy based on RBFNN
The paper is aimed to exploit a creep constitutive mode of TC11 titanium alloy based on RBF neural network. Creep testing data of TC11 titanium alloy obtained under the same temperature and different stress are considered as knowledge base and the characteristics of rheological forming of materials and radial basis function neural network (RBFNN) are also combined when exploiting the model. A part of data extracted from knowledge base is divided into two groups: one is learning sample and the other testing sample, which are being performed training, learning and simulating. Then predicting value is compared with the creep testing value and the theoretical value deduced by primary model, which validates that the RBFNN model has higher precision and generalizing ability.
RBF neural network TC11 titanium alloy creep constitution relationship numerical simulation
Xianghua Peng Yingshe Luo Jingye Zhou Min Yu Tao Luo
College of Information Engineering, Xiangtan University, Xiangtan, Hunan, 411105, China Institute of Rheological Mechanics and Material Engineering, Central South University of Forestry an College of Computer and Communication Engineering, Changsha University of Science and Technology, Ch
国际会议
郑州
英文
2007-10-23（万方平台首次上网日期，不代表论文的发表时间）