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.
Jitai NIU, Zuyan LIU, Cheng JIN and Guangtao Zhou
X. H. Peng et al., "Research on Creep Constitutive Model of TC11 Titanium Alloy Based on RBFNN", Materials Science Forum, Vols. 575-578, pp. 1050-1055, 2008