Paper Title:
Research on Creep Constitutive Model of TC11 Titanium Alloy Based on RBFNN
  Abstract

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.

  Info
Periodical
Materials Science Forum (Volumes 575-578)
Edited by
Jitai NIU, Zuyan LIU, Cheng JIN and Guangtao Zhou
Pages
1050-1055
DOI
10.4028/www.scientific.net/MSF.575-578.1050
Citation
X. H. Peng, Y. S. Luo, J. Y. Zhou, M. Yu, T. Luo, "Research on Creep Constitutive Model of TC11 Titanium Alloy Based on RBFNN", Materials Science Forum, Vols. 575-578, pp. 1050-1055, 2008
Online since
April 2008
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Price
$32.00
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