ISSN:
1662-9752
Source:
Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
Topics:
Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
Notes:
The paper is aimed to exploit a creep constitutive mode of TC11 titanium alloy based onRBF neural network. Creep testing data of TC11 titanium alloy obtained under the same temperatureand different stress are considered as knowledge base and the characteristics of rheological formingof materials and radial basis function neural network (RBFNN) are also combined when exploitingthe model. A part of data extracted from knowledge base is divided into two groups: one is learningsample 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 byprimary model, which validates that the RBFNN model has higher precision and generalizing ability
Type of Medium:
Electronic Resource
URL:
http://www.tib-hannover.de/fulltexts/2011/0528/02/18/transtech_doi~10.4028%252Fwww.scientific.net%252FMSF.575-578.1050.pdf
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